Moving Beyond Data Integration with Data Collaboration

Chapter 4. Build a Resilient Data Architecture

Regardless of which data collaboration platform you choose to deploy, your implementation must deliver several core features if you want to achieve a truly seamless data collaboration experience and fully leverage the power of data collaboration. This is vital to note because, although all of the data collaboration platforms we discussed in the previous chapter have the potential to enable data collaboration without integrations, simply deploying those platforms is hardly enough to implement this concept.

Instead, you should strive in your deployments to adhere to the following principles and practices, which are what make a data collaboration architecture different from other types of data integration or pooling architectures.

Start with New Integration Projects

Before we begin discussing specific data collaboration features and characteristics, here is a point of advice: most businesses will find it much easier to apply this concept to projects where new integrations are needed, such as migration of systems, connecting two applications, or updating, enhancing, or building new applications, rather than ripping and replacing to apply it to point-to-point integrations of applications or systems.

We suggest that you begin implementing this technique by deploying new projects according to the data collaboration playbook rather than trying to replace integrations you’ve already built for existing applications with connection methodologies ...