Enterprises are producing a staggering amount of data every day. Disparate data sources, lack of access, and complex data integration challenges can prevent organizations from fully utilizing the data they collect. As data continues to grow, these issues compound. A data fabric helps organizations overcome these challenges.
What is a Data Fabric?
Data fabric is an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. Over the last decade, developments within the hybrid cloud, artificial intelligence, the internet of things (IoT), and edge computing have led to the exponential growth of big data, creating even more complexity for enterprises to manage. This has made the unification and governance of data environments an increasing priority as this growth has created significant challenges, such as data silos, security risks, and general bottlenecks to decision-making. Data management teams are addressing these challenges head-on with data fabric solutions. They are leveraging them to unify their disparate data systems, embed governance, strengthen security and privacy measures, and provide more data accessibility to workers, particularly their business users.
These data integration efforts via data fabrics allow for more holistic, data-centric decision-making. Historically, an enterprise may have had different data platforms aligned to specific lines of business. For example, you might have an HR data platform, a supply chain data platform, and a customer data platform, which house data in different and separate environments despite potential overlaps. However, a data fabric can allow decision-makers to view this data more cohesively to better understand the customer lifecycle, making connections between data that didn’t exist before. By closing these gaps in understanding customers, products, and processes, data fabrics are accelerating digital transformation and automation initiatives across businesses.
Why do you need it?
Modern data management is complex. New technologies, new kinds of data and new platforms are being added all the time. And it’s not easy to change and bolster data management methods with each shift in technology. As technology innovation speeds up, traditional approaches to data management become unsustainable.
A data fabric can help you address rapid changes in technology and minimize disruption. The adaptable nature of data fabric can help you create a data management strategy with augmented data integration.
A data fabric is agnostic and works on different deployment platforms and with all kinds of data processing methods. It facilitates the use of data as a strategic asset by abstracting complexity. And with a data fabric, you can combine, access, share and govern any data on any platform from any location.
What are the biggest benefits?
A main benefit of a data fabric is increased ease of use, through consistent distributed access to data. This can be broken into three sub-benefits:
Accelerated data delivery, without compromising quality
Data fabric technology shortens the time from data discovery and data ingestion to delivery and consumption. Moreover, data quality is continuously refined through AI and ML algorithms that use active metadata to integrate and manage enterprise data.
Self-service consumption and collaboration
Using a data fabric solution, both business and technical users can quickly and consistently find what they’re seeking. This is vital at a time when organizations are dealing with a proliferating number of data sources and silos, plus big data use cases. Data fabric weaves them all together, with an easy-to-follow thread.
Automated integration, management, and data governance
Because data fabric architectures are highly automated, they can perform tasks that once required significant manual effort, such as integrating data sources and analyzing the quality of their data. Automation saves time and also reduces the risks of errors and compliance issues.
Data Fabric Use Cases
There are many different uses for a data fabric, but a few are highly common. One such common example is the virtual/logical collection of geographically diverse data assets to facilitate access and analysis. The data fabric is usually used for centralized business management in this case. Because the distributed line operations that collect and use the data are supported through traditional applications and data access/query interfaces, there is a lot to be gained by organizations that have regional or national segmentation of their activities. These organizations often require central management and coordination.
Another major use case for data fabrics is the establishment of a unified data model following a merger or acquisition. When these take place, the database and data management policies of the previously independent organization often change, meaning it becomes more difficult to collect information across organizational boundaries. A data fabric can overcome this by creating a unified view of data that enables the combined entity to harmonize on a single data model.
Consider a data fabric to meet your growing data needs
While many organizations are undergoing their digital transformation, much of IT infrastructure history is about playing catch-up with their traditional data. Thus, it’s not surprising that data architecture, one of the fastest-growing areas of business, often requires a revamp. When it comes to data storage, access, and usage, it’s nearly impossible for anyone to keep up. However, an increasingly popular approach for addressing scale is automation, which data fabrics provide in spades for essential functions such as data governance, data protection, and integration, among other things. Now that organizations are embracing technologies such as data lakes, data warehouses, and others, it makes sense to add the fabric approach before your organization grows any further.