Data integration is what makes business analytics possible. That means that data integration must be “modern”—that is, up to date and in step with what organizations’ users, data scientists, and digitally transformed applications and processes need right now. Legacy technologies and practices can hold organizations back from realizing the potential of their data for driving smarter decisions and actions. It can also make it difficult to effectively govern data and improve its quality and findability, especially as sources become bigger and more diverse.
This presentation will examine TDWI research to highlight trends and directions in data integration. It will discuss challenges and opportunities organizations are facing in modernizing data integration, including through adoption of cloud-based services and platforms. Artificial intelligence, automation, real-time data streaming, and end-to-end data pipelines are some of the key factors driving the evolution of modern data integration. We will discuss the importance of gaining a big-picture view that brings together data selection, acquisition, preparation, transformation, and integration.
Topics to be covered include:
- Keeping pace with what diverse users need
- Data catalogs and metadata management for faster location and integration of data
- Data virtualization and federation alternatives to traditional integration
- Dealing with hybrid, multicloud environments
- Future trends: semantically rich AI-infused data integration, ELT, data lakehouses, and more