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Five Key Capabilities You Need in a Data Fabric Solution

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Data has become the backbone of every organization. However, managing data can be daunting, especially when dealing with large volumes from different sources. According to this survey by CIOinsight, about 60% of organizations are not confident in their data and analytics. This is where a data fabric solution comes into play.

A data fabric solution is a unified platform that seamlessly integrates data from multiple sources and provides a comprehensive view of the entire data landscape. But not all data fabric solutions are created equal. To gain a competitive edge in your industry and leverage your data to its full potential, it is crucial to choose a data fabric solution that offers key capabilities.

This article highlights the benefits of implementing a data fabric solution and discusses five key capabilities you need in a data fabric solution to ensure that your organization can effectively manage its data and drive business success.

Benefits of implementing a data fabric solution

A data fabric solution is a comprehensive data management approach that offers organizations several crucial benefits.

  • Data agility: A data fabric solution offers agility in data management by enabling organizations to adapt quickly to changing business needs. It allows organizations to integrate new data sources and formats, perform data transformations, and build new applications on top of the data fabric.
  • Improved data quality: A data fabric solution provides capabilities such as data cleansing, data enrichment, etc., which can help improve the data quality. This is important because poor‑quality data can lead to incorrect decisions.
  • Better data governance: A data fabric solution provides capabilities such as data governance, which ensures that the data is managed to meet increasingly complex and stringent regulatory and compliance requirements.
  • Cost savings: Data fabric solutions can also help organizations save costs associated with data management. By reducing the need for data silos and integrating data from various sources, organizations can eliminate duplicate data and reduce the cost of maintaining multiple data systems. Additionally, data fabric solutions can help organizations optimize their data storage and processing costs by providing a scalable and flexible solution.

Five key capabilities of a data fabric solution

Implementing a data fabric solution offers immense benefits, as seen above. But as stated earlier, not all data fabric solutions are created equal, and some may not meet your organization's needs.

To help you make an informed decision, below are five key capabilities you need in a data fabric solution.

1. Comprehensive view of your data

Aside from integrating data from multiple sources, another important feature that your chosen solution should have is a comprehensive view of data, giving you a single source of truth across your organization.

Beyond giving you a single source of truth across your organization, your data fabric solution should allow you to build single views according to business needs. For example, let’s say your engineering team wants a view model with user interaction data (website visits, user flow, etc.) and a data science team model with product information. The ability to build single views with each separate dataset will greatly improve the development cycle.

Also, your chosen data fabric solution should offer low‑code/no‑code capabilities so that anyone in your organization, technical or nontechnical, can create a data aggregation pipeline.

2. Real‑time data availability and access

Real‑time data availability and access are essential for organizations to make informed decisions quickly and to respond rapidly to changing business conditions. Data fabric solutions use technologies such as in‑memory data processing, caching, streaming, etc., as well as an event‑driven architecture based on the data streams to achieve real-time data availability and access.

Moreover, your organization’s solution should integrate seamlessly with change data capture (CDC) systems. CDC systems detect changes occurring on a data source and emit the corresponding event in small, near real‑time increments to the configured event streaming platform.

3. High performance and scalability

High performance and scalability are crucial considerations for any data fabric solution. A high‑performance data fabric solution can handle large volumes of data, process it quickly, and deliver it to users in real time. As the data volumes grow, the solution must be able to scale to handle the increased load without compromising performance.

A good way to test the performance and scalability of a data fabric solution is to run benchmark tests of several solutions using sample data. Though most solutions aren’t free, solutions like Mia‑Platform Fast Data offer free demos that allow you to determine whether they are the right fit for you before committing.

4. Robust data governance

Robust data governance ensures that the data within the data fabric is accurate, consistent, and trustworthy. To be sure your data fabric solution has robust data governance, ensure it has the following key features.

  • Data Lineage: Data lineage tracks the movement of data from its origin to its current location. It helps to ensure data accuracy and enables users to trace back the data to its source, which is crucial for regulatory compliance.
  • Data Security: A data fabric solution with robust data governance should have strict data security policies to protect sensitive data. This includes authentication, authorization, encryption, and access control policies such as role‑based access control (RBAC).
  • Compliance: Compliance with regulations like GDPR is crucial for data governance. The ideal data fabric solution for your organization should have built‑in compliance features that ensure that data is collected, stored, and used in accordance with these regulations.

5. Cloud-native architecture

Finally, a cloud‑native architecture is ideal. This enables it to run seamlessly in cloud environments and leverage cloud services like auto‑scaling, data warehousing, and serverless computing.

A cloud‑native architecture is characterized by its ability to handle containerized workloads and microservices, which allows for high scalability and fault tolerance. This makes it easier to scale the data fabric solution as data volumes grow and move workloads between different environments — on‑premises cloud environments, including public, private, and hybrid clouds — as business needs change.

Additionally, a cloud‑native architecture allows for more efficient resource utilization, as resources can be dynamically allocated and released as needed, reducing costs, increasing efficiency, and addressing sustainability.

How Mia‑Platform Fast Data can help you achieve your business goals

When choosing a data fabric solution, it’s important that your choice satisfies all your requirements and is sufficiently scalable to keep up with your present and future business goals. By considering the five capabilities outlined in this article, you can be sure to make a good decision.

Mia‑Platform Fast Data is an excellent option for many organizations, as it allows them to securely manage their data, ensuring data consistency and correctness across all channels with the Command and Query Responsibility Segregation (CQRS) pattern.

To learn more about Mia‑Platform Fast Data, check out this white paper on the advantages of Fast Data and so much more.


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Paolo Martinoli

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