Enabled Data Quality and Data Governance

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.

Businesses today need fast, scalable, and agile data and analytics, and cloud-based solutions are proving critical to satisfying these requirements. They enable organizations to rapidly and easily spin up systems and services for collecting, managing, and analyzing data. More important, cloud-based solutions deliver value from “data gravity”the surging volumes of new data created in the cloud by social media, the IoT, multichannel customer behavior, and other activity.

From AI and machine learning to data discovery and real-time analytics, a strong data architecture strategy is critical to supporting your organization's data-driven goals. Greater speed, flexibility, and scalability are common wish-list items, alongside smarter data governance and security capabilities. Many new technologies and approaches have come to the forefront of data architecture discussions, including data lakes, in-memory databases and engines like Spark and cloud services of all shapes and sizes.

Your Data Strategy should be concise, actionable, and understandable by business and IT! Data is not just another resource. It is your most powerful, yet poorly managed and therefore underutilized organizational asset. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Overcoming lack of talent, barriers in organizational thinking, and seven specific data sins are organizational prerequisites to be satisfied before (a measurable) nine out of 10 organizations can achieve the three primary goals of an organizational Data Strategy, which are to: