Despite the increasing adoption of Artificial Intelligence (AI) applications, most organizations are bound to see implementation challenges. One of the issues lies in the data itself. A recent survey showed 80% of companies believe their data is suitable for AI, but more than half are actually dealing with challenges like internal data quality and categorization […] The post AI-Ready Data: Characteristics, Challenges & Best Practices appeared first on Git for Data - lakeFS.| Git for Data – lakeFS
Overview of the data platform built for the AI era powered by an all-new scale-out architecture, built from the ground up for all-flash.| www.vastdata.com
Explore 5 defining trends in the annual State of Data and AI Engineering 2025 report. Uncover what changed and what's trending this year.| Git for Data - lakeFS
What role does AI in data engineering stand to play in enabling best practices? Keep reading to learn how data engineers benefit from AI solutions.| Git for Data - lakeFS
Explore the leading tools and trends that shaped data engineering in 2023. Read the detailed report on data version control at scale.| Git for Data - lakeFS
Uncover the benefits of data version control. Understand what it is, how it works, and why it's essential for data engineers| Git for Data - lakeFS
The Technology Radar is an opinionated guide to today's technology landscape. Read the latest here.| Thoughtworks