July CHUG Event: Best practices on Building A Hadoop Data Lake Solution- Diyotta

Best practices on Building a Hadoop Data Lake Solution

Description:

The world of "big data" is changing dramatically right before our eyes – from the increase in big data growth to the way in which it’s structured and used. The trend of "big data growth" presents enormous challenges, but it also presents incredible opportunities.

Many organizations are pushing towards harnessing the power of distributed platforms like Hadoop to analyze and gain insights which were never attempted before. Business users are continuously envisioning new and innovative ways to use data for operational reporting and advanced analytics. The Data Lake or Data Reservoir, a next-generation data storage and management solution, is gaining lot of popularity to meet the ever-evolving needs of increasingly savvy users.

Often, the Data Lake initiatives suffer from the experimental or exploratory start which is limited in vision, purpose and the long term goals which it needs to accomplish. While the goal of the data lake is to collect diverse set of data and making it accessible for analytics, there are certain key best practices which we should keep in mind while building out the

In this session, you will learn from the experts about:

· Characteristics of a data lake

· Data ingestion in the data lake

· Metadata/data lineage within the data lake

· Audit trail/traceability within the data lake

· Provisioning data out of the data lake

· Self-service data pipelines for data lake

About Speaker

Ravindra Punuru is a technology-driven thought leader who builds the strategy on products and envisions the future of data integration on big data platforms. Ravindra spearheads the research and big data product strategy and architecture department at Diyotta. Ravindra brings over 16 years of expertise in application development, design and implementation of data warehouse systems and architecture on MPP and Hadoop platforms.

About Diyotta:

Diyotta provides a flexible, powerful and high performing data integration solutions for managing big data within the enterprise.

Diyotta turns the data lake into an information hub. It is the industry’s first data provisioning platform purpose-built for big data across hybrid data systems and the cloud. In the new world of big data, we accelerate data warehouse modernization and enable the virtual integration of complex data flow across environments.

Diyotta offers a design-once architecture for rapid change of both data and platforms; agent-based, point-to-point integration for all of your data; and optimal use of all data platform functions in a unified interface. With Diyotta companies fully leverage their existing data platforms with the quickest time to value, make the move to modern data platforms with the highest level of reuse possible, and respond to business needs for new data and analytics without constraints.