In an increasingly digital world, most global enterprises are forced to find practical ways of adequately dealing with their data lest they fail to maximize existing business opportunities. Operating in complex combinations of on-premises and cloud environments can prove to be a daunting task. It is for this reason that data fabric is considered a standard solution to issues of data management. Incorporating data fabrics into your data management system can significantly increase your chances of quickly adapting to changing technological needs.
Data fabric
What is a data fabric? In simple terms, data fabric refers to the process of creating a single environment that allows for the coordination of existing architecture and technology. In simple terms, a data fabric enables you to run suitable applications at the right time and place.
What are the components of a data fabric?
Like any other system, a data fabric is made of several components that work in a unified manner to achieve desired results. Here are the critical components that make up for an efficient data fabric system:
Data ingestion
Data ingestion is a critical element in a data fabric. It provides the basis upon which data from various sources like databases, cloud source applications, and data streams are formatted into a desirable design. Through data ingestion, real-time and stream processing are made easier.
Data management and intelligence
This component allows you to regulate who views your data. Sensitive data should be kept out of the public domain since such information can easily be used to compromise the execution of crucial IT functions within an organization. Global structures such as lineage control and metadata management can be integrated using this component.
Data orchestration
This component is designed to coordinate the functionality of every current stage. It focuses on streamlining end-to-end data workflow by allowing you to define how often you should run the pipelines and how best you can manage data produced by those pipelines. Unless the different components of a data fabric are well-coordinated, achieving seamless data management can become mission impossible.
Data discovery
In this layer, you can undertake data management techniques such as data modeling, data curation, and data preparation. Once this is done, data analysts can easily find and consume data across two silos in a manner that appears data was from the same data set. Therefore, this is probably the most essential layer of data fabric as it seeks to solve the problem of silos. Anyone in sync with IT will tell you that silos pose a major threat to your data management system and dealing with them should be a top priority.
Data access
This layer is responsible for ensuring that your data is seamlessly transmitted to data analysts. To perform this function, data access employs APIs, dashboards, and data services. Keep in mind that the main aim of this layer is to build semantics, create intelligence and formulate rules that are critical in formatting existing data and ensuring they exist in a desirable format. One that is authentic and easy to understand. Easy access to your data allows you the opportunity to make the necessary adjustments before systems become redundant.
Final thought
Has it ever struck you that the reason your enterprise is not making any meaningful progress is as a result of a flawed data management approach? How you organize your data will determine whether you succeed or fail. As discussed in this article, incorporating a data fabric into your data system can help to better manage your data to promote efficiency and the ultimate success of your venture. Whether you are running a small enterprise or a multimillion company, you stand a chance of benefiting a lot from using data fabric.
