The free exchange and use of information is an essential element of any business that requires data in order to succeed. Unfortunately, many businesses of all shapes and sizes have problems because they use different systems to carry out various processes.

This strategy in itself makes sense—you want to use the best applications for finances, platform building, and sales—but these programs don’t always come in the same box. However, when you pick and choose applications across a business, it creates roadblocks between departments and works against the easy flow of data. Read on to learn about data integration and how it works to solve this problem.

Defining Data Integration

Data integration is the process of taking data from several sources and combining everything into unified datasets. This has uses both operationally and analytically, and it is often the first step in a wider data management process.

The objective of integration is to create a set of consistent data that is usable for everyone within your organization. Once all the data is integrated, you can use it to gain valuable insights and solve problems in new ways.

There is no limitation to which industries can use and benefit from data integration—if your company has data from disparate sources, integration can help you consolidate and solidify your strategy. When you have information from more sources, the value of your data skyrockets.

How Does Data Integration Work?

With data integration, there are data sources and target systems. Integration pulls data from various sources and routes them into your target system, performing simple cleaning processes along the way to prevent duplicate or redundant data.

For this reason, data integration is typically more complicated than simply directing numbers on a spreadsheet to move to a larger spreadsheet. A program must scour the different datasets to ensure you aren’t left with unnecessary numbers or inaccuracies. Who would have thought combining datasets could be so tricky?

Data Integration Solutions

Now that you have an understanding of data integration, let’s take a deeper look at the problems integration works to solve.

Big Data

Big data is just what it sounds like—vast quantities of data. You’ll hear a lot of people say, “the more data, the better.” While that sentiment certainly has a basis in truth—if you have more data about your customers, you can better tailor your products and advertisements to them—it comes with its share of conundrums.

The two issues that surface regarding big data are data volume and data variety. A robust system takes care of the volume problem, but variety is still an issue—enter integration. Integration helps you organize and decipher vast quantities of data, no matter where that data comes from.


A massive issue with rudimentary integration, or integration without cleaning and consolidation, is that you’re likely to be left with duplicate data. Even simple integration systems can catch exact duplicates, but what happens when different pieces of data describe the same thing in different ways?

For instance, perhaps one source comes from overseas, where dates are listed as DD/MM/YYYY; meanwhile, another source comes from the United States, where dates are written as MM/DD/YYYY. You don’t need both variations, so integration steps in to clean things up. This process makes it easier to recognize patterns and avoid being bogged down with unnecessary information.

Data Silos

Data silos are a thing of the past that we’re still tripping over today. As with many other data solutions, you can see the good intentions of data silos while also feeling frustrated by the problems they cause. Essentially, data silos refer to data sources stored in specific locations.

Say a company has a Toledo branch and a Tucson branch. Each location has its own unique set of data that the larger company doesn’t have easy access to since the data is stored on-site. Integration—especially cloud data integration—can take those unique data sources and bring them together in a way that your entire business can take advantage of.


Why create more work than you need to? The best strategy is to make something once, then deliver it to as many people as need it. One central data source eliminates redundancy and reduces confusion while also promoting collaboration.

Benefits of Data Integration

Now that you’ve seen all the problems data integration solves, let’s consider some of the integration’s benefits.

Reduced Costs

The more processes you can automate, the less your employees will need to work to complete tasks. This opens up their schedules to complete new and different tasks, which means you can continue to pay your employees the same amount while receiving more deliverables. The longer the human workflow, the more you end up paying.


Building on the previous point, this boosts the efficiency and productivity of employees companywide. Where some workers could only focus on basic, busy work tasks, they now can dive into more complex work. This gets your customers the results they’re looking for while providing more fulfilling work for your employees.

Better Data Quality

When you work with clean data, overall quality increases. It’s easy to struggle through data with redundancies and inaccuracies without really realizing what’s happening until a computer signals otherwise. All incoming information is validated with integration, which means you don’t need to worry about creating unnecessary roadblocks for your employees.

Upgraded Decision Making

No good decisions are made based on a lack of information. With integration, you and your employees will have everything needed to make educated choices for your business. This is why integration coupled with data analytics is the ideal team—the easier your data is to parse, the better your insights will be.

Enhanced Customer Experience

No one wants to wait around to get answers. With integrated data, your customers will receive the information they’re looking for without spending a lot of time doing it.

Now that you know what data integration is and how it works, consider adding data integration to your information pipeline. Whether you have multiple data management systems or a single coherent system, the integration will bring all your information together for a prime view of all the information at work in your business.

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