Data lake: how Red Hat maintains data quality across multiple Drupal sites
Data accuracy and consistency is an important goal for any organization.
Maintaining data quality across multiple websites and applications (Drupal or otherwise), with different teams managing the same data in multiple systems, becomes complex and difficult to manage. Having a pool of data becomes an attractive solution to resolve some of these issues and allow for greater transparency and consistency across an organization. But, creating a scalable, reliable, and useful system can brings its own challenges.
Join us, as we explore several ways that Red Hat is using a data lake architecture to share data between different Drupal sites.
We’ll cover:
- What is a data lake?
- The benefits, challenges, and considerations of using a data lake.
- Several ways Red Hat has integrated a data lake architecture with Drupal.
- Lessons learned along the way.
When: to
Room: Room 303-305
Track: development & coding
Learning Objectives
1. Evaluate whether a data lake architecture will solve your data sharing needs.
2. Design and implement a data lake architecture.
3. Integrate Drupal with a data lake implementation.
Prerequisites
Content management. Data model and schema concepts.
Synopsis
Explore how Red Hat uses a data lake architecture to share data between Drupal sites in several different ways.