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Today, machines are able to emulate human intelligence through the use of artificial intelligence technology. Approaches such as machine learning, deep learning, natural language processing,
- Idan Novogroder
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
- Einat Orr, PhD
TL;DR In the previous blog, Introducing the LangChain lakeFS Loader, and sample notebook, we explained and demonstrated integration of lakeFS with LangChain and LLM models
- Amit Kesarwani
Git for data may sound odd at first. But using the Git logic and mechanisms for data lakes makes a lot of sense. After all,
- Oz Katz
Data is a valuable asset to any company today. But can you really use this massive amount of data in its raw form to train
- Idan Novogroder
Efficient data management is a critical component of any modern organization. As data volumes grow and data sources become more diverse, the need for robust
- Amit Kesarwani, Jonathan Rosenberg
lakeFS is a powerful solution for data version control that enables data practitioners to manage data as code using Git-like operations and achieve reproducible, high-quality
- Iddo Avneri
What is mirroring We are pleased to announce a preview of a long-awaited lakeFS feature: transactional mirroring across regions. Mirroring builds on top of S3
- Ariel Shaqed (Scolnicov), Idan Novogroder, Guy Hardonag
Machine learning solutions come in handy for addressing various problems and achieving a wide range of goals. However, if we look at ML applications from
- Idan Novogroder
In a previous article, we explored how dbt and Databricks work together. We will now review a specific feature of dbt Cloud – dbt Cloud
- Tal Sofer
If you’ve come across our content, you may have noticed blogs diving into the technical details of lakeFS, and this is one of them. These
- Ariel Shaqed (Scolnicov)
