Trends for Modernizing Analytics and Data Warehousing in 2019

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.

The Internet of Things, social media and enterprise content all have one thing in common: they generate vast quantities of data — ever-faster. So much so that picking out relevant information and assembling it into meaningful patterns is a tall order. These new data sources also present another challenge. They generate unstructured data - such as text and emojis - that don’t fit neatly into traditional database structures. This data can however hold valuable insights on important and hard-to-quantify concepts such as social sentiment.

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.

Do you have data governance on your mind? Do you envision an environment where people are held formally accountable for the data they define, produce and use? Does metadata play a big role in that governed environment? Of course, it does. To manage any “thing” requires that you have quality information about that thing. Join Bob Seiner, of KIK Consulting and TDAN.com, with Gal Alon, Senior Director of Business Development for an industry leading metadata management automation software provider Octopai, as they discuss the who’s, what’s, why’s and how’s of automating and leveraging your metadata environment to successfully govern your organization’s data. Bob and Gal will spend the hour chatting about the role metadata management plays in data governance as well as discuss specific use cases to improve probability of Data Governance success.