A Data Fabric, sometimes referred to as enterprise data fabric or data integration fabric, is a paradigm shift to advanced data integration and analytics. In the scope of modern data management, a data fabric provides the means for collecting, persisting, and analyzing diverse data sources. It also enables software-based integration of all data-related processes, technologies, and capabilities into a single IT infrastructure. Moreover, an enterprise data fabric provides standardized methods to access, store and manage the vast amounts of raw facts of an organization.
In most cases, data fabric infrastructures come with advanced data management features like in-memory data processing for real-time data. Furthermore, they are very scalable and can grow in-line with the business priorities of an enterprise. Hence, data fabrics alleviate the limitations of traditional Enterprise Data Warehouse (EDW) platforms, which are not capable of handling data silos and coping with the different levels of data ingestion. Nowadays, many businesses are adopting data fabric as a new data management approach that fosters efficient read/write access to their massive data sets. They use it as a key enabler for processing, understanding, and analyzing their big data while at the same time delivering faster processing times.
Data Fabric is gaining traction in Enterprise Data Management because it integrates relational databases and data lakes to provide support for both structured and unstructured data. It’s not uncommon for organizations to have multiple databases that store different types of data, but they don’t necessarily integrate with each other. Data Fabric solves this problem by combining databases and data lakes into a single platform that can manage all types of data – including structured, unstructured and streaming – in one place. The need to integrate both structured and unstructured data is one of the biggest challenges facing organizations today. Research firms like IDC predict that most enterprise data will be unstructured in the years to come. This means that traditional architectures will not be able to support the increasing demand for unstructured data management.
Data fabric also integrates data in motion and data at rest. For example, when a customer submits an order, the enterprise system can process that data in real-time, storing it in a relational database, while also executing analytics on the same data to find patterns or anomalies. Moreover, data fabric has features like self-service analytics that allow business users to use their own applications to query the data without having to go through other IT systems. This gives business users more control over their data and improves agility because they don’t need to wait for the IT department to approve new queries or apps.
By using an enterprise data fabric infrastructure, businesses can access all their streaming data from any location, including mobile devices. This is a huge step forward for efficiency. Additionally, enterprises can still use their existing infrastructure. They do not need to invest in new hardware or infrastructure costs when adopting data fabric technology. Specifically, data fabric integrates relational databases and data lakes because many companies have legacy systems that don’t fit into modern architectures. For example, suppose you want to analyze your historical transactional data (e.g., orders) in conjunction with your recent clickstream events (e.g., website traffic). In that case, you will need access to both sources of information at once to perform data analysis across them. Overall, by using data fabric, companies can combine data from various sources inside and outside the company, including public cloud services, on-premises systems, and third-party Application Programming Interfaces (APIs). This enables them to better analyze their data and thereby make better business decisions.
Here are some characteristic examples of how organizations in different sectors take advantage of enterprise data fabric infrastructures:
By and large, the introduction of data fabric has opened many possibilities for enterprise data management. This is a truly promising ground to be in, and data managers need to take advantage of this new technology as soon as possible. The tools within these fabrics will allow businesses to influence their future and provide a method for growth, success, data democratization, and eventually reward the risk takers who embrace this new technology. Hence, when embarking on their data management journey, modern enterprises must consider data fabric solutions.
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