Application integration vs data integration: where they differ and how they’re merging

Application integration vs data integration

Data integration and application integration are often incorrectly treated as one and the same.

This can lead to miscommunication between teams, misusing either approach, and neglecting at least one of the approaches altogether.

To help you and your team get on the same page, we’ll break down how the two differ by walking through their definitions as well as examples of how they can work. We’ll then share how—despite their inherent differences—they’re beginning to overlap in interesting ways.

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What is data integration?

Simply put, data integration is the process of collecting data from several data sources, transforming it, and then loading it into a data warehouse (i.e. following an ETL process). From there, your analysts can retrieve the data and use it in the analytics and business intelligence (BI) tools they rely on.

An example of performing data integration
This example involves combining data from marketing platforms to a data warehouse, like Snowflake. From there, your team can use the data in analytics tools to spot trends and uncover additional insights.

The clear benefit of data integration is that it allows your team to gather all the data that’s needed before beginning their analysis. This allows them to arrive at better decisions, both for their function and for the business more broadly. 

A clear con, however, is that historically (and even to this day), organizations have approached data integration with a batch-oriented process. This means that data would move to the data warehouse on a consistent cadence but in a way that was far from real time (e.g. once per day)—preventing analysts from accessing and leveraging more recent data.

Related: A look at data integration’s benefits

What is application integration?

Application integration is the process of keeping your apps in sync when an event or data changes in one of them. This normally involves using their application programming interfaces (APIs) as a means for communicating with each other.

An example of an application integration between Salesforce and Marketo
This application integration example involves adding a new lead in Marketo based off of the new lead created in Salesforce.

Application integration provides your team with various benefits:

  • Your applications are kept up to date, allowing employees to access and use the latest information
  • Human errors (caused by manual data entry) that could create significant issues down the line, such as sending a client an inaccurate invoice, are avoided
  • Employees can save time, as they no longer have to move between apps and engage in extensive data entry

However, like data integration, application integration has often been done using a batch process, which prevents data from getting added in real time. For example, once a new lead gets created in your CRM, your marketing automation tool—among other tools affected—would only add the lead several hours later. As a result, your marketers might lose valuable time in nurturing the lead simply because they’re unaware it exists. 

Related: Examples of application integration

How application integration and data integration are coming together

Today, the two are overlapping in various ways.

  1. Data can move at or near real time. Organizations are now expected to use this approach—over the batch method—for both data and application integration so that employees can access more accurate, up-to-date data in their apps.
  1. Application integration also involves retrieving data from a data warehouse. Since data integration already provides data to your warehouse, application integration can simply involve taking the data that’s in the warehouse and moving it to downstream tools in real time.
  1. Teams are coming together to tackle both approaches. Now that both methods involve moving data from the data warehouse to downstream apps, the business analytics team (responsible for managing data integrations) and the business technology team (responsible for managing application integrations) can work alongside one another to fulfill their respective goals.

In short, the way that application integration and data integration function is nearly identical—the only clear difference being the downstream apps that use the data and the respective teams who access those apps.

Related: How to decide between an iPaaS and an enterprise automation platform

Ready to get started?

You can use Workato, the leader in integration-led automation, to not only implement either integration approach, but to also automate your business processes end-to-end without writing a single line of code. 

To learn more about the platform, and to discover how it can benefit your team, you can schedule a demo with one of our experts.

About the author
Jon Gitlin Content Strategist @ Workato
Jon Gitlin is the Managing Editor of The Connector, where you can get the latest news on Workato and uncover tips, examples, and frameworks for implementing powerful integrations and automations. In his free time, he loves to run outside, watch soccer ( matches, and explore local restaurants.