In this episode of Let’s Talk, we hosted two guests from Varada to talk about creating analytics-ready data lakes. Before we go there, we do need to understand the basic difference between data lakes and data warehouses, and also the limitations of each. Varada has seen many use-cases that drive users from data warehouses to data lakes; what are those use-cases? More importantly, what use-cases are served best with data lakes vs data warehouses? We then talked about solutions that are there to make data lakes analytics-ready so the data team and data scientists can start tapping into those.

GuestsDavid Krakov, Co-founder and CTO at Varada; Ori Reshef, Vice President Of Products at Varada

Check more about Varada, named by Gartner a “Cool Vendor in Data Management”. Varada enables data practitioners to go beyond the traditional limitations imposed by data infrastructure and instead zero in on the data and answers they need—with complete control over performance, cost and flexibility. In Varada’s world of big data, every query can find its optimal plan, with no prior preparation and no bottlenecks, providing consistent performance at a petabyte-scale.


You may also like