🐍 Python Libraries for Analytics Engineers

In today's edition: What's Shaping the Future of Data?

• ⚙️ Why Complex Projects Need More Than Smart Engineers

• 📊 Battle-Tested Modeling Techniques for Tabular Data

• ⚡A Note on the Dirichlet Distribution

• ⚡ Inside Husky's Query Engine: Real-Time Access to 100 Trillion

• 📱 OpenAI's Sora soars to No. 3 on the US App Store

• 🐙 Google pushes Jules coding agent into terminals

• 💡 AI Tutorial:Turn any logo into a 3D design with AI

• 🤖 AI Tools and Data Tools to checkout

7 Python Libraries Every Analytics Engineer Should Know

Analytics engineers sit at the intersection of data engineering and data analysis. While data engineers focus on infrastructure and data scientists focus on modeling, analytics engineers concentrate on the "middle layer", transforming raw data into clean, reliable datasets that other data professionals can use.

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Why Complex Projects Need More Than Just Smart Engineers

Every engineer starts by getting really good at their specific area. Software developers learn programming languages and algorithms. Hardware engineers master circuit design and component selection. But when projects get big enough, knowing your own piece isn’t enough anymore. You need to understand how your work connects to everyone else’s work.

Battle-Tested Modeling Techniques for Tabular Data

Over hundreds of Kaggle competitions, we’ve refined a playbook that consistently lands us near the top of the leaderboard—no matter if we’re working with millions of rows, missing values, or test sets that behave nothing like the training data…Below are seven of our most battle-tested techniques, each one made practical through GPU acceleration…

A Note on the Dirichlet Distribution

In this post, I explore some properties of the Dirichlet distribution and illustrate the behavior of the symmetric Dirilichet distribution as alpha, the concentration parameter, varies. Understanding this behavior may be helpful in constructing an informative prior for the multinomial distribution…

Inside Husky’s query engine: Real-time access to 100 trillion events

At Datadog, we process more than 100 trillion events and billions of queries every day—across logs, traces, network data, and more. To support that scale, we built Husky, our third-generation event store. We detailed its architecture in a series of posts on exactly-once ingestion and multi-tenancy and massively parallel compaction.

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👨‍💻 Data Tools, Libraries

spyglass
A personal search engine, crawl & index websites/files you want with a simple set of rules

trigger.dev
The developer-first open source Zapier alternative.

DocsGPT
DocsGPT is a cutting-edge open-source solution that streamlines the process of finding information in project documentation

With Observable, you can fast-track data exploration, analysis, and visualization at scale.

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AI News:

☄️ Perplexity launches Comet browser for free

Perplexity AI has rolled out its Comet browser globally at no cost. The browser acts as a personal assistant, able to search, organize tabs, draft emails, shop and more. Originally reserved for $200/month Max subscribers, Comet quickly attracted a waitlist of millions. Now available for free, it positions Perplexity against rivals like Google’s Gemini in Chrome, OpenAI’s Operator and Anthropic’s browser agents.

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📱 OpenAI's Sora soars to No. 3 on the US App Store

OpenAI's Sora app saw 56,000 downloads on its first day. It is now ranked third Top Overall app on the US App Store, despite being invite-only and limited to users in the US and Canada. The ChatGPT app and Google's Gemini iOS apps had stronger launches, with each reaching at least 80,000 downloads on day one, but since Sora is invite-only, that may not be a fair comparison.

💰 Where startups actually spend on AI

Andreessen Horowitz released its AI Spending Report, analyzing transaction patterns from fintech startup Mercury’s 200,000+ customers to show which AI companies are capturing real startup dollars versus just generating traffic. OpenAI took the top spot, with Anthropic in the second place, and Perplexity (No. 12) and Merlin AI (No. 30) rounding out the list of general assistants.

🐙 Google pushes Jules coding agent into terminals

Google launched Jules Tools, a new command-line interface and public API for its autonomous coding agent, allowing developers to trigger tasks and monitor progress from terminals rather than switching to separate browser windows. Developers can now control Jules through typed commands in terminal windows, automating repetitive tasks or creating coding assignments.

🏗️ Anthropic’s major infrastructure shift

Anthropic has hired Rahul Patil, former Chief Technical Officer (CTO) of Stripe, as its new CTO to help strengthen its AI infrastructure and improve the speed, reliability, and safety of its AI platforms. Patil, who is replacing Anthropic co-founder Sam McCandlish (who is now Anthropic’s Chief Architect and will primarily work on AI model training), will focus on compute, infrastructure, and other engineering tasks.

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AI Tutorial

Turn any logo into a 3D design with AI

1. Go to ChatGPT and sign in.

2. Upload a clean black-and-white version of your logo or icon.

3. Search Google Images for “Cinema 4D materials” or “Blender textures,” or look for specific materials like marble, metal, wood, or glass; save the PNG.

4. Upload both the logo and texture into ChatGPT-4o and prompt:

“Create a 3D version of this logo (left image) using the texture from the right image. Cinema 4D style, 8K quality, realistic lighting and shadows, black background.”

4. If needed, refine the output by asking for tweaks like “Make it more metallic”, “Add more depth”, or “Change the lighting angle.”

Tip: experiment with unusual textures like fabric, ice, or even food to make your design stand out.

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👀 I wonder how long they are going to last

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