Why Modern Design Patterns are Critical Success Factors for Data Warehouses and Data Lakes
Webinar Speaker: Philip Russom, Senior Research Director for Data Management
Date: Wednesday, August 26, 2020
Time: 9:00 a.m. PT, 12:00 p.m. ET
Database designs must modernize to address new requirements for digital business and analytics, plus leverage cloud and cloud data platforms.
According to TDWI’s 2020 data and analytics survey, users’ data management priorities for 2020 include supporting advanced analytics, correcting existing data architectures, providing flexible data access via self-service, and handling increasing data volumes. All these and other priorities are ably enabled by an integrated data warehouse and data lake, with modern data design patterns on a modern cloud data platform.
As users take action to support new goals for business analytics and cloud-based data management, they typically modernize two broad areas:
- Data platforms and related tools from software vendors and open source
- User-defined design patterns for data and applications
Note that a data design pattern can range from local designs such as data models to global ones such as the overall design of a database. Furthermore, there needs to be a large-scale design pattern (or data architecture) to organize and govern relationships across multiple data sets and data platforms.
This webinar will describe the current state of data design patterns, plus where successful data management and analytics professionals are taking them.
Webinar attendees will learn:
- Trends and drivers for data design patterns and architectures for data warehouses and data lakes
- How a warehouse and a lake each has an internal design, but also integrates tightly into a larger architecture
- Real-world use cases and infrastructure roles for modern design patterns
- TDWI reference architecture for a unified cloud warehouse-lake
- The role of cloud providers and cloud data platforms in enabling modern design patterns and similar large architectures
- • Critical success factors around selecting a cloud data platform that is conducive to modern data design patterns, such as the integrated cloud warehouse-lake
Philip Russom, Ph.D.