Data Mesh is the Answer to Your Integration Challenges. Fact or Fiction?
Data mesh is a hot topic in data management circles. But what exactly is data mesh and why does it continue to spark debate?
Paul Lacey, Senior Director of Product Marketing at Matillion, explores the concept in depth in Data Mesh: Fact or Fiction , a webinar sponsored by Database Trends and Applications (DBTA) and now available for streaming.
The data mesh: Solving today’s enterprise data challenges
A data mesh is a modern, distributed architecture designed to meet some persistent enterprise challenges in centralizing and managing data at scale:
Difficulty creating a single source of the truth
For decades, establishing a single centralized data repository has been a challenge for businesses, and data is only increasing in its variety, volume, and velocity.
Shifting management of ETL pipelines
If IT staff members building an ETL pipeline leave an organization, getting up to speed can be a lengthy and complicated process for team members taking over.
Separation of data processing expertise and SME knowledge
The division between data engineers and business SMEs can create an inefficient game of “telephone” within an enterprise.
Unresponsive centralized analytics
When analytics teams are overburdened, data consuming business stakeholders may be waiting too long for the information they need, stalling projects and initiatives.
Data mesh defined
The data mesh approach to enterprise data management centers around four core tenets:
- Domain ownership – Segmenting data ownership within an organization so that individuals take responsibility for its usefulness
- Data as a product – Giving datasets a top priority within an enterprise
- Infrastructure abstraction – Finding systems and solutions that free data consumers from worrying about underlying IT infrastructure
- Distributed governance – Ensuring that data is appropriately governed across an organization
How do you achieve it?
Data mesh isn’t an off-the-shelf solution that an enterprise can simply purchase and deploy—it’s a far-reaching approach that requires a confluence of an organization’s people, processes, and technology. And it may be the way forward in addressing your company’s integration challenges.
So, how do you make it happen?
The webinar outlines steps involved in creating a virtualized and a physical data mesh, explaining why each approach may be optimal for an organization’s specific needs. It also explores “fact or fiction” with common ideas about data mesh as a concept:
- FICTION: Data mesh requires a different set of technologies
- FICTION: It has the potential to resolve all data integration issues
- FICTION: It’s the recommended approach for any type of organization
- FACT: It reduces data downtime
- FACT: It accelerates the adoption of ML, AI, and other analytics technologies
- FICTION: Its implementation is solely the IT department’s responsibility
- FICTION: It’s a brand-new concept
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