<?xml version="1.0" encoding="UTF-8"?>
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    <title>data-analytics</title>
    <link rel="self" type="application/atom+xml" href="https://links.biapy.com/guest/tags/352/feed"/>
    <updated>2026-04-18T09:20:42+00:00</updated>
    <id>https://links.biapy.com/guest/tags/352/feed</id>
            <entry>
            <id>https://links.biapy.com/links/12388</id>
            <title type="text"><![CDATA[OpenBB]]></title>
            <link rel="alternate" href="https://openbb.co/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12388"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Financial data platform for analysts, quants and AI agents. 
The AI Workspace for Finance.

 Bridge your data with AI. Build AI-powered analytics applications, faster, securely and on your terms. 

- [OpenBB @ GitHub](https://github.com/OpenBB-finance/OpenBB).]]>
            </summary>
            <updated>2026-04-03T12:04:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12322</id>
            <title type="text"><![CDATA[claude-pulse]]></title>
            <link rel="alternate" href="https://github.com/NoobyGains/claude-pulse" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12322"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Real-time usage monitor for Claude Code — session limits, weekly limits, and plan tier with colour-coded progress bars]]>
            </summary>
            <updated>2026-03-28T08:20:01+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12190</id>
            <title type="text"><![CDATA[pgit]]></title>
            <link rel="alternate" href="https://github.com/ImGajeed76/pgit" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12190"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Git-like version control CLI backed by PostgreSQL with pg-xpatch delta compression.

Related contents:

- [pgit: What If Your Git History Was a SQL Database? @ oseifert](https://oseifert.ch/blog/building-pgit).]]>
            </summary>
            <updated>2026-03-19T15:53:12+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12127</id>
            <title type="text"><![CDATA[nao]]></title>
            <link rel="alternate" href="https://getnao.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12127"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[the Analytics Agent built for context engineering.
Build your agent context like a file system.

Deploy a chat UI for anyone to run analytics on your data.

- [nao @ GitHub](https://github.com/getnao/nao).

Related contents:

- [SQL Is Solved. Here&amp;#039;s Where Chat-BI Still Breaks @ Ju Data Engineering Newsletter](https://juhache.substack.com/p/sql-is-solved-heres-where-chat-bi).]]>
            </summary>
            <updated>2026-03-16T07:05:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/12105</id>
            <title type="text"><![CDATA[Rudel]]></title>
            <link rel="alternate" href="https://rudel.ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/12105"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Understand how your team codes with AI.
Coding Agent Analytics for Claude Code.

Rudel gives engineering leaders visibility into Claude Code usage across their team. Track productivity, quantify ROI, and surface quality signals, automatically.

- [Rudel @ GitHub](https://github.com/obsessiondb/rudel).]]>
            </summary>
            <updated>2026-03-13T12:36:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11904</id>
            <title type="text"><![CDATA[Shaper]]></title>
            <link rel="alternate" href="https://taleshape.com/shaper/docs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11904"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source, SQL-driven Data Dashboards powered by DuckDB.

Build analytics dashboards simply by writing SQL.

- [Shaper @ GitHub](https://github.com/taleshape-com/shaper).

Related contents:

- [Digest \#202: Terraform Claude Skills, FinOps FOCUS 1.2, AI Fatigue for Cloud Engineers, and MCP for Web Data Extraction @ DevOps Bulletin](https://www.devopsbulletin.com/p/digest-202-terraform-claude-skills).]]>
            </summary>
            <updated>2026-02-24T07:10:47+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11722</id>
            <title type="text"><![CDATA[phptop]]></title>
            <link rel="alternate" href="https://github.com/bearstech/phptop" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11722"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[PHP basic ressource profiler (CPU/memory), safe and useful for production sites.

phptop prints per query and average metrics comparable to &amp;#039;time&amp;#039; (wallclock, user and system CPU time) along with memory and other ressource usages.

It can be easily globally activated on a LAMP server and requires little resources and a single line configuration change in your php.ini. It has been used by Bearstech on many production servers for years without any problems.]]>
            </summary>
            <updated>2026-02-06T10:22:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11652</id>
            <title type="text"><![CDATA[kube-opex-analytics]]></title>
            <link rel="alternate" href="https://github.com/rchakode/kube-opex-analytics" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11652"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Kubernetes usage analytics for CPU, Memory, and GPU — track costs and optimize cluster resources.

kube-opex-analytics is a Kubernetes usage accounting and analytics tool that helps organizations track CPU, Memory, and GPU resources consumed by their clusters over time (hourly, daily, monthly).]]>
            </summary>
            <updated>2026-01-30T12:54:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11631</id>
            <title type="text"><![CDATA[Microsoft Fabric]]></title>
            <link rel="alternate" href="https://www.microsoft.com/en-us/microsoft-fabric" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11631"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Data Analytics Platform.

Related conttens:

- [Qu&amp;#039;est-ce que Microsoft Fabric ? @ datacamp :fr:](https://www.datacamp.com/fr/blog/what-is-microsoft-fabric).]]>
            </summary>
            <updated>2026-01-27T11:05:00+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11493</id>
            <title type="text"><![CDATA[Sortarr]]></title>
            <link rel="alternate" href="https://github.com/Jaredharper1/Sortarr" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11493"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Sonarr &amp;amp; Radarr Media Library Insights.

Sortarr is a lightweight web dashboard for Sonarr and Radarr that helps you understand how your media library uses storage. It is not a Plex tool, but it is useful in Plex setups for spotting oversized series or movies and comparing quality vs. size trade-offs.]]>
            </summary>
            <updated>2026-01-16T13:44:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/11421</id>
            <title type="text"><![CDATA[Apache Spark]]></title>
            <link rel="alternate" href="https://spark.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/11421"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Unified Engine for large-scale data analytics.

Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. 

- [Apache Spark @ GitHub](https://github.com/apache/spark).

Related contents:

- [Introducing Apache Spark® 4.1 @ databricks](https://www.databricks.com/blog/introducing-apache-sparkr-41).
- [From Chaos to Scale: Templatizing Spark Declarative Pipelines with DLT-META @ databricks](https://www.databricks.com/blog/chaos-scale-templatizing-spark-declarative-pipelines-dlt-meta).
- [Breaking the Microbatch Barrier: The Architecture of Apache Spark Real-Time Mode @ databricks](https://www.databricks.com/blog/breaking-microbatch-barrier-architecture-apache-spark-real-time-mode).]]>
            </summary>
            <updated>2026-03-17T12:31:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10889</id>
            <title type="text"><![CDATA[Deepnote]]></title>
            <link rel="alternate" href="https://deepnote.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10889"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Analytics and data science notebook for teams. Jupyter notebook  for the AI era.

- Link Snowflake, BigQuery, CSVs, and 60+ data sources
- Write in Python, SQL, R — or just prompt Deepnote Agent
- Build powerful data apps and dashboards with AI

- [Deepnote @ GitHub](https://github.com/deepnote/deepnote).]]>
            </summary>
            <updated>2025-11-05T13:06:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10874</id>
            <title type="text"><![CDATA[xlsxsql]]></title>
            <link rel="alternate" href="https://github.com/noborus/xlsxsql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10874"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A CLI tool that executes SQL queries on xlsx files and outputs the results to various files, and also executes SQL queries on various files and outputs them to xlsx files.]]>
            </summary>
            <updated>2025-11-04T07:19:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10523</id>
            <title type="text"><![CDATA[Cially]]></title>
            <link rel="alternate" href="https://cially.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10523"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Discord AnalyticsMade Simple

Cially is an open-source Discord Server Stats dashboard that provides real-time insights, member activity tracking, and detailed server statistics to help you understand and optimize your Discord community.

 🪼Cially is a powerful, open-source dashboard designed to provide in-depth insights, real-time analytics, and detailed statistics for your Discord server. Monitor member activity, track engagement trends, and make data-driven decisions with ease. 

- [Cially @ GitHub](https://github.com/cially/cially).]]>
            </summary>
            <updated>2025-10-06T05:57:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10398</id>
            <title type="text"><![CDATA[pepy.tech]]></title>
            <link rel="alternate" href="https://pepy.tech/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10398"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[PyPI Package Statistics &amp;amp; Analytics

Track downloads, analyze trends, and gain insights into the Python ecosystem]]>
            </summary>
            <updated>2025-09-26T05:57:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10396</id>
            <title type="text"><![CDATA[SedonaDB]]></title>
            <link rel="alternate" href="https://sedona.apache.org/sedonadb/latest/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10396"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[SedonaDB is an open-source single-node analytical database engine with geospatial as a first-class citizen. It aims to deliver the fastest spatial analytics query speed and the most comprehensive function coverage available.

- [SedonaDB @ GitHub](https://github.com/apache/sedona-db).

Related contents:

- [Introducing SedonaDB: A single-node analytical database engine with geospatial as a first-class citizen @ Apache Sedona](https://sedona.apache.org/latest/blog/2025/09/24/introducing-sedonadb-a-single-node-analytical-database-engine-with-geospatial-as-a-first-class-citizen/).]]>
            </summary>
            <updated>2025-10-03T11:20:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10238</id>
            <title type="text"><![CDATA[Semlib]]></title>
            <link rel="alternate" href="https://semlib.anish.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10238"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Semantic Data Processing.
Build data processing and data analysis pipelines that leverage the power of LLMs 🧠 

Semlib is a Python library for building data processing and data analysis pipelines that leverage the power of large language models (LLMs). Semlib provides, as building blocks, familiar functional programming primitives like map, reduce, sort, and filter, but with a twist: Semlib&amp;#039;s implementation of these operations are programmed with natural language descriptions rather than code. Under the hood, Semlib handles complexities such as prompting, parsing, concurrency control, caching, and cost tracking.

- [Semlib @ GitHub](https://github.com/anishathalye/semlib).]]>
            </summary>
            <updated>2025-09-16T12:17:48+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/10095</id>
            <title type="text"><![CDATA[pandas]]></title>
            <link rel="alternate" href="https://pandas.pydata.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/10095"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Python Data Analysis Library.

pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool.
 Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more 

- [pandas @ GitHub](https://github.com/pandas-dev/pandas).

Related contents:

- [Leveraging Pandas and SQL Together for Efficient Data Analysis @ KD nuggets](https://www.kdnuggets.com/leveraging-pandas-and-sql-together-for-efficient-data-analysis).
- [I Cleaned a Messy CSV File Using Pandas .  Here’s the Exact Process I Follow Every Time. @ towards data science](https://towardsdatascience.com/i-cleaned-a-messy-csv-file-using-pandas-heres-the-exact-process-i-follow-every-time/).]]>
            </summary>
            <updated>2025-12-12T13:33:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/182</id>
            <title type="text"><![CDATA[GitHub Readme Stats]]></title>
            <link rel="alternate" href="https://github.com/anuraghazra/github-readme-stats" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/182"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[⚡ Dynamically generated stats for your github readmes.

Related contents:

- [EP 61: Coding in My Pants @ Linux Matters](https://linuxmatters.sh/61/).]]>
            </summary>
            <updated>2025-09-18T15:25:41+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/212</id>
            <title type="text"><![CDATA[Observable Framework]]></title>
            <link rel="alternate" href="https://observablehq.com/framework/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/212"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The best dashboards are built with code.
Create fast, beautiful data apps, dashboards, and reports from the command line. Write Markdown, JavaScript, SQL, Python, R… and any language you like. Free and open-source.

A static site generator for data apps, dashboards, reports, and more. Observable Framework combines JavaScript on the front-end for interactive graphics with any language on the back-end for data analysis. 

- [Observable Framework @ GitHub](https://github.com/observablehq/framework).]]>
            </summary>
            <updated>2025-10-21T14:50:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/239</id>
            <title type="text"><![CDATA[Lampyre :ru:]]></title>
            <link rel="alternate" href="https://lampyre.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/239"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Data analysis &amp;amp; OSINT tool for everyone.

**warning:** created by ex-employee of the FSB

Related contents:

- [Episode \#509: Les dangers de l’OSINT @ NoLimitSecu :fr:](https://www.nolimitsecu.fr/les-dangers-de-losint/).]]>
            </summary>
            <updated>2025-12-09T09:20:53+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/454</id>
            <title type="text"><![CDATA[GIT quick statistics]]></title>
            <link rel="alternate" href="https://git-quick-stats.sh/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/454"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Simple way to access various statistics in git repository. 
Git quick statistics is a simple and efficient way to access various statistics in git repository. 

Any git repository may contain tons of information about commits, contributors, and files. Extracting this information is not always trivial, mostly because there are a gadzillion options to a gadzillion git commands - I don&amp;#039;t think there is a single person alive who knows them all. Probably not even Linus Torvalds himself :).

- [GIT quick statistics @ GitHub](https://github.com/git-quick-stats/git-quick-stats).]]>
            </summary>
            <updated>2025-08-28T17:13:55+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/539</id>
            <title type="text"><![CDATA[Shinar]]></title>
            <link rel="alternate" href="https://github.com/Chivo-Systems/Shinar/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/539"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AI Call Analytics.
Clean, annotate, and summarize call transcripts with GPT-4.5.

Open Source AI Calling Transcriptions, Summaries, and Analytics built on OpenAI Whisper.]]>
            </summary>
            <updated>2025-08-28T17:27:58+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/723</id>
            <title type="text"><![CDATA[Gmail to SQLite]]></title>
            <link rel="alternate" href="https://github.com/marcboeker/gmail-to-sqlite" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/723"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Index your Gmail account to a SQLite DB and play with the data. 

This is a script to download emails from Gmail and store them in a SQLite database for further analysis. I find it extremely useful to have all my emails in a database to run queries on them. For example, I can find out how many emails I received per sender, which emails take the most space, and which emails from which sender I never read.]]>
            </summary>
            <updated>2025-08-28T17:58:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/754</id>
            <title type="text"><![CDATA[TextQuery]]></title>
            <link rel="alternate" href="https://textquery.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/754"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[All-in-One Desktop App to Analyze Data Locally.

TextQuery is an all-in-one desktop app to import, query, modify, and visualize your raw data with SQL.]]>
            </summary>
            <updated>2025-08-28T18:03:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/780</id>
            <title type="text"><![CDATA[Hyperparam]]></title>
            <link rel="alternate" href="https://hyperparam.app/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/780"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Look At Your Data 👀.

Data quality is the most important factor in machine learning success. Hyperparam brings exploration and analysis of massive text datasets to the browser.

- [Hyperparam @ GitHub](https://github.com/hyparam).]]>
            </summary>
            <updated>2025-08-28T18:07:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/809</id>
            <title type="text"><![CDATA[Apache Doris]]></title>
            <link rel="alternate" href="https://doris.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/809"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open source data warehouse for real time data analytics.

Apache Doris is an easy-to-use, high-performance and real-time analytical database based on MPP architecture, known for its extreme speed and ease of use. It only requires a sub-second response time to return query results under massive data and can support not only high-concurrency point query scenarios but also high-throughput complex analysis scenarios.

- [Apache Doris @ GitHub](https://github.com/apache/doris).]]>
            </summary>
            <updated>2025-08-28T18:12:23+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/847</id>
            <title type="text"><![CDATA[Moose]]></title>
            <link rel="alternate" href="https://docs.fiveonefour.com/moose" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/847"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Moose lets you develop analytical backends in pure TypeScript or Python code.
The developer framework for your data &amp;amp; analytics stack.

Moose is an open source developer framework for building analytical backends. Moose is designed to help you quickly prototype, productionize, and scale data products, data pipelines, and data APIs - on OLAP and streaming infrastructure - using native TypeScript or Python.

- [Moose @ GitHub](https://github.com/514-labs/moose).]]>
            </summary>
            <updated>2025-08-28T18:18:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1211</id>
            <title type="text"><![CDATA[Quacklytics]]></title>
            <link rel="alternate" href="https://github.com/xz3dev/quacklytics" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1211"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Quacklytics is an open-source analytics service built using DuckDB and designed to run analytical queries directly inside your browser. It provides a seamless, lightweight, and high-performance way to process your data without the need for expensive server-side compute resources.]]>
            </summary>
            <updated>2025-08-28T19:18:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1442</id>
            <title type="text"><![CDATA[R]]></title>
            <link rel="alternate" href="https://www.r-project.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1442"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The R Project for Statistical Computing.

R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.

Related contents:

- [Episode 608: R With Eric Nantz @ Coder Radio](https://coder.show/608).
- [R Weekly Highlights](https://serve.podhome.fm/r-weekly-highlights).
- [R Podcast](https://r-podcast.org).
- [If all the world were a monorepo @ Julie&amp;#039;s Substack](https://jtibs.substack.com/p/if-all-the-world-were-a-monorepo).
- [Python is not a great language for data science. Part 1: The experience @ Genes, Minds, Machines](https://blog.genesmindsmachines.com/p/python-is-not-a-great-language-for).]]>
            </summary>
            <updated>2025-11-26T13:15:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1531</id>
            <title type="text"><![CDATA[Visprex]]></title>
            <link rel="alternate" href="https://www.visprex.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1531"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Visualise your CSV files in seconds without sending your data anywhere.

- [Visprex documentation](https://docs.visprex.com/).
- [Visprex @ GitHub](https://github.com/visprex/visprex).]]>
            </summary>
            <updated>2025-08-28T20:11:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1576</id>
            <title type="text"><![CDATA[BirdNET-Analyzer]]></title>
            <link rel="alternate" href="https://kahst.github.io/BirdNET-Analyzer/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1576"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[BirdNET-Analyzer is an open source tool for analyzing bird calls using machine learning models. It can process large amounts of audio recordings and identify (bird) species based on their calls.

- [BirdNET-Analyzer @ GitHub](https://github.com/kahst/BirdNET-Analyzer).]]>
            </summary>
            <updated>2025-08-28T20:19:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1597</id>
            <title type="text"><![CDATA[GarminDB]]></title>
            <link rel="alternate" href="https://github.com/tcgoetz/GarminDB" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1597"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Download and parse data from Garmin Connect or a Garmin watch, FitBit CSV, and MS Health CSV files into and analyze data in Sqlite serverless databases with Jupyter notebooks. 

Python scripts for parsing health data into and manipulating data in a SQLite database. SQLite is a light weight database that doesn&amp;#039;t require a server.

Related contents:

- [Episode 601: Taming the Demons @ Linux Unplugged](https://linuxunplugged.com/601).]]>
            </summary>
            <updated>2025-08-28T20:23:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1621</id>
            <title type="text"><![CDATA[Tokei]]></title>
            <link rel="alternate" href="https://github.com/XAMPPRocky/tokei" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1621"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Count your code, quickly. 

Tokei is a program that displays statistics about your code. Tokei will show the number of files, total lines within those files and code, comments, and blanks grouped by language.

- [Tokei - Enfin des stats sur votre code @ Korben :fr:](https://korben.info/tokei-compteur-code-optimisation-projets.html).]]>
            </summary>
            <updated>2025-08-28T20:27:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1736</id>
            <title type="text"><![CDATA[SQLMesh]]></title>
            <link rel="alternate" href="https://sqlmesh.readthedocs.io/en/stable/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1736"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Efficient data transformation and modeling framework that is backwards compatible with dbt.

SQLMesh is a next-generation data transformation framework designed to ship data quickly, efficiently, and without error. Data teams can efficiently run and deploy data transformations written in SQL or Python with visibility and control at any size.

- [SQLMesh @ GitHub](https://github.com/TobikoData/sqlmesh).

Related contents:

- [Why SQLMesh Might be The Best dbt Alternative @ The Data Toolbox](https://thedatatoolbox.substack.com/p/why-sqlmesh-might-be-the-best-dbt).]]>
            </summary>
            <updated>2025-08-28T20:45:46+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1757</id>
            <title type="text"><![CDATA[Our World in Data]]></title>
            <link rel="alternate" href="https://ourworldindata.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1757"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Research and data to make progress against the world’s largest problems.

To make progress against the pressing problems the world faces, we need to be informed by the best research and data.

Our World in Data makes this knowledge accessible and understandable, to empower those working to build a better world.]]>
            </summary>
            <updated>2025-08-28T20:48:50+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1921</id>
            <title type="text"><![CDATA[Stata]]></title>
            <link rel="alternate" href="https://www.stata.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1921"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your data tell a story. Explore. Visualize. Model. Make a difference.
Better insight starts with Stata.

Stata is statistical software for data science.]]>
            </summary>
            <updated>2025-08-28T21:16:11+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1949</id>
            <title type="text"><![CDATA[Apache Pinot™]]></title>
            <link rel="alternate" href="https://pinot.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1949"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Insights, Unlocked in Real Time.

Apache Pinot™: The real-time analytics open source platform for lightning-fast insights, effortless scaling, and cost-effective data-driven decisions.

- [Apache Pinot @ GitHub](https://github.com/apache/pinot).

Related contents:

- [Serving Millions of Apache Pinot™ Queries with Neutrino @ Uber Blog](https://www.uber.com/en-FR/blog/serving-millions-of-apache-pinot-queries-with-neutrino/?uclick_id=ed80e0fe-d305-48c1-b7e9-ed149ec25b99).]]>
            </summary>
            <updated>2025-08-28T21:21:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/1950</id>
            <title type="text"><![CDATA[structured-logprobs]]></title>
            <link rel="alternate" href="https://arena-ai.github.io/structured-logprobs/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/1950"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[structured-logprobs is an open-source Python library that enhances OpenAI&amp;#039;s structured outputs by providing detailed information about token log probabilities.

This library is designed to offer valuable insights into the reliability of an LLM&amp;#039;s structured outputs. It works with OpenAI&amp;#039;s Structured Outputs, a feature that ensures the model consistently generates responses adhering to a supplied JSON Schema. This eliminates concerns about missing required keys or hallucinating invalid values.

- [structured-logprobs @ GitHub](https://github.com/arena-ai/structured-logprobs).]]>
            </summary>
            <updated>2025-08-28T21:21:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2010</id>
            <title type="text"><![CDATA[Angle-grinder]]></title>
            <link rel="alternate" href="https://github.com/rcoh/angle-grinder" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2010"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Slice and dice log files on the command line.

Angle-grinder allows you to parse, aggregate, sum, average, min/max, percentile, and sort your data. You can see it, live-updating, in your terminal. Angle grinder is designed for when, for whatever reason, you don&amp;#039;t have your data in graphite/honeycomb/kibana/sumologic/splunk/etc. but still want to be able to do sophisticated analytics.

Related contents:

- [A list of new(ish) command line tools @ Julia Evans](https://jvns.ca/blog/2022/04/12/a-list-of-new-ish--command-line-tools/).]]>
            </summary>
            <updated>2025-08-28T21:32:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2024</id>
            <title type="text"><![CDATA[📊 A-Packets]]></title>
            <link rel="alternate" href="https://apackets.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2024"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Online PCAP Analysis and Network Traffic Insights.

Effortless PCAP File Analysis in Your Browser

Explore and analyze PCAP files online using A-Packets, designed to provide comprehensive insights into network protocols like IPv4/IPv6, HTTP, Telnet, FTP, DNS, SSDP, and WPA2. This tool allows users to easily view details of network communications and dissect layers of data transmission.]]>
            </summary>
            <updated>2025-08-28T21:33:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2057</id>
            <title type="text"><![CDATA[Paperless-AI]]></title>
            <link rel="alternate" href="https://clusterzx.github.io/paperless-ai/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2057"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[An automated document analyzer for Paperless-ngx using OpenAI API and Ollama (Mistral, llama, phi 3, gemma 2) to automatically analyze and tag your documents.

 It features: Automode, Manual Mode, Ollama and OpenAI, a Chat function to query your documents with AI, a modern and intuitive Webinterface.

- [Paperless-AI @ GitHub](https://github.com/clusterzx/paperless-ai).]]>
            </summary>
            <updated>2025-08-28T21:40:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2077</id>
            <title type="text"><![CDATA[git-of-theseus]]></title>
            <link rel="alternate" href="https://github.com/erikbern/git-of-theseus" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2077"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Analyze how a Git repo grows over time.]]>
            </summary>
            <updated>2025-08-28T21:42:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2119</id>
            <title type="text"><![CDATA[Gravity]]></title>
            <link rel="alternate" href="https://www.smartesting.com/en/gravity/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2119"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Empower your testing with AI &amp;amp; usage insights.

Gravity monitors real-world user behaviors and usage patterns in live production and test environments to generate quality analytics, identify test coverage gaps, and assist in prioritizing and generating test cases.]]>
            </summary>
            <updated>2025-08-28T21:49:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2132</id>
            <title type="text"><![CDATA[AIL-Framework]]></title>
            <link rel="alternate" href="https://github.com/supdevinci/ail-framework-docker" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2132"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[AIL-Framework is a powerful open-source project designed for online data analysis and web crawling, tailored for cybersecurity researchers and analysts.

Related contents:

- [1 Tools en 5 commandes @ Laurent Biagotti&amp;#039;s LinkedIn :fr:](https://www.linkedin.com/posts/laurent-biagiotti-19779284_1-%F0%9D%97%A7%F0%9D%97%BC%F0%9D%97%BC%F0%9D%97%B9%F0%9D%98%80-en-5-%F0%9D%97%96%F0%9D%97%BC%F0%9D%97%BA%F0%9D%97%BA%F0%9D%97%AE%F0%9D%97%BB%F0%9D%97%B1%F0%9D%97%B2%F0%9D%98%80-et-activity-7281937762511929344-MiOX/).]]>
            </summary>
            <updated>2025-08-28T21:52:26+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2179</id>
            <title type="text"><![CDATA[Tirreno]]></title>
            <link rel="alternate" href="https://www.tirreno.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2179"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Know Your User™

Open source user analytics
for sovereign cybersecurity.

Tirreno is open-source user analytics software.

Tirreno is a universal analytic tool for monitoring online platforms, web applications, SaaS, communities, IoT, mobile applications, intranets, and e-commerce websites. It is effective against external threats associated with partners or customers, as well as internal risks posed by employees or suppliers.

- [Tirreno @ GitHub](https://github.com/TirrenoTechnologies/tirreno).]]>
            </summary>
            <updated>2025-08-28T22:00:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2203</id>
            <title type="text"><![CDATA[Glean]]></title>
            <link rel="alternate" href="https://glean.software/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2203"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[System for collecting, deriving and querying facts about source code.

Glean is a system for working with facts about source code. You can use it for:

- Collecting and storing detailed information about code structure. Glean is designed around an efficient storage model that enables storing information about code at scale.
- Querying information about code, to power tools and experiences from online IDE features to offline code analysis.

- [Glean @ GitHub](https://github.com/facebookincubator/glean).

Source: [Indexing code at scale with Glean @ Engineering at Meta](https://engineering.fb.com/2024/12/19/developer-tools/glean-open-source-code-indexing/).]]>
            </summary>
            <updated>2025-08-28T22:04:33+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2222</id>
            <title type="text"><![CDATA[SDF Labs]]></title>
            <link rel="alternate" href="https://www.sdf.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2222"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Data Runs Better on SDF. Transform Data Better with SDF.
SDF is the fastest way to build a scalable, reliable, and optimized data warehouse.

SDF is a developer platform for data that scales SQL understanding across an organization, empowering all data teams to unlock the full potential of their data.

SDF is a multi-dialect SQL compiler, transformation framework, and analytical database engine. It natively compiles SQL dialects, like Snowflake, and connects to their corresponding data warehouses to materialize models.

- [SDF Docs](https://docs.sdf.com/).
- [SDF @ GitHub](https://github.com/sdf-labs/sdf-cli).

Source: [Testing is Not Enough: Transforming Data Quality with Write, Audit, Publish using SDF Build @ SDF Blog](https://blog.sdf.com/p/testing-is-not-enough-transforming).]]>
            </summary>
            <updated>2025-08-28T22:06:34+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2490</id>
            <title type="text"><![CDATA[Wren AI]]></title>
            <link rel="alternate" href="https://getwren.ai/oss" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2490"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open-source sQL AI Agent. Text2SQL made Easy!

Wren AI is an open-source SQL AI Agent that empowers data, product, and business teams to access insights through AI chat, built-in well designed intuitive UI and UX, integrating seamlessly with tools like Excel and Google Sheets.

- [Wren AI @ GitHub](https://github.com/Canner/WrenAI).]]>
            </summary>
            <updated>2025-08-28T22:50:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2586</id>
            <title type="text"><![CDATA[Apache Arrow]]></title>
            <link rel="alternate" href="https://arrow.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2586"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics.

Apache Arrow defines a language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs. The Arrow memory format also supports zero-copy reads for lightning-fast data access without serialization overhead.

- [Apache Arrow @ GitHub](https://github.com/apache/arrow/).
- [arrow-rs @ GitHub](https://github.com/apache/arrow-rs).

Related contents:

- [Fast columnar JSON decoding with arrow-rs @ arroyo](https://www.arroyo.dev/blog/fast-arrow-json-decoding).
- [I spent 6 hours learning Apache Arrow: Overview @ Data Engineer Things&amp;#039;s Medium](https://blog.det.life/i-spent-6-hours-learning-apache-arrow-overview-e7f3b8ee85b2).]]>
            </summary>
            <updated>2025-08-28T23:07:06+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2764</id>
            <title type="text"><![CDATA[pgBadger]]></title>
            <link rel="alternate" href="https://pgbadger.darold.net/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2764"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[PostgreSQL log analyzer.

_pgBadger_ is a PostgreSQL log analyzer built for speed with fully detailed
reports and professional rendering.

- [pgBadger @ GitHub](https://github.com/darold/pgbadger/).
- [Linux Pratique - Supervision d&amp;#039;une instance PostgreSQL @ Dalibo :fr:](https://blog.dalibo.com/2024/11/18/lp4.html).
- [Analyse des traces de PostgreSQL avec pgBadger @ Diamond Connect :fr:](https://connect.ed-diamond.com/linux-pratique/lphs-054/analyse-des-traces-de-postgresql-avec-pgbadger).]]>
            </summary>
            <updated>2025-08-28T23:37:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2853</id>
            <title type="text"><![CDATA[Databricks]]></title>
            <link rel="alternate" href="https://www.databricks.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2853"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Databricks Data Intelligence Platform.
Databricks brings AI to your data to help you bring AI to the world.

Related contents:

- [SQL Gets Easier: Announcing New Pipe Syntax @ Databricks blog](https://www.databricks.com/blog/sql-gets-easier-announcing-new-pipe-syntax).]]>
            </summary>
            <updated>2025-08-28T23:53:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2873</id>
            <title type="text"><![CDATA[Graphic Walker]]></title>
            <link rel="alternate" href="https://docs.kanaries.net/graphic-walker" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2873"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Graphic Walker is a different open-source alternative to Tableau. It allows data scientists to analyze data and visualize patterns with simple drag-and-drop / natural language query operations.

- [Graphic Walker @ GitHub](https://github.com/Kanaries/graphic-walker).]]>
            </summary>
            <updated>2025-08-28T23:55:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2874</id>
            <title type="text"><![CDATA[Panel Graphic Walker]]></title>
            <link rel="alternate" href="https://github.com/panel-extensions/panel-graphic-walker" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2874"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[A project providing a Graphic Walker Pane for use with HoloViz Panel. 

A simple way to explore your data through a Tableau-like interface directly in your Panel data applications.

panel-graphic-walker brings the power of Graphic Walker to your data science workflow, seamlessly integrating interactive data exploration into notebooks and Panel applications. Effortlessly create dynamic visualizations, analyze datasets, and build dashboards—all within a Pythonic, intuitive interface.]]>
            </summary>
            <updated>2025-08-28T23:55:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2878</id>
            <title type="text"><![CDATA[DataEase]]></title>
            <link rel="alternate" href="https://dataease.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2878"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[DataEase is an open source data visualization analysis tool that helps users quickly analyze data and gain insights into business trends, thereby improving and optimizing their business. DataEase supports a wide range of data source connections, can quickly create charts by dragging and dropping, and can be easily shared with others.

- [DataEase @ GitHub](https://github.com/dataease/dataease).]]>
            </summary>
            <updated>2025-08-28T23:57:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2931</id>
            <title type="text"><![CDATA[BemiDB]]></title>
            <link rel="alternate" href="https://bemidb.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2931"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Zero-ETL data analytics with Postgres.

Simple and cost-effective cloud analytics platform automatically synced with your data sources.

BemiDB is a Postgres read replica optimized for analytics. It consists of a single binary that seamlessly connects to a Postgres database, replicates the data in a compressed columnar format, and allows you to run complex queries using its Postgres-compatible analytical query engine.

- [BemiDB @ GitHub](https://github.com/BemiHQ/BemiDB).]]>
            </summary>
            <updated>2025-08-29T00:06:42+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2940</id>
            <title type="text"><![CDATA[Evidence]]></title>
            <link rel="alternate" href="https://evidence.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2940"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Business Intelligence as Code. Build polished data products with SQL.
Build fast, interactive data visualizations in pure SQL and markdown.

Evidence is a lightweight framework for building data apps. It&amp;#039;s open source and free to get started.

- [Evidence @ GitHub](https://github.com/evidence-dev/evidence).]]>
            </summary>
            <updated>2025-08-29T00:07:18+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2942</id>
            <title type="text"><![CDATA[OpenMetadata]]></title>
            <link rel="alternate" href="https://open-metadata.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2942"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open and unified metadata platform for data discovery, observability, and governance.

A single place for all your data and all your data practitioners to build and manage high quality data assets at scale. Built by Collate and the founders of Apache Hadoop, Apache Atlas, and Uber Databook.

OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration. 

OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration. It is one of the fastest-growing open-source projects with a vibrant community and adoption by a diverse set of companies in a variety of industry verticals. Based on Open Metadata Standards and APIs, supporting connectors to a wide range of data services, OpenMetadata enables end-to-end metadata management, giving you the freedom to unlock the value of your data assets.

- [OpenMetadata @ GitHub](https://github.com/open-metadata/OpenMetadata).]]>
            </summary>
            <updated>2025-08-29T00:07:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/2943</id>
            <title type="text"><![CDATA[data stack in a box]]></title>
            <link rel="alternate" href="https://github.com/wisemuffin/nsw-doe-data-stack-in-a-box" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/2943"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Department of Education (DOE) for New South Wales (AUS) data stack in a box.
With the push of one button you can have your own data stack up and running in 5 mins! 🏎️.

- [Data Stack in a Box — New South Wales Department of Education (ft. DuckDB, Dagster, dbt, dlt and Evidence.dev) @ David Griffiths&amp;#039; Medium](https://davidgriffiths-data.medium.com/data-stack-in-a-box-new-south-wales-department-of-education-ft-e2bd12840d3e).
- [Your November Dose of Data - November 2024 @ Data Council](https://mailchi.mp/datacouncil/october-6416684).]]>
            </summary>
            <updated>2025-08-29T00:07:21+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3100</id>
            <title type="text"><![CDATA[Anyquery]]></title>
            <link rel="alternate" href="https://anyquery.dev/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3100"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Use SQL for everything. Query anything with old-school cool SQL.

Anyquery is a CLI tool to run SQL queries on any data source, no matter if it&amp;#039;s a file, an API, logs, or a local app.
See the integrations for the full extent of what you can do. 

- [Anyquery @ GitHub](https://github.com/julien040/anyquery).]]>
            </summary>
            <updated>2025-08-29T00:33:25+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3307</id>
            <title type="text"><![CDATA[Snowflake]]></title>
            <link rel="alternate" href="https://www.snowflake.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3307"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[The Snowflake AI Data Cloud - Mobilize Data, Apps, and AI.
Snowflake delivers ease of use, instant elasticity, and lower TCO.

- [How to make Product give a shit about your architecture proposal @ Andy G&amp;#039;s Blog](https://gieseanw.wordpress.com/2024/10/09/how-to-make-product-give-a-shit-about-your-architecture-proposal/).]]>
            </summary>
            <updated>2025-08-29T01:08:51+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3315</id>
            <title type="text"><![CDATA[Redash]]></title>
            <link rel="alternate" href="https://redash.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3315"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Redash helps you make sense of your data.  Make Your Company Data Driven.
Connect and query your data sources, build dashboards to visualize data and share them with your company.

Redash is designed to enable anyone, regardless of the level of technical sophistication, to harness the power of data big and small. SQL users leverage Redash to explore, query, visualize, and share data from any data sources. Their work in turn enables anybody in their organization to use the data. Every day, millions of users at thousands of organizations around the world use Redash to develop insights and make data-driven decisions.

- [Redash @ GitHub](https://github.com/getredash/redash).]]>
            </summary>
            <updated>2025-08-29T01:08:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3316</id>
            <title type="text"><![CDATA[Apache Kylin]]></title>
            <link rel="alternate" href="https://kylin.apache.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3316"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Kylin is a high concurrency, high performance and intelligent OLAP engine that provides low-cost and ultimate data analytics experience.

- [Apache Kylin @ GitHub](https://github.com/apache/kylin).
- [#3 Mettre à disposition la donnée lorsque l&amp;#039;on est Data Engineer @ Data-Crafting.io Newsletter :fr:](https://datacrafting.substack.com/p/3-mettre-a-disposition-la-donnee).]]>
            </summary>
            <updated>2025-08-29T01:08:59+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3396</id>
            <title type="text"><![CDATA[Proof of SQL]]></title>
            <link rel="alternate" href="https://github.com/spaceandtimelabs/sxt-proof-of-sql" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3396"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Proof of SQL is a high performance zero knowledge (ZK) prover developed by the Space and Time team, which cryptographically guarantees SQL queries were computed accurately against untampered data. It targets online latencies while proving computations over entire chain histories, an order of magnitude faster than state-of-the art zkVMs and coprocessors.]]>
            </summary>
            <updated>2025-08-29T01:22:57+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3575</id>
            <title type="text"><![CDATA[Zircolite]]></title>
            <link rel="alternate" href="https://wagga40.github.io/Zircolite/#/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3575"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Zircolite is a standalone tool written in Python 3. It allows to use SIGMA rules on : MS Windows EVTX (EVTX, XML and JSONL format), Auditd logs, Sysmon for Linux and EVTXtract logs.

- [Zircolite @ GitHub](https://github.com/wagga40/Zircolite).]]>
            </summary>
            <updated>2025-08-29T01:53:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3739</id>
            <title type="text"><![CDATA[Data For Good]]></title>
            <link rel="alternate" href="https://dataforgood.fr/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3739"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Les technologies numériques sont incroyablement puissantes et redéfinissent le fonctionnement de notre société. Pour les acteurs qui œuvrent pour l&amp;#039;intérêt général, la technologie peut parfois être un levier démutiplicateur d&amp;#039;impacts positifs, cependant et malheureusement ces acteurs n&amp;#039;ont souvent pas les ressources technologiques ou humaines pour accélérer leur action citoyenne. Data for Good existe pour rétablir l&amp;#039;équilibre.

- [286 - Data &amp;amp; Dev - Christophe Blefari @ &amp;lt;ifttd&amp;gt; :fr:](https://www.ifttd.io/episodes/data-dev).
- [289 - Data 4 Good - Ronan Sy @ &amp;lt;ifttd&amp;gt; :fr:](https://www.ifttd.io/episodes/data-4-good).]]>
            </summary>
            <updated>2025-08-29T02:19:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/3741</id>
            <title type="text"><![CDATA[Amazon Athena]]></title>
            <link rel="alternate" href="https://aws.amazon.com/athena/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/3741"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Interactive SQL. Analyze petabyte-scale data where it lives with ease and flexibility.

Amazon Athena is a serverless, interactive analytics service built on open-source frameworks, supporting open-table and file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. Analyze data or build applications from an Amazon Simple Storage Service (S3) data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python. Athena is built on open-source Trino and Presto engines and Apache Spark frameworks, with no provisioning or configuration effort required.

- [286 - Data &amp;amp; Dev - Christophe Blefari @ &amp;lt;ifttd&amp;gt; :fr:](https://www.ifttd.io/episodes/data-dev).]]>
            </summary>
            <updated>2025-08-29T02:21:28+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4517</id>
            <title type="text"><![CDATA[First Pull Request]]></title>
            <link rel="alternate" href="https://firstpr.me/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4517"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[What was the first pull request you sent on GitHub?]]>
            </summary>
            <updated>2025-08-29T04:30:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4828</id>
            <title type="text"><![CDATA[Apache Tika bindings for PHP]]></title>
            <link rel="alternate" href="https://github.com/vaites/php-apache-tika" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4828"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Apache Tika bindings for PHP: extract text and metadata from documents, images and other formats.

The Apache Tika™ toolkit detects and extracts metadata and text from over a thousand different file types (such as PPT, XLS, and PDF).]]>
            </summary>
            <updated>2025-08-29T05:23:03+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4877</id>
            <title type="text"><![CDATA[The Grand Complete Data Science Guide With Videos And Materials]]></title>
            <link rel="alternate" href="https://github.com/krishnaik06/The-Grand-Complete-Data-Science-Materials" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4877"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Contribute to krishnaik06/The-Grand-Complete-Data-Science-Materials development by creating an account on GitHub.]]>
            </summary>
            <updated>2025-08-29T05:31:07+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4897</id>
            <title type="text"><![CDATA[GlareDB]]></title>
            <link rel="alternate" href="https://glaredb.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4897"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Your Data Pipeline, Simplified.  GlareDB: An analytics DBMS for distributed data.

Data exists everywhere: your laptop, Postgres, Snowflake and as files in S3. It exists in various formats such as Parquet, CSV and JSON. Regardless, there will always be multiple steps spanning several destinations to get the insights you need.

GlareDB is designed to query your data wherever it lives using SQL that you already know.

- [GlareDB @ GitHub](https://github.com/GlareDB/glaredb)
- [What the Heck is GlareDB? @ HackerNoon](https://hackernoon.com/what-the-heck-is-glaredb).]]>
            </summary>
            <updated>2025-08-29T05:33:08+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4955</id>
            <title type="text"><![CDATA[Faraday Security]]></title>
            <link rel="alternate" href="https://faradaysec.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4955"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Protect your business, scale your security.  Open Source Vulnerability Management Platform.

Security has two difficult tasks: designing smart ways of getting new information, and keeping track of findings to improve remediation efforts. With Faraday, you may focus on discovering vulnerabilities while we help you with the rest. Just use it in your terminal and get your work organized on the run. Faraday was made to let you take advantage of the available tools in the community in a truly multiuser way.

Faraday aggregates and normalizes the data you load, allowing exploring it into different visualizations that are useful to managers and analysts alike.

[Faraday @ GitHub](https://github.com/infobyte/faraday).]]>
            </summary>
            <updated>2025-08-29T05:43:16+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/4956</id>
            <title type="text"><![CDATA[trdsql]]></title>
            <link rel="alternate" href="https://noborus.github.io/trdsql/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/4956"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[CLI tool that can execute SQL queries on CSV, LTSV, JSON and TBLN. Can output to various formats.

- [trdsql @ GitHub](https://github.com/noborus/trdsql).]]>
            </summary>
            <updated>2025-11-04T07:56:31+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5024</id>
            <title type="text"><![CDATA[Chainsaw]]></title>
            <link rel="alternate" href="https://github.com/WithSecureLabs/chainsaw" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5024"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Rapidly Search and Hunt through Windows Forensic Artefacts.

Chainsaw provides a powerful ‘first-response’ capability to quickly identify threats within Windows forensic artefacts such as Event Logs and MFTs. Chainsaw offers a generic and fast method of searching through event logs for keywords, and by identifying threats using built-in support for Sigma detection rules, and via custom Chainsaw detection rules.]]>
            </summary>
            <updated>2025-08-29T05:55:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5060</id>
            <title type="text"><![CDATA[qsv]]></title>
            <link rel="alternate" href="https://github.com/jqnatividad/qsv" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5060"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[CSVs sliced, diced &amp;amp; analyzed. 

qsv (pronounced &amp;quot;Quicksilver&amp;quot;) is a command line program for indexing, slicing, analyzing, filtering, enriching, validating &amp;amp; joining CSV files.]]>
            </summary>
            <updated>2025-08-29T06:00:22+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5103</id>
            <title type="text"><![CDATA[text2vec]]></title>
            <link rel="alternate" href="https://text2vec.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5103"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[text2vec is an R package which provides an efficient framework with a concise API for text analysis and natural language processing (NLP).

[text2vec @ GitHub](https://github.com/dselivanov/text2vec).]]>
            </summary>
            <updated>2025-08-29T06:07:29+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5104</id>
            <title type="text"><![CDATA[MITIE]]></title>
            <link rel="alternate" href="https://github.com/mit-nlp/MITIE" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5104"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[library and tools for information extraction.

This project provides free (even for commercial use) state-of-the-art information extraction tools. The current release includes tools for performing named entity extraction and binary relation detection as well as tools for training custom extractors and relation detectors.]]>
            </summary>
            <updated>2025-08-29T06:07:30+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5109</id>
            <title type="text"><![CDATA[RapidMiner]]></title>
            <link rel="alternate" href="https://rapidminer.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5109"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Amplify the Impact of Your People, Expertise &amp;amp; Data.

Altair and RapidMiner share the same vision to make data analytics simple enough for all users, but scalable, governed, and safe enough for all enterprises. RapidMiner is the enterprise-ready data science platform that amplifies the collective impact of your people, expertise and data for breakthrough competitive advantage.]]>
            </summary>
            <updated>2025-08-29T06:08:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5110</id>
            <title type="text"><![CDATA[KNIME]]></title>
            <link rel="alternate" href="https://www.knime.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5110"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[KNIME offers a complete platform for end-to-end data science, from creating analytic models, to deploying them and sharing insights within the organization, through to data apps and services.

[KNIME @ GitHub](https://github.com/knime)]]>
            </summary>
            <updated>2025-08-29T06:08:27+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5194</id>
            <title type="text"><![CDATA[KNIME Analytics Platform]]></title>
            <link rel="alternate" href="https://www.knime.com/knime-analytics-platform" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5194"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[KNIME Analytics Platform is free and open source, which ensures users remain on the bleeding edge of data science, 300+ connectors to data sources, and integrations to all popular machine learning libraries.]]>
            </summary>
            <updated>2025-08-29T06:23:35+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5260</id>
            <title type="text"><![CDATA[dbt]]></title>
            <link rel="alternate" href="https://www.getdbt.com/product/what-is-dbt/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5260"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[dbt™ is a SQL-first transformation workflow that lets teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone on the data team can safely contribute to production-grade data pipelines.

[dbt @ GitHub](https://github.com/dbt-labs/dbt-core).]]>
            </summary>
            <updated>2025-08-29T06:33:39+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5721</id>
            <title type="text"><![CDATA[Kangas]]></title>
            <link rel="alternate" href="https://github.com/comet-ml/kangas" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5721"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[🦘 Explore multimedia datasets at scale.

Kangas is a tool for exploring, analyzing, and visualizing large-scale multimedia data. It provides a straightforward Python API for logging large tables of data, along with an intuitive visual interface for performing complex queries against your dataset.]]>
            </summary>
            <updated>2025-08-29T07:50:20+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5915</id>
            <title type="text"><![CDATA[Volatility Framework]]></title>
            <link rel="alternate" href="https://github.com/volatilityfoundation/volatility" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5915"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Volatile memory extraction utility framework - An advanced memory forensics framework.

The Volatility Framework is a completely open collection of tools, implemented in Python under the GNU General Public License, for the extraction of digital artifacts from volatile memory (RAM) samples. The extraction techniques are performed completely independent of the
system being investigated but offer visibilty into the runtime state of the system.]]>
            </summary>
            <updated>2025-08-29T08:22:37+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/5919</id>
            <title type="text"><![CDATA[StreamAlert]]></title>
            <link rel="alternate" href="https://streamalert.io/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/5919"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[StreamAlert is a serverless, real-time data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response.

[StreamAlert @ GitHub](https://github.com/airbnb/streamalert)]]>
            </summary>
            <updated>2025-08-29T08:24:38+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/6382</id>
            <title type="text"><![CDATA[DuckDB]]></title>
            <link rel="alternate" href="https://duckdb.org/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/6382"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[DuckDB is an in-process SQL OLAP database management system.

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL
DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and several extensions designed to make SQL easier to use.

- [DuckDB @ GitHub](https://github.com/duckdb/duckdb).

Related contents:

- [DuckDB - Le moteur SQL qui transforme vos données @ Korben :fr:](https://korben.info/duckdb-moteur-sql-transformation-donnees.html).
- [Why DuckDB is my first choice for data processing @ \&amp;gt;robinlinacre](https://www.robinlinacre.com/recommend_duckdb/#why-duckdb-is-my-first-choice-for-data-processing).
- [DuckDB is Probably the Most Important Geospatial Software of the Last Decade @ dbreunig.com](https://www.dbreunig.com/2025/05/03/duckdb-is-the-most-impactful-geospatial-software-in-a-decade.html).
- [Why Semantic Layers Matter — and How to Build One with DuckDB @ MotherDuck](https://motherduck.com/blog/semantic-layer-duckdb-tutorial/).
- [Querying Billions of GitHub Events Using Modal and DuckDB (Part 1: Ingesting Data) @ noreasontopanic](https://noreasontopanic.com/p/querying-billions-of-github-events).
- [DuckDB beats Polars for 1TB of data @ Confessions of a Data Guy](https://www.confessionsofadataguy.com/duckdb-beats-polars-for-1tb-of-data/).
- [Building Your Modern Data Analytics Stack with Python, Parquet, and DuckDB @ KD nuggets](https://www.kdnuggets.com/building-your-modern-data-analytics-stack-with-python-parquet-and-duckdb).
- [Building an Obsidian RAG with DuckDB and MotherDuck @ MotherDuck](https://motherduck.com/blog/obsidian-rag-duckdb-motherduck/).]]>
            </summary>
            <updated>2026-02-16T06:10:15+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7240</id>
            <title type="text"><![CDATA[Metabase]]></title>
            <link rel="alternate" href="https://www.metabase.com/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7240"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Open Source Business Intelligence

 The simplest, fastest way to get business intelligence and analytics to everyone in your company 😋 

[Metabase @ GitHub](https://github.com/metabase/metabase).]]>
            </summary>
            <updated>2025-08-29T12:03:32+00:00</updated>
        </entry>
            <entry>
            <id>https://links.biapy.com/links/7693</id>
            <title type="text"><![CDATA[Keshif]]></title>
            <link rel="alternate" href="https://keshif.me/" />
            <link rel="via" type="application/atom+xml" href="https://links.biapy.com/links/7693"/>
            <author>
                <name><![CDATA[Biapy]]></name>
            </author>
            <summary type="text">
                <![CDATA[Keshif is a web-based tool that lets you browse and understand datasets easily.

- [Keshif @ GitHub](https://github.com/adilyalcin/keshif)]]>
            </summary>
            <updated>2025-08-29T13:19:33+00:00</updated>
        </entry>
    </feed>
