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lakeFS Acquires DVC, Uniting Data Version Control Pioneers to Accelerate AI-Ready Data

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lakeFS Named Cool Vendor™ in the 2026 Gartner® Coolest Vendor Innovations in Data Management

Data Engineering

Data+AI Summit 2022 Recap: Top 6 Industry trends and 9 major announcements!

It was 27th June 2022. San Francisco was bustling with 5000+ data folks from around the world to attend the Data & AI summit live

Proudly announcing lakeFS Cloud

What is lakeFS? As data practitioners, we use many different terms to talk about what we do – we call it business intelligence, analytics, data

LakeFS Introduces a New Approach to Data Manageability and Reliability

lakeFS Cloud provides a Git-like repository for data lakes in a hosted version available in AWS Marketplace NEW YORK and TEL AVIV, June 22, 2022–lakeFS,

The State of Data Engineering 2022

A year has passed since we shared the State of Data Engineering 2021. And since we released that article last May, not much has changed

7 Winning Habits of Effective Data Engineers  

As organizations develop new product offerings and data streams, data engineers deal with the largest and most complex datasets ever. Add growing teams and new

Towards Effective DataOps

Gain the confidence to mess with your datawithout making a mess of your data. “If it hurts, do it more often.” is a wise piece

Clearing the mess – How to ensure data quality with versioning

The last decade saw an unprecedented rise in the number of organizations that base their decisions and operations on data. The number of digital products

5 Painful mistakes data engineers make, and how to avoid them

Modern data engineering practices lead more and more organizations to a broader use of object stores. This happens due to the rising scale and complexity

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Introducing the Boto S3 Router Package on PyPI!

Introduction It may seem strange at first, but increasingly we cannot be sure when putting or getting data from an object store that the data

lakeFS Git-like interface for scalable data

Closing the Gap: Lifecycle Management for Data Products

As data practitioners, we use many different terms to talk about what we do – we call it business intelligence, analytics, data pipelines, or insights.

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How to Level Up Your Data Lake Architecture

What is the Basic Data Lake? A data lake is primarily two things: an object store and the objects being stored. It might look something

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How Easy It Is to Re-use Old Pandas Code in Spark 3.2?

In October, it was announced that the Pandas API was being integrated with Spark. This was particularly exciting news for a Pandas-baby like myself, whose

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