Modernize Your Data Architecture to Deliver Oracle as a Service

The migration to cloud-based data architectures continues at a rapid pace, including databases and data management. Oracle databases are part of this trend, and during this webinar you will learn how to automate the provisioning and management of Oracle databases so that you can deliver an “as-a-service” experience with 1-click simplicity. Experts will walk you through the process of
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Spotlight

OTHER ON-DEMAND WEBINARS

Building the Road Map for Real-Time Data and Analytics

As organizations strive to be more competitive, they often need real-time insights; no one wants to make decisions based on stale data. TDWI research indicates that real-time data collection is already in the mainstream. Some use cases include inventory management, fulfillment, supply chain, and logistics in which retailers must be able to assess product availability and consumer demand in real time. Forward-looking organizations also want to enrich real-time data with other data types to provide even better analytics.
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Planning for a Scalable Enterprise Data Lake

tdwi.org

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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How to advance your Data Analytics Maturity: Key steps to take you to the next level

Today’s most successful organisations are utilising data to drive accelerated growth. They are each on a journey towards greater data maturity, increasing the value of their data and deepening their insights as they go. However, the rapid growth of analytic solutions has not successfully transformed every business into a data-driven powerhouse – yet. So how can you ensure the route you take to AI maturity is a successful one? As with any endeavor, your company will face obstacles as you strive to transform into a data-driven organisation. To succeed, it’s important to evaluate where you are today, the challenges that lie ahead, and what exactly “ahead” means for you and your team.
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Cloud Data Warehouse Modernization

tdwi.org

The economic model and elegance of cloud environments are motivating companies to assess their existing on-premises data warehouses and modernize their enterprise information environments. However, confusion about what is meant by “modernization” has led some to believe that “lifting and shifting” their on-premises implementation to a cloud environment is the default approach. In these cases, the results are mixed—while the system has technically been moved to a modern cloud platform, by no means is it modernized.
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