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Thought Leadership

Data Engineering Machine Learning Thought Leadership

The State of Data Engineering 2024

Einat Orr, PhD

Since 2021 we’ve been releasing the annual State of Data Engineering Report, a compilation of all the relevant categories that have a direct impact on data engineering infrastructure. In 2024, we see 3 primary trends that influence the categories which will be covered in this report. Trend #1: GenAI influence on software infrastructure As predicted […]

Data Engineering Machine Learning Thought Leadership

Why Is DataOps So Hard and What Tools Make It Easier?

Einat Orr, PhD

TL;DR: DataOps complexity arises from unclear R&Rs, a lack of standardization in interfaces, distributed technology complexities, and difficulties in implementing engineering best practices. The solution is to define clear responsibilities, address missing requirements, and manage data pipelines efficiently using emerging solutions that enhance the manageability and resilience of DataOps. What makes DataOps so hard is,

Data Engineering Thought Leadership

Data Engineering in 2024: Predictions

Oz Katz

This article was originally published on Datanami and is republished here with permission. As we officially kick off 2024, I realized I have a few thoughts on the direction of the data landscape that might be of interest to others.  This is a recap of my “predictions.”  I will admit that it’s a mix of what I

Product Thought Leadership

Major Milestone: lakeFS 1.0 Is Now Generally Available

Oz Katz

TL;DR:  lakeFS 1.0 is generally available. You can upgrade to this version via the Assets here. Just over three years ago we publicly released the initial lakeFS. Our mission when we first launched lakeFS was to provide data practitioners with a scalable data version control system that would bring order to the chaos that comes

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

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