More than ever, accurate data is vital to business success, and organizations worldwide are racing toward budget-friendly, cloud-based analytics solutions that scale dynamically. Centralized analytics and data management solutions can assist an organization in many ways. For example, filtering and delivering the most applicable data to each internal department–like a company’s sales and finance teams–allows each group to operate more independently and effectively to support the larger organization.
When relevant data is easily accessible to the employees who need it, businesses realize enhanced productivity, streamlined processes, and innovations that provide additional value to customers. Also, by giving “ownership” of data to functional groups, companies can more easily adhere to and govern data privacy policies throughout their lines of business.
The convergence of all these factors drives the increasing importance of a data mesh architecture in today’s marketplace.
Data as the new currency
Before I talk more about data mesh, a short backstory is helpful. Many years ago, the value of data as the “new currency” became clear for organizations of all sizes. Today, most organizations make significant investments to capture as much information as possible and store it in data lakes.
However, storing enormous volumes of data without a way to extract relevant meaning isn’t helpful. Organizations must analyze and convert data into insights that drive better development and business practices.
The DevOps methodology chips away at many challenges by aligning operations and development teams to streamline coding processes. In data engineering parlance, DataOps takes everything a step further by ensuring data pipeline observability, data reconciliation, and streamlined workflows.
The role of data mesh
Large organizations have a highly complex data environment. They need more effective ways to combine available information to harvest its potential benefits. Data mesh builds upon the foundation provided by cloud native data technologies and the DataOps model to manage it.
In the simplest view, data mesh architecture extends data management practices. It eases the burden on data analysts by helping tease out the most relevant data for each functional group within a company. With data mesh, each domain’s front-end applications receive a uniquely appropriate feed from the data pipeline. In turn, employees in those departments gain the deeper insights they need to do their jobs more effectively.
Benefits of a data mesh architecture
Beyondsoft’s clients implementing a back-end data mesh architecture gain four key benefits:
- Maximizing data as a product: Reliable data guides modern businesses, so using available information is vital for effective and streamlined work.
- Domain-driven data ownership and architecture: Data needed by one corporate department filters into a different “bucket” than data required by other departments.
- A self-serve data platform: With data mesh in place, team members can get the most from domain-focused, automated front-end apps.
- Federated governance: Since each functional group “owns” its data, it can also manage the data and its associated usage rules.
Data mesh has use cases across verticals
In the finance vertical, data mesh architecture can help a bank’s loan department secure customer-confidential data required to process and deliver customer loans as rapidly as possible. Simultaneously, data mesh can support other employees in the bank’s business planning team who need more general information to monitor long-term income derived from interest on those loans and anticipate corporate profitability.
In the insurance vertical, a claims department needs specific information about customers’ insurance policies and the nature of their claims to process payments quickly. However, the insurance company’s actuarial group may require a completely different, anonymized data set to analyze various demographics and determine policy rates. A data mesh architecture supports individual groups’ needs.
Get started with help from Beyondsoft
As these examples illustrate, adopting a data mesh architecture can streamline operations, assist with federated governance, and empower various corporate departments with near real-time information specific to their role. In today’s fast-moving marketplace, functional differentiators like data mesh architecture can help organizations be more agile and advance their business at a brisker pace.
Reach out to our team at Beyondsoft to discuss how data mesh can benefit your organization and to learn how we’ve helped our other customers.