How To Design a Cloud-Native Data Lake Solution

Traditionally, data had been produced and stored at multiple sources. Given the high cost of the traditional Data warehousing system, only pristine data could be used for analytics and reporting. There was a clear need for a central platform. The advent of Big Data and Cloud systems led to the evolution of Enterprise data lake within organizations. The concept of data lake has evolved from a Hadoop-based on-premise data lake to an object-storage cloud-based data lake with compute being provisioned only when the need arises. The Big Data and Cloud Engineering team at Abzooba has been playing a key role in helping organizations achieve their goal of digital transformation. We have been a trusted partner for our clients in their Data Modernization, Cloud Migration and Advanced Analytics journey. Join us in this session as we discuss: - Best practices for designing a data lake solution - Introduction to Olive and Pine, building blocks for Data Lakes - Demo of Olive (Data Ingestion Framework) - Bonus: A 60-days full-featured, free trial (including installation and support) of Olive for all interested attendees. * About Olive: Olive is a cloud agonistic Data Ingestion Framework with a low resource footprint. Developed in-house, our data engineers and practitioners use Olive daily in their work. We found Olive to be so useful, that we decided to release it at a very low cost in the Azure and AWS marketplace. We have also shared the Azure and AWS marketplace links in attachments section, for easy reference. About Bijoy Bora: Bijoy is the SVP & Global Head, BD&C Engineering practice, Abzooba Inc. He is also a Professor of Practice, in their MS Data Science program, School of Engineering & Computer Science, University of the Pacific, San Francisco. CA. Bijoy was also the Co-founder of Zaloni Inc.