How to Scale New Products with a Data Lake on AWS and Qubole

The global spread of the novel coronavirus (COVID-19) and the economic impact that followed has prompted many businesses to furlough the workforce or migrate from the traditional office to remote-working environments. The volatile landscape has created incremental risks, especially for organizations heavily relying on IT Sec/Ops teams to monitor security and privacy and enforce regulatory compliance.

If you are looking for the scalability and performance needed to support interactive, ad hoc analytics on billions of rows – and with SQL – this latest Data Science Central webinar will show you how to combine distributed, columnar storage and parallel query processing with powerful aggregate functions to deliver faster time to insight using modern, on-demand analytics, as well as how to leverage the power of Kafka and Spark connectors to plug into existing data pipelines. We will discuss the architectural overview of columnar databases, share real-world use cases and give a live demonstration.

Data modernization, especially through cloud migration, is critical to realizing value from today’s fast, diverse, and high-volume data. Modernization is about overhauling legacy data management and practices that hold organizations back from achieving business goals, improving resilience, and reducing risk. However, often overlooked in the rush to develop new applications and migrate data is modernizing data governance. Poor attention to data governance will bake problems into overall modernization efforts that become hard to correct, increase risks, and ultimately reduce the value of data.

Explore three common ways that customers use Redis Enterprise to build a bridge to modern real-time applications. Today’s applications are faster, more powerful, and routinely capable of doing things that were considered extraordinary just a few years ago. Your applications must evolve. But who wants to constantly migrate, replatform, or re-architect?