2 Is a data mesh right for you?

 

This chapter covers

  • Introducing the data mesh to your organization
  • Considering decision drivers before choosing a data architecture
  • Comparing the data mesh to other popular data architectures
  • Transforming your organization’s architecture into a data mesh

In the first chapter, we explained the meaning of data mesh. We also explained why your company should consider implementing it. In this chapter, we answer two other essential questions:

  • Should I implement a data mesh in my business (i.e., what are data mesh drivers)?
  • How much effort does it take to implement a data mesh (i.e., would the benefits outweigh the effort of its implementation)?

The presence of the first question may surprise you in the context of this book. Data mesh has become one of the hottest buzzwords in the industry. But many companies have started to implement it without first considering whether it fits their organizations (or thinking through all of the requirements and ramifications). We have observed several similar rushes toward patterns or practices in the past (including microservices or Agile). A large number of these ended badly, and people blamed the patterns and practices instead of their own implementation mistakes. The truth is, there is no silver bullet. Every pattern or practice has its area of applicability. They come with tradeoffs. Treat a data mesh as yet another tool in your toolbox.

2.1 Analyzing data mesh drivers

2.1.1 Business drivers

2.1.2 Organizational drivers

2.1.3 Domain-data drivers

2.1.4 Minor organizational drivers

2.1.5 Is a data mesh a good fit for me?

2.2 Data mesh alternatives and complementary solutions

2.2.1 Enterprise data warehouse

2.2.2 Data lake

2.2.3 Data lakehouse

2.2.4 Data fabric