3 Key Benefits of Implementing a Data Fabric for Your Business
Welcome to Data Fabric Threads — a blog series dedicated to educating and promoting new features of Data Fabric products at IBM and some of the great minds behind them. Data Fabric Threads is focused on taking a feature oriented approach to understanding Data Fabric with posts directly from product managers and engineers.
This a repost of the first blog post in the Data Fabric Threads series, originally published on LinkedIn.
Think of each place you store your data as a thread. Each thread is a stream of data coming from a particular source — a customer database, social media sentiment, or transaction information. Each data thread is providing key data for your organization. Individually, each thread is siloed; isolated threads are limited in their ability to drive business outcomes.
However, when these data threads are stitched together, we can bridge siloed data and create a Data Fabric.
What is a data fabric?
A data fabric is an architectural approach to simplify data access in an organization to facilitate self-service data consumption. This approach combines data from a variety of complex sources, regardless of location, reducing data silos across use cases like data governance, data integration, single customer views, and trustworthy AI.
Using metadata, a data fabric architecture helps drive business outcomes by not only helping keep track of where data is stored but also pulls together data to make easier to model, integrate and query any data sources, build data pipelines, and integrate data in real-time. Data Fabric emphasizes accessibility, while also maintaining security and governance of the data.
Three Key Benefits of Data Fabric
Implementing a Data Fabric can reduce “time for integration design by 30%, deployment by 30%, and maintenance by 70%.” (Gartner). Data Fabric provides three key benefits — (1) improved data protection, (2) intelligent integration, and (3) democratization of data.
Improved Data Protection — One of the key features of data fabric is its ability to combine data sources. By being able to efficiently combine data sources, data silos that existed previously will vanish. However, these combined data sources does not mean compromised data security. Data Fabric is intelligent enough to understand how to control the flow of data. In addition, data fabric can ensure that specific data is only available to certain people.
In the Data Management Layer, organizations control where the data moves while maintaining security of their systems. In the Data Ingestion Layer, organizations find links between structured and unstructured data.
Intelligent Integration — Alongside providing access, data fabric allows for more seamless management of the data. Intelligent integration of data also encompasses ensuring data is compliant with regulations of a country or industry. In addition, this is where private information is masked and protected.
In the Data Processing layer, the organization refines the data to ensure that only relevant data is surfaced for data extraction. For example, redacting or masking social security numbers for analysts who are looking at loan approvals. In the Data Orchestration layer, the organization transforms, integrates, and cleans the data, making it usable for teams across the business. This orchestration allows for data to be consistent across the organization and simplifies use.
Democratization of Data — Most importantly, bringing this data together and making it accessible to the right people will allow them to use the data to drive business outcomes. Data Fabrics allow more people in the company to access data and ultimately decreases previous data silo bottlenecks.
In the Data Discovery Layer, the organization surfaces new opportunities to integrate disparate data sources. In the Data Access Layer, the organization ensures the right permissions for certain teams to comply with government regulations, surface relevant data using dashboards and other data visualization tools. Ultimately, democratized data means that different teams to pull from the larger data sources to discover business insights.
Conclusion
Data fabric breaks down data silos to create a more accessible, secure, and integrated data landscape. Most importantly, data fabric decentralizes data so organizations can make data driven decisions faster. Just like common fabric, data fabric can be created in many ways.
Data fabric allows business to more easily access, move, and analyze their data to manage business outcomes in an increasingly data driven world.
