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Available On-Demand - This webinar has been recorded and is now available for download.

The Operational Data Warehouse in Today’s Hybrid Cloud Environments

Webinar Speaker: Philip Russom, Senior Research Director for Data Management

Date: Wednesday, October 30, 2019

Time: 9:00 a.m. PT, 12:00 p.m. ET

Why you need to upgrade the real time, cloud, services, and mixed workload capabilities of your DW architecture to support today’s fast-paced tactical and operational decision making

Most data structures within a data warehouse assume a fair amount of time latency. For example, think of report data that is updated daily, weekly, or monthly. As another example, consider times series and other historical data that is used primarily for long-term strategic planning.

However, other business management practices require low-latency data that is typically a few hours or minutes old for use in management dashboards, operational reporting, and real-time analytics. To enable these use cases, many users have successfully built an operational data warehouse (OpDW) that is designed and optimized to capture, process, and present fresh data in real time or close to it. Note that the best OpDWs support a mix of transactional processing (to get the freshest operational data) and analytic processing (to turn fresh data into actionable insights that can be applied immediately).

However, like everything else in data warehousing and analytics, the OpDW must evolve to support streaming data, larger data volumes, and business demands for more frequent information and analytics to help the organization innovate and compete via data and analytics. Organizations facing these challenges and opportunities need to plan their modernization to leverage the power and innovation of today’s hybrid cloud and services environments.

Attend this TDWI webinar to learn about:

  • What a modern OpDW is and does
  • Enabling technologies and practices that modernize the OpDW, such as columnar data management, in-memory execution, optimization for continuous updates, distributed and cloud-based data management, and various types of services
  • How and why the best OpDWs provide high performance for mixed and concurrent workloads for both operations and analytics, sometimes called hybrid transactional and analytic processing (HTAP)
  • Real-world use cases for the modern OpDW, namely operational reporting and analytics, management dashboards, innovative data-driven practices (self-service, advanced analytics, process automation), fraud detection, customer recommendations, and user collaboration across large, distributed enterprises

Philip Russom, Ph.D.

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