Headless agents are coming for your data. Be ready with lakeFS

Thought Leadership

Data Engineering Thought Leadership

The State of Data Engineering 2023

Einat Orr, PhD

A lot has happened since 2022, from the rise of Generative AI to the economic slowdown and job losses impacting data practitioners in 2023. In fact, it’s safe to say that the GenAI hype doesn’t seem to be high enough to counterbalance the influence of the struggling economy, as the demand for data practitioners is […]

Thought Leadership

MLOps Is Overfitting: Here’s Why

Einat Orr, PhD

VC surveys show that the MLOps category has significantly expanded in the past few years, with hundreds of companies defining themselves as part of this dynamically evolving niche.  MLOps systems provide the infrastructure allowing ML practitioners to manage the lifecycle of their work from development to production in a robust and reproducible manner. An MLOps

Data Engineering Thought Leadership

Year in Review: Thanks A-LOTL for an Outstanding 2022

Adi Polak

2022 has been an incredible year, in the same way that roller coasters are thrilling. Our industry has seen many shifts and rapid changes – which we experienced together. In 2022, we witnessed how data engineering teams became increasingly central to any data-driven organization. And the growth of more significant roles of Analytics Engineers, ML

Data Engineering Thought Leadership

5 New Year Resolutions for Data Engineers

Michal Wosk

As a new year is just around the corner, it is time to look ahead to the year that is coming and make some new year resolutions. It is a chance to adopt new habits that will make you more successful and more impactful, but it is also a great opportunity to stop some bad

Thought Leadership

What a Year With lakeFS Taught Me

Michal Wosk

A year ago, in November 2021, I took a bold decision to leave my role at Microsoft and join team lakeFS as VP Marketing. Upon joining I wrote an article on why I decided to join. But just before publishing the piece, I had a change of heart; it didn’t feel right to me. It

Data Engineering Thought Leadership

4 Ways to Reduce Cloud Data Storage Costs

Oz Katz

In the past year, words like recession, business slowdown and monetary cuttings are being heard more and more often. Not just in the economic press and in the media, these discussions are very much heard also in almost all companies – within boardrooms, in management meetings and when engaging with potential investors and customers. As

Data Engineering Thought Leadership

Data Mesh: What is it and What Does it Mean for Data Engineers?

The lakeFS Team

Organizations have practically always needed data analytics, and they jumped on the analytics bandwagon as soon as the first computers appeared on the scene. In the 80s, businesses built data warehouses using relational databases as their decision-support systems (DSS). However, as companies generated more diverse data at high velocity, relational databases showed their limitations.  This

Data Engineering Thought Leadership

Data versioning as your ‘Get out of jail’ card – DVC vs. Git-LFS vs. dolt vs. lakeFS

Einat Orr, PhD

Data Versioning at Scale: Solutions Overview Back when I was a 23-year-old student, I worked at an Israeli networking company as a BI analyst in the Operations department. My job revolved around modeling the company’s inventory which was quite costly and needed optimization.  At some point, I attended a meeting of the company’s management. When

Data Engineering Thought Leadership

The State of Data Engineering 2022

Einat Orr, PhD

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 in the data landscape. In fact, we had discussions internally about whether we should even do an update for 2022. We kid. It was another year worthy of its own

We use cookies to improve your experience and understand how our site is used.

Learn more in our Privacy Policy