Top Data Integration Use Cases for the Year Ahead

Businesses generate a lot of data. And it’s become increasingly distributed. Data sources are no longer limited to mainframe and applications but extend beyond the enterprise IT landscape.

Data integration is the process that lets you connect the dots between all your different structured and unstructured data sources, whether it’s social media platform data, app information, payment tools, CRM, ERP reports, or others, and plug that data into analytics and insight solutions to create actionable intelligence for better business decisions or to achieve a business objective.

How does data integration work?

As a process, it’s comprised of the many different architectural techniques, practices, and solutions companies use to achieve their data goals. Since every business has different data goals, there’s no one size fits all method. Still, data integration tools and solutions are usually comprised of a few standard building blocks: users who need data, a primary server, and a disparate or interconnected system of external and internal data sources plugged into the primary server. Users request data from the main server. The main server then intakes, aggregates, enhances, and combines the requested data from the various data sources into a unified set of data that’s delivered to the user.

Why is data integration important?

Overall, data integration helps to transfer and sync different data types and formats between systems and applications. It’s not a one-and-done event, but a continuous process that keeps evolving as business requirements, technologies, and frameworks change. As organizations generate more and more data, it provides an opportunity for better business insights. Your data integration strategy determines how much value you can get out of your data, and which data integration type will work best for your use cases and initiatives.