What is Data Fabric?

Data Fabric is a design concept that makes it easier for organizations to deal with the growing and complex data ecosystem. It provides integration of Data and Connection processes. It supports the design, use, and distribution of data in all environments such as the cloud environment.

Organizations had previously purchased different CRM systems and machines to store their data in order to apply analytics. Then Hadoop, Spark, and Kubernetes technologies emerged. And many companies are still trying to come up with their own solutions. This results in high costs, slow integration, difficult access to searched data, and frequent renewals.

It can be explained Data Fabric as follows. For example, an artist’s music is recorded on a laptop, a cloud, or any mp3 recorder. The music is then uploaded to a medium accessible to the end consumer, such as Spotify or Youtube. The consumer can listen to this music (data) through various channels (Apps, API, services, etc.) from the devices they use (headphones, computers). The person opened the Spotify app using their phone and started music. Then he went to his computer and cut the music from the phone and made him continue from the computer. Afterward, he liked the music on the Spotify interface using his smart watch on his arm. This data describes the fabric. The word fabric in Data Fabric represents the interconnection of applications and services, such as stitches in the fabric. These technologies make producers and consumers more connected with each other.

It can be explained the data fabric for organizations is as follows. With the development of the Internet, cloud computing emerged. And this caused the data to increase exponentially. We can clean up this data mess with the data fabric design concept. First of all, we must store the data coming from our data sources with the right technologies (eg NoSQL, SQL, and Files). With this step, it is easy to see which data is where. From here, the data warehouses to be distributed are fed. And data scientists can retrieve desired data from these distribution data warehouses in various ways. With the data fabric structure, data scientists can quickly access data with a significant connection from the initial data sources.