Data Mesh definition
Data mesh is a decentralized data architecture to make data available through distributed ownership of data. Various teams own, manage and share data as a product or service they offer to other groups inside the company or without. The idea is that distributing ownership of data (versus centralizing it in a data warehouse or data lake with a single owner, for example) makes it more easily accessible to those who need it, regardless of where the data is stored.
You can imagine why this might be a hot topic in the data ecosystem. Companies are constantly looking for ways to make more data available to more users more quickly. The data mesh conversation has continued in data ecosystem leader blogs we’ve gathered in our Q3 roundup.
VP Product Marketing and Analyst Relations at Alation, Mitesh Shah, interviews former Gartner Analyst Sanjeev Mohan in this Q&A-style blog. Mohan shares his definitions of data mesh, data fabric and the modern data stack and why they’re such hot topics at the moment. Mohan suggests the possibility that new terms (like data mesh) are actually history repeating itself, dives into what these new strategies and architectures bring to the table for data-first companies and identifies the pros and cons of centralizing or decentralizing data and metadata.
Eric Gerstner, Data Quality Principal, Collibra leverages his background as a former Chief Product Owner managing technology for digital transformation to dive into the data mesh concept. He explains that “No amount of technology can solve for good programmatics around the people and process.” He sees data mesh as a conceptual way of tying technology to people and processes and enabling an organization to improve its data governance. This article helps to shed light on the narrative of data mesh and how it fits into modern data organizations in both the immediate and further-out futures. He sees data mesh as key to linking people and processes – people that know how to interpret and organize data and the processes that drive and collect data into the organization itself.
This blog by Matillion really unpacks the concept of data mesh at a fundamental level. It’s really about bringing data out from its usual role as a supporting player and elevating it to a product in and of itself. It’s about “productizing” data and offering it to customers within and without the company. Customers have an expectation of the quality of the product and the service they are utilizing. A data mesh can help data owners meet those expectations. Furthermore, this blog explains the steps necessary to create a data mesh with Matillion. Matillion’s low-code/no-code platform is an ideal partner for individual data teams that include a mix of domain and technology expertise.
Data Mesh Architecture: ALTR's Take
We’re all about making data easier to access – for authorized people. As the data mesh architecture proliferates, companies need to ensure that all data owners across the company are enabled with the appropriate tools in place to keep their sensitive data from spreading recklessly – to meet both internal guidelines and government regulations on data privacy. A data mesh architecture really democratizes data ownership and access, and ALTR’s no-code, low up-front cost solution democratizes data governance to go hand in hand with it. Data owners from finance to operations to marketing do not need to know any code to implement data access controls on the sensitive data they’re responsible for.