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Developing a machine learning application is a complex process that involves steps such as processing massive volumes of data, testing multiple ML models, parameter optimization,
- Einat Orr, PhD
As OpenAI unveiled ChatGPT, which swiftly explained difficult problems, carved sonnets, and discovered errors in code, the usefulness and adaptability of LLMs became clear. Soon
- Einat Orr, PhD
Metadata enforcement is a broad term that can refer to different aspects of managing and controlling metadata. Let’s explore few key areas: Understanding Metadata Enforcement
- Amit Kesarwani
Databricks Delta Lake includes a number of time travel features to let you access any previous version of the extensive data that Delta automatically versions
- Tal Sofer
The Write-Audit-Publish (WAP) pattern in data engineering gives teams greater control over data quality. But what does it entail, and how do you implement it?
- Einat Orr, PhD
When Databricks users first hear about lakeFS, a common response is, “I already have time travel in Delta Tables.” This raises an important question: how
- Iddo Avneri
Snowflake has many advantages, but its security and scalability are arguably the leading magnets for data practitioners. More and more businesses are migrating their data
- Idan Novogroder
The lakehouse architecture has become the backbone of modern big data operations, but it comes with specific issues. The challenge of data versioning arises in
- Oz Katz
An upcoming release of lakeFS will no longer include user management with ACLs. The code currently used to manage users and groups will remain open
- Oz Katz, Einat Orr, PhD
This article is the continuation of Building A Management Layer For Your Data Lake: 3 Architecture Components. In this part, we explore open table formats,
- Einat Orr, PhD
The growth in amounts of data was the catalyst for replacing traditional analytics databases with data lakes. While data lakes were able to handle large
- Einat Orr, PhD
