How to Weave Your Data Fabric in Three Steps

Are you drowning in data? As data multiplies relentlessly, many organizations feel that way.

But you need to do more than just keep your head above water. Your data is the source of valuable and potentially game-changing business insights.

A data fabric can help you take control of that data and put its power to work for your organization. Here’s how in 3 steps:

1. Connect all data. Data in silos is of limited value. It might be stored in an enterprise data warehouse, various database management systems, in data lakes, or in lakehouses —whether on-premises, in the cloud, or at the edge. You need to bring together all the data in your organization, both structured and unstructured.
2. Build active metadata. Semantically enriching metadata with a data catalog is key to making the data in your fabric a source of valuable analytic insights. Traditionally, data pipelines have been built to perform the extract, transform, and load (ETL) process using static data models. Data warehouses are a good example. However, when the structure of data is not known (think IoT data, pdf documents, and images), artificial intelligence (AI) is needed to understand, tag, and semantically enrich the data, right before it is used.
3. Automate and orchestrate. To handle very large amounts of structured and unstructured data requires automation and orchestration. For example, data in forms can be accepted or rejected automatically depending on whether it is complete or not. Orchestration tools fueled by active metadata funnel the data to the right analytic projects.

What does all this add up to? When your data is gathered and semantically enriched, users — whether they are technical or not — can define, access, integrate, and share data themselves. This fosters a culture of self-service and collaboration. An enterprise that can organize and enrich data quickly can leverage it for analytic insights. The result is an organization that moves with greater agility.

In addition, your data engineers will be far more productive. Many data engineers spend more than 50% of their time building complex data pipelines. But a data fabric that is built with AI-enabled and automated processes frees up their time to perform higher-order tasks.

Finally, your data operations will be more efficient. When the value of data is understood, it can be placed in the right tier of storage for better price performance. Data that is used for cutting-edge analytics can be kept on more expensive and responsive storage media, while seldom-used data can be moved to less-expensive options.

Without a fabric, the value inherent in your data will go unrealized, even as you swim in that sea of information. Why not start weaving your data fabric today?

For more information, visit: https://www.hitachivantara.com/intelligent-dataops