Data Integration (DI)

What is data integration?

Data integration is the process of combining data from many different sources into an application. You need to deliver the right data in the right format at the right timeframe to fuel great analytics and business processes.

A data integration project usually involves the following steps:

Quality is a relative and never-ending judgment, one that needs to be defined by the business (or business unit) that’s consuming the data. An essential element of holistic data governance, trustworthy data serves critical business needs across the enterprise—from legal to finance to marketing and beyond.

Driving data quality requires a repeatable process that includes:


  • Accessing data from all its sources and locations, whether those are on premises or in the cloud or some combination of both.
  • Integrating data, so that records from one data source map to records in another (e.g., even if one dataset uses "lastname, firstname” and another uses "fname, lname,” the integrated set will make sure both end up in the right place). This type of data preparation is essential for analytics or other applications to be able to use the data with any success.
  • Delivering integrated data to the business exactly when the business needs it, whether it is in batch, near real time, or real time.


Informatica has been positioned as a leader on the Gartner Data Integration Tools Magic Quadrant for 10 consecutive years.

Experts at Bloor Research estimate up to 80% of a data scientist's time is spent preparing the data rather than analyzing it.

How you benefit from data integration

You’ve learned from bitter experience that if you’re not managing your data, the data will overpower your business. But you wouldn’t write your own database or code an enterprise ERP system in your IT shop. Likewise, you shouldn’t hand-code your data integration projects. You need a proven, automated, and agile data integration solution that lets you combine or migrate data swiftly, painlessly, and cost effectively—one that gives you:


  • Universal access: Can you get to the data, whether it’s in a legacy database, the cloud, Hadoop, or a hybrid ecosystem?
  • Built-in data quality: If you move inconsistent or incorrect data to a new application, will the data be cleansed? How effective will the new application be?
  • Vendor stability: Invest with a proven vendor you know will be around in the future.
  • Business-IT collaboration: You’ll want a tool that reduces the back-and-forth between business and IT so that businesses get exactly what they need, and quickly.


Why Informatica?

or more than 20 years, Informatica Data Integration has refined fragmented data—small or big, clean or dirty, complete or incomplete—into complete, trustworthy assets. Our approach offers:

  • Development agility: Tools that make it easy for business and IT to prototype, operationalize, and reuse quickly.
  • Enterprise scalability: Deployable with flexibility for departments, enterprises, or Integration Competency Centers.
  • Operational confidence: Provides visibility and insight into your business-critical processes.

Built on the Informatica Platform and our Integration Competency Model, Informatica data integration projects are five times faster and 50 percent more productive than hand-coded initiatives.

Our data integration transforms the value of your data—arguably now your most critical asset—faster, more effectively, in more situations, and for more needs, than any other solution.

1 Comparative costs and uses for data integration platforms, Bloor Research, March 2014.

That’s how much faster a data warehousing project goes with Informatica compared to hand coding, according to analysis conducted by Bloor Research.