Best Practices in Collaborative Data Integration
Collaborative data integration is a collection of user best practices and software tool functions that foster collaboration among the growing number of technical and business people involved in data integration projects and initiatives. Collaboration requirements for data integration (DI) projects have intensified greatly in this decade, largely due to the increasing number of DI specialists within organizations, the geographic dispersion of DI teams, and the need for business people to perform stewardship for DI. Furthermore, gone are the days when DI specialists could work in isolation. Today, DI specialists must collaborate with specialists in other data management disciplines, especially data quality and master data management. And many of them active in data governance and competency centers, which are collaborative by nature. This presentation discusses the best practices, organizational structures, and software tool functions that can help DI professionals adapt to an increasingly collaborative world.
You will learn:
- What the collaborative tasks of DI are and why they’re increasingly important
- Trends that are making DI even more collaborative
- How collaboration for data integration reaches both technical and non-technical people, who may work in multiple organizations
- Which approaches foster collaboration to bring the extended team together
- How collaborative data integration’s requirements for tools, techniques, and teams vary among organizations and projects
Philip Russom, Ph.D.