Netflix Tech

JANUARY 6, 2025

Part 2: Navigating Ambiguity By: VarunKhaitan With special thanks to my stunning colleagues: Mallika Rao , Esmir Mesic , HugoMarques Building on the foundation laid in Part 1 , where we explored the what behind the challenges of title launch observability at Netflix, this post shifts focus to the how. How do we ensure every title launches seamlessly and remains discoverable by the right audience?

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Metadata Algorithm Systems Building 87

KDnuggets

JANUARY 6, 2025

AI is growing fast! Learn the top skills for 2025 to stay ahead in this exciting field.

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databricks

JANUARY 6, 2025

Introduction MLOps is an ongoing journey, not a once-and-done project. It involves a set of practices and organizational behaviors, not just individual tools.

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Project IT 114

KDnuggets

JANUARY 6, 2025

Learn how to structure your data science projects to make them more organized and minimize chaos!

Data Science 129

Data Science Project Data 129

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

Data

Monte Carlo

JANUARY 6, 2025

2024 was a real doozy. If you emerged from the generative AI haze with your sanity still intact, then we salute you. This year, we saw early GenAI use cases like chatbots and copilots, we saw data teams introducing open table formats into their lakehouses, we saw data products grow in popularity more than ever before, and we saw everything in between.

Insurance 52

Insurance Unstructured Data High Quality Data Government 52

KDnuggets

JANUARY 6, 2025

Kickstart your data engineering career with an expert guide available on GitHub.

Data Engineering 126

Data Engineering Data Engineer Engineering Data 126

Confluent

JANUARY 6, 2025

Learn how startup Reworkd leverages Confluents complete data streaming platform to scale real-time data scraping with generative AI.

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Data 64

ArcGIS

JANUARY 6, 2025

Discover how integrated CAD and GIS workflows using ArcGIS for AutoCAD can improve collaboration and data management for parcel information.

Data Management 62

Data Management Management Data Architecture 62

Confessions of a Data Guy

JANUARY 6, 2025

I’ve been playing around more and more lately with DuckDB. It’s a popular SQL-based tool that is lightweight and easy to use, probably one of the easiest tools to install and use. I mean, who doesn’t know how to pip install something and write SQL? Probably the very first thing you learn when cutting your […] The post Using DuckDB to read JSON files in S3 appeared first on Confessions of a Data Guy.

SQL 100

SQL IT Data 100

Snowflake

JANUARY 6, 2025

The incredible promise of the fully autonomous vehicle (AV) and more advanced driver assistance systems (ADAS) has been driving the automotive industry for the better part of the last decade. It has inspired original equipment manufacturers (OEMs) to innovate their systems, designs and development processes, using data to achieve unprecedented levels of automation.

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Manufacturing Cloud Computing Data Storage Algorithm 96

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

Systems

Netflix Tech

JANUARY 6, 2025

This article is the last in a multi-part series sharing a breadth of Analytics Engineering work at Netflix, recently presented as part of our annual internal Analytics Engineering conference. Need to catch up? Check out Part 1 , which detailed how were empowering Netflix to efficiently produce and effectively deliver high quality, actionable analytic insights across the company and Part 2 , which stepped through a few exciting business applications for Analytics Engineering.

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Engineering Entertainment Designing Finance 81

Picnic Engineering

JANUARY 6, 2025

Picnic increasingly follows a data-driven approach towards serving content. Every customer sees their own version of the store, fitted to their needs and behaviors. While this enables a better user experience, it also places heavy demands on the flexibility of our store backend systems. The continuous introduction of new insights and data points, as well as the desire for business logic that can quickly evolve, introduces a set of challenges which are not easilysolved.

SQL 69

SQL Java Database Accessible 69

Precisely

JANUARY 6, 2025

Key takeaways : Real-time data is critical for exceptional customer experiences. Customers expect immediate responses and personalized interactions, and streaming data architectures help you meet these expectations. Integrated and scalable architectures drive business agility. By consolidating the data of disparate systems when leveraging streaming data architecture, you improve operational efficiency, reduce costs, and adapt to new technologies.

Data Architecture 59

Data Architecture Architecture Pipeline-centric Banking 59