Build an Effective Data Governance Framework

With the explosive growth of DataOps to drive faster and more confident business decisions, proactively understanding the quality and health of your data is more important than ever. Data observability is an emerging discipline within data quality used to expose anomalies in data by continuously monitoring and testing data using artificial intelligence and machine learning to trigger alerts when issues are discovered.

Data scientists require on-demand access to data, powerful processing infrastructure, and multiple tools and libraries for development and experimentation. Meanwhile, IT has a difficult time keeping up with these changing needs while ensuring operational efficiency and compliance. Sound familiar? CDSW was designed precisely to r

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.

Join us for this on-demand with Looker where we explore the top Business Intelligence trends for 2019. In this 50-minute webinar, you will learn about the issues affecting BI, the role of analytics as a critical success factor for organizational success, and how companies are leveraging BI and analytics for high-value insights.