Because BI/DW architectures have historically been engineered to maintain the performance of OLTP systems, implementation decisions of the past have forced analysts to sacrifice data accessibility and flexibility in return for reasonable reporting and analytics performance. The reliance on ERP and other operational systems to run the business negatively impacts the agility of the data analyst. Limited data accessibility and increased latency are effectively engineered into the analytics environment, creating complexities that preclude the rapid discovery of actionable insights.
As the pace of business accelerates, there is a need to strike a balance between production operational systems and the needs of today’s data analysts. This Webinar explores how data complexities constrain users from rapidly testing new models, simulations, what-if analyses, and predictive models. In contrast to traditional data warehouses organized for specific reporting purposes, we discuss how we can free the analysts from the constraints of pre-aggregations to support analyses, caching of predefined queries, materialized views, and canned reports.
By uprooting data complexity, we can diminish the need for data extraction, limit the redundant operational data stores, and reduce the repeated transformations prior to loading into alternate data models. We will explore ways to enable greater flexibility in gaining advantage from ERP systems by accessing the raw data to better support data discovery and interactive investigations.
Attendees will learn about:
Individual, Student, & Team memberships available.