Modernizing Data Integration with Data Fabric Architecture

Data integration has become an essential part of the data management process. It is quite complex to perform data integration and data management as there are many challenges. Data Fabric is a new architecture that can be used to modernize data integration and data management. Data and analytics specialists need to move past conventional data management methods and toward cutting-edge solutions like AI-enabled data integration in order to decrease human mistakes and total expenses. 

By providing consistent data, efficient data management promotes operational excellence. Meanwhile, inadequate risk management, data loss, and faulty data are all consequences of data management mistakes. Making judgments based on inaccurate data causes businesses to lose enormous sums of money. Organizations today have to cope with settings that are more varied, dispersed, and complicated. As a result, data administration has also grown more difficult. Leaders in data and analytics must move beyond conventional approaches that result in expensive but ineffective data integration cycles, high maintenance costs for earlier integrations, a lack of real-time and event-driven data exchange, etc.