Make Big Data Work in the Cloud

In this webinar we will discuss a more modern view of the data lake and consider best practices for planning and implementing a scalable enterprise data lake. The flaws in early data lakes were often rooted in the expectations of data consumers who put a premium on self-service data analytics. However, with no data governance mechanisms, data lakes quickly became more of a glorified “dumping ground,” “data swamp,” or “beta lake” for organizational data.In recent years, though, some innovations have allowed the data lake to evolve into an agile yet managed environment for accumulating shared data resources that can be optimally used for competitive advantage. Data lakes have evolved beyond the original on-premises concept based solely on Hadoop and now include pretty much any distributed computing platform (Hadoop, Spark, EMR, serverless, etc.) and any storage mechanism (HDFS, S3, ADLS), either on-premises or in the cloud.

In order to maximize the value of your data and democratize AI across the organization, citizen data scientists are emerging and implementing machine learning models into business analytics applications such as Microsofts Excel, Power Apps, Power BI, Reporting Services and more. In this webinar, attendees will learn more about how their organizations can add AI to BI, making more predictive decisions along the way.

This session will discuss how the master data management platforms are evolving to meet needs of digital economy. A modern master data management platform incorporates graph technology, infuses insights from the data using advanced analytics and ML, and offer big data scale performance in the cloud. Join this webinar to learn about these and other critical capabilities that power connected customer experience, compliance, and business alignment.

CockroachDB has already defined what it means to be a cloud database and its unique architecture delivers some key innovations. Now with CockroachDB Serverless we use CockroachDB’s architecture to remove all barriers between developers and the promise of a massively scalable, familiar SQL database that can power applications of any size.