Data Analytics Testautomation Concept

Data management is fundamental to every application. Managing this precious asset is an essential competency in modern businesses of every sort. Innovations in data platforms are being adopted, and data management approaches are evolving rapidly to keep pace. Increasingly, enterprises are converging their data warehouse, data lake, and other data management platforms onto distributed cloud-native infrastructures. As more types of data are consolidated into their platforms, enterprises implement more scalable DataOps pipelines and more comprehensive governance practices to manage it all. Want to learn more? This webinar brings together a panel of experts, moderated by James Kobielus, TDWI’s research director for data management.

As companies invested in their digital transformations, one side effect was the proliferation of data environments and varying database instances. With so many systems to navigate, many organizations have fallen prey to operational disruptions and now struggle to achieve the high level of performance and scalability that their transformations promised.

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.

According to PwC, nearly 4 out of 5 CEOs believe that remote collaboration will last after the pandemic. And Gartner predicts that through 2025, 80% of organizations trying to scale digital business will fail because they don’t take a modern approach to data and analytics governance.