What is Data Integration?

What is Data Integration?

Imagine driving down the road in a car with no mirrors. You can look around you to find the information you need, but you need to take your eyes off the road. You can drive, but you don’t know if it’s safe to change lanes. You’re missing a key piece of data to make a decision. This is what it’s like when your data is not integrated: part of your view is crystal clear but you do have a blindspot the size of a truck.


What is Data Integration?

Data integration is the process used to combine data from disparate sources into meaningful and valuable information.

You might have inventory data in one place, raw material information in a different place, and sales data in a different place. Without bringing the data together how can you be sure you’re making the right decisions? As the number of data sources continues to grow, it is important to have the ability to analyze all the data in order to make informed decisions.

Until recently the technology was not good enough to bring all that data into one place. Or if the data was brought into one place, it was impossible to manipulate it or query it in a way that was useful. Today, the data gods have gifted us with the necessary tools. Companies that fail to adopt and make use of these tools fall behind.

Key warning signs of data bottlenecks

  • multiple, disparate databases are used to track inventory, production, sales and to serve customers and they are not sharing information
  • slow access to relevant reports that are needed to make business decision - i.e. real-time production line efficiency
  • having highly qualified IT resources tied up in building reports needed by decision makers
  • critical business processes are slow - hindered by lack of relevant data

How to do data integration

customized solutions and broad application suites

With customized solutions for data integration, the company can take advantage of many features and functions tailored to its particular IT topology. The organization can create its own data management designs, flows and processes. However, both these solutions come at a hefty price, both in terms of licensing and in terms of IT staffing required to maintain and run the setup.

in-house solution

Using in-house resources and technical skill are usually where most companies start. That is because some decision makers feel the pain of not having the right data on time faster than others. This approach produces a ‘custom’ - creating a solution based on the exact needs of the organization or a part of it. The drawbacks are that the setup is not meant to be easy to maintain or scalable. And usually if the employees that implemented the solution leave the company the solution can no longer be maintained.

modern data integration tools

The use of packaged solutions enables a company to make savings in time and total cost when implementing a data solution. Modern tools use data pipelines to integrate a variety of data sources and bring data into a data warehouse. An added benefit is that these tools are more robust and come with features


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  • data integration
  • data management