Data Mesh Vendors and Buyers Guide

The concept of data mesh first appeared in Zhamak Dehghani’s landmark 2019 article. Since then, data mesh has rapidly transformed from a proposal into a functional technology that is revolutionizing how businesses use data, work together, and drive innovation.

The data mesh market is still in its infancy, but already, there are several data mesh vendors with game-changing offerings.

This article is intended for CIOs, CDOs, data architects, data engineers, data scientists, and other stakeholders interested in discovering how a data mesh architecture can improve their business.

Data mesh is an emerging data architecture for managing and delivering enterprise data. It is based on the belief that business domains should be able to define, access, and control their own data products, without relying solely on centralized data teams.

The data mesh concept is based on the following 4 principles:

1. Data ownership and architecture is domain-oriented and decentralized

2. Data is delivered as a product

3. Data infrastructure is a self-serve data platform

4. Data governance is federated

In a decentralized, domain-oriented data mesh architecture, datasets are integrated, processed, and managed by data products, which deliver clean and unified data to authorized data consumers on-demand.

Although data governance is distributed (each business domain governs its own data products), centralized data governance tools are still necessary, with security policies, and compliance standards, fully enforced.

Business outcomes are inextricably tied to how organizations manage and utilize data. Here’s how data mesh vendors can help you improves business, data management, and organizational performance.

Business drivers for data mesh

• Enables faster data delivery
  Data mesh speeds up and democratizes data delivery with a self-service approach to data access. At the same time, the mesh conceals the underlying data complexities from users.

• Supports data-driven insights
  Since domain teams define and manage their own data products, they are free to analyze and operationalize them according to their needs. This allows domains to accelerate decision making and extract more value from their data.

• Increases agility and scalability
  Data mesh decentralizes data management and shifts data ownership over to the business domains. As a result, it reduces reliance on centralized IT teams, fosters domain autonomy, and positions organizations to utilize more data.

Data management drivers for data mesh

• Improves data quality and governance
  Domain-based data operations, combined with automated data governance enforcement, promote easier access to fresh, high-quality data.

• Ensures compliance
  Improved visibility, quality, and governance models enabled across the data mesh make it easier to respond to emerging regulations. Plus, automated rules related to data anonymity and access controls make it easier to maximize the value of data while remaining compliant with data privacy regulations.

Organizational drivers for data mesh

• Create cross-functional domain teams
  Unlike centralized data architectures, in which highly-skilled data teams are responsible for creating and maintaining data pipelines, data mesh gives domain experts control over data. This leads to greater IT-business cooperation, enhanced domain knowledge, and greater business agility.

• Foster data-driven cultures of innovation
  As the custodians and controllers of their own data products, business domain teams have the autonomy to experiment with the data however they like. This experimentation, combined with the motivation to ensure the quality of their own data products, increases analytical capabilities, innovation, and outcomes.

  
  
  

When evaluating data mesh vendors, make sure they offer all of the following capabilities:

• Support for the 4 data mesh principles
  This is the starting point, including decentralized domain ownership, treatment of data as a product, self-service platform, and federated data governance.

• Data cataloging
  The solution must identify, classify, and build an inventory of data assets, and visually display information supply chains.

• Data engineering
  The vendor should enable the quick assembly of scalable and reliable data pipelines that support analytical and operational workloads – with common data preparation flows, productized for reuse by the domains.

• Data governance
  The data mesh must distribute certain quality assurance, privacy compliance, and data availability policies and enforcement to the business domains, while maintaining centralized governance over company-wide data policies.

• Data preparation and orchestration
  The data mesh model ought to enable quick orchestration of source-to-target data flows, including data cleansing, transformation, masking, validation, and enrichment.

• Data integration and delivery
  The vendor should be able to access data from any source, and pipeline it to any target, in any method: ETL (bulk), messaging, CDC, virtualization, and APIs

• Data persistence layer
  The vendor should selectively store and/or cache data in the data center, or within individual domains, to enhance data access performance.

Of all data mesh vendors, the K2View Data Product Platform is outstanding because it:

• Can be deployed on premises, in the cloud as an iPaaS (Integration Platform as a Service), or across hybrid environments
• Integrates all data, from all sources, into any number of data products, for secure distribution among the business domains.
• Aggregates business entity data into a secure, high-performance Micro-Databases, ensuring business entity data is always fresh, and accessible to authorized users.
• Provides centralized data governance, cataloging, and modeling, while providing autonomy and self-service access to data by business domains.
• Supports both analytical and operational workloads.
• Unites all company domains via a federated alliance by providing a single, trusted, and holistic view of all business entity data.
• Can be deployed in weeks and adapt to change on the fly.

As the first Data Product Platform in the market, K2View is uniquely capable of supporting core operational workloads in a data mesh, including data masking, data anonymization, synthetic data generation, data tokenization, customer 360, legacy application modernization, data migration and more.