Moving Beyond Data Integration with Data Collaboration

Chapter 5. Getting More from Data Collaboration

The last chapter walked through the fundamentals of getting started with data collaboration that doesn’t require integrations—including how you need to think and act to place the technique at the center of your data architecture and collaboration strategy.

But the practices we covered, such as treating data as a network of connected data products, represent only the beginning of the full potential of a data collaboration-centric approach to data management that moves beyond integrations. Once you’ve gotten your strategy off the ground, you can take additional steps to derive more value from it.

This chapter explains those steps and the ways in which they help organizations double down on the agility, efficiency, and simplicity that data collaboration brings to integration. It also discusses how data collaboration complements and reinforces other key practices, such as digital transformation and measuring the impact of new digital investments.

As with the previous chapter, the practices described here can be supported using any data collaboration platform—although, your platform won’t necessarily enable all of these features using out-of-the-box configurations. In many cases, you’ll need to set up and manage your data collaboration tools in a specific way to meet the following goals.

Embrace Standards

There are many ways to approach data collaboration and many tools to help enable it, as we noted in Chapter 3. However, no matter ...