The Modernization of the Data Warehouse: Tackling New Architectures for New Use Cases in Analysis and Operations
Webinar Speaker: Philip Russom, Senior Research Director for Data Management
Date: Wednesday, September 18, 2019
Time: 9:00 a.m. PT, 12:00 p.m. ET
Why data is warehouse modernization such a pressing issue today?
Business innovation requires bigger and better data. This is especially apparent in emerging practices for advanced analytics (based on mining, clustering, statistics, machine learning, etc.) and self-service data access (for data discovery, prep, visualization, etc.). Data warehouses are under pressure to provision the voluminous and structurally diverse data required by these innovative practices.
Legacy warehouse designs need serious updating. The average data warehouse today was designed by technical users to provision data for reporting, dashboards, and online analytic processing (OLAP). This kind of warehouse design is poorly suited to advanced analytics, self-service, and the new data sources that current businesses practices demand. Hence, many existing warehouse designs need to be modernized, augmented, and optimized. Furthermore, users designing a new data warehouse should keep both sets of requirements in mind.
Technical users need to rethink their platform choices. To achieve the technical goals of the modern data warehouse, many users have decided to “replatform” by migrating warehouse data (in whole or in part) to new data platforms such as those based on Hadoop, columns, clouds, and new relational databases, with cloud-based data platforms preferred.
This webinar will explore four critical success factors:
- Compelling business drivers and use cases for the modernized data warehouse
- New platforms and strategies for data management
- How modernization is aided by cloud, multicloud, and hybrid cloud environments
- Hybrid data architectures specifically for the modernized data warehouse
Philip Russom, Ph.D.