7 Best Reasons to Work on Next Generation Federated Data Integration Model

Data integration (DI) has undergone an outstanding advancement in recent years. ETL (extract, transform, and load), data federation, replication, synchronization, changed data capture, data quality, master data management, natural language processing, business-to-business data exchange, and many more set of techniques are known as data integration. Likewise, vendor products for DI have achieved maturity. The users have advanced their DI teams to epic proportions. Competency centers regularly staff DI. Modern practices such as collaborative DI and agile DI continue to come up. DI, as a domain, has earned its autonomy from relevant practices such as data warehousing and database administration. Next-generation Federated Data Model (NFDM) for developers allows integrating APIs and Enterprise Data Sources in ways that were formerly believed to be impossible. Federated Data Model for developers interprets SQL like a regular database, but also, APIs and Enterprise Data Sources are transmitted within their language.

Here are the 7 Effective Reasons to Work on Next Generation Federated Data Integration Model.

The next-generation data integration is a recourse to fix the shortcomings of the previous generation DI: Next-generation requirements, particularly real-time, data services, and high availability, requires a modern architecture, whereas most previous generation DI lacks a recognizable architecture. Older ETL solutions, designed for serial processing, need to be redesigned for parallel processing to encounter next-generation requirements for vast data volumes.

Businesses are changing rapidly than ever before: Businesses have frequently been adapting to boom-and-bust economies, financial crises, shifts in global dynamics or competitive pressures, and recession. Real-world applications and business objectives, which are influenced by economic issues, are supported by DI. DI solutions need to be occasionally modified to align with technical goals and business objectives for data.

Some DI solutions need to be improved or replaced on a serious note: Based on low-end techniques such as hand-coding, flat files, and file transfer protocol (FTP), most DI solutions for B2B data exchange are bequests. If modern DI techniques are to be brought into B2B. Data exchange these legacies need a makeover or need to be replaced. Similarly, older data warehouses, customer data hubs, and data sync solutions also need a makeover.

The next generation is about tapping more tasks of DI tools one already has: Most DI programs have supported data federation for a few years now, yet only 30% of users have tapped this capability. Recent capabilities for real-time, micro-batch processing, changed data capture (CDC), messaging, and complex event processing (CEP) is yet to be tapped.

For most DI solutions, unstructured data is still an unexplored horizon: Many vendors DI platforms now support text analytics, text mining, and other forms of simple language processing. In text-laden industries such as insurance, healthcare, and federal government, handling non-structured and complex data types is a preferable generational landmark.

DI is set to become an IT infrastructure: You need to think ahead of time when data integration infrastructure is open and accessible by most of the business the way that local area networks are today. Developing DI into an allocated infrastructure facilitates business integration via shared data.

Even mature DI solutions have room to grow: NGDI concentrates on the next stage of a carefully planned development.