Are you planning to implement a data governance program? What are the things that practitioners often overlook or underestimate, and what are the most common mistakes they make? Join us to hear from Katherine Fraser, CEO of 1 to learn more about the key components of a successful data governance program, common mistakes made and to avoid when implementing a data governance program, and tips for maintaining a successful data governance program.
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In this webinar, we will discuss the importance of data maps in building a privacy program. We look at the gap between privacy and engineering teams, the problems of scaling privacy programs with a business process approach to data mapping, and how an application-led approach helps you develop dynamic & complete data maps.
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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.
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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.
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