by CData Software | July 15, 2022 | Last Updated: December 05, 2023

App Integration vs. Data Integration: How to Choose the Right Tools

Integration is an integral part of ensuring your technology stack works for you. Coordinated data gives everyone across your organization to do their jobs more effectively ­– from content writers embedding tweets into blog posts to data teams reconciling data warehouses after a company merger.

Understanding each type of integration is essential to picking the right tool for the job. To introduce the basics:

  • Application integration, or app integration, is an approach that allows data from one application to work with another using fixed data schemas.
  • Data integration is an approach that compiles and transforms disparate data from multiple sources in a single location.

In this article, we’ll delve deeper to properly compare these two concepts. We’ll also unpack how to view each approach to determine where they’ll perform best in your organization’s data ecosystem.

App integration vs. data integration explained

Today’s growing digital landscape means that data gets siloed and fragmented into pockets across organizations. Additionally, organizations must address the explosion of unstructured data that doesn’t fit seamlessly into systems built for structured data. Modern integration software solutions solve these challenges by allowing organizations to unite data across the business.

From a high level, choosing the right integration strategy involves a series of questions about how you want to treat your data, and the outcome you’re expecting. These questions include:

  • Which data do you want to move?
  • When do you want to move that data?
  • How much data do you want to move?
  • What do you want to accomplish with that data?

Application integration can be viewed in some ways as data taking a taxi, while data integration is a bit like data taking an airplane. Each has its advantages and disadvantages.

What is application integration?

Application integration allows data from one application to directly enhance and expand functions for another application. Organizations usually look to application integration to improve the functionality of business processes that include more than one data source or system. The interoperability of those systems allows businesses to improve operations, streamline reporting, and innovate faster using technology that works together.

Also known as application-to-application (A2A) integration, it acts as a taxi in that it:

  • Transports data on-demand
  • Only takes smaller loads of data at a time
  • Takes data to a specific location

To accomplish this integration, teams can install a data connector between two applications. As the number of point-to-point connections grows, organizations might use a connectivity platform to track and manage each connection.

Some business processes, however, require data from multiple data sources to be compiled in one location before it is extracted for analysis. That’s where data integration steps in.

Benefits of app integration

  • Efficiency and productivity: A2A integration streamlines business processes, enabling faster operations with reduced errors through automated data exchange between applications.
  • Real-time data access and improved decision-making: App integration facilitates real-time data sharing across different applications, leading to more informed and timely decision-making.
  • Scalability and flexibility: A2A integration offers a scalable and flexible solution that easily adapts to changing business needs and technological advancements

Examples of app integration

  1. CRM integration: Integrating Customer Relationship Management (CRM) systems allow organizations to collate customer and account data from various touchpoints. By connecting marketing automation, sales, support, and financial tools, business gain a 360-degree view of customer health, engagement, and satisfaction.
  2. E-commerce platform integration: Organizations can connect e-commerce platforms with inventory management, order processing, and payment systems to optimize end-to-end e-commerce processes. This ensures real-time updates on product availability, streamlined order fulfillment, and accurate financial transactions.
  3. HRS integration: Human Resources Systems (HRS) integration optimizes processes like recruitment, employee onboarding, payroll, and performance management. Connecting diverse HR data reduces manual data entry, improves workforce management, and optimizes decision-making.
  4. ERP integration: Integrating Enterprise Resource Management (ERP) platforms gives organizations the ability to connect various departments, including finance, supply chain, manufacturing, and human resources, to streamline business operations.

What is data integration?

Data integration is the process of pulling data from multiple systems and sources and uniting the information to enable broad, flexible use cases. Both unstructured and structured data can be replicated under this model and fed into a single repository to later be extracted, transformed, and leveraged for wider business needs. Organizations often use this method to integrate massive data sets across multiple databases and applications to ensure all data is accessible and reliable.

The data integration approach acts more as an airplane, as it can:

  • Only transports a handful of times per day
  • Can take large groups of data
  • Unite many sources and destinations through fixed hub locations

Data integration requires more infrastructure and development efforts to configure and run ELT (extract, load, transform) processes, as well as additional upkeep costs and administrative work. However, depending on your organization’s data needs, this method provides a robust and dependable solution to data management.

Choose the data you move

Modern data integration solutions like CData Sync offer strategic data replication via Change Data Capture (CDC) to send updates only for data that has changed. This allows you to only replicate and move the data you need instead of spending time and money moving mass volumes of data unnecessarily.

This travel metaphor helps differentiate the significant differences between application integration and data integration. As you’re considering your goals, remain mindful of the above traits and how they fit into your integration use cases.

Benefits of data integration

  • Unified data views: Data integration consolidates information from disparate sources into a unified view, providing a comprehensive and consistent understanding of the data.
  • Improved decision-making: Access to holistic datasets allows decisions makers to identify patterns, trends, and insights that may have been overlooked when data is fragmented across disparate systems.
  • Increased operational efficiency: Data integration pipelines automate the movement and transformation of data. They reduce manual effort, increase data accuracy, lower the likelihood of errors, and streamline operational processes.

Examples of data integration

  1. Business intelligence and reporting: Data integration is commonly used to consolidate information from various data sources into a repository in order to leverage for reporting and analysis. Bringing unified data into reporting tools like Power BI, Looker, and Tableau allows business leaders to make well-informed decisions.
  2. Customer insights: Bringing account information from disparate systems like CRMs, customer support, marketing automation, and sales platforms into one location allows businesses to follow customers throughout their entire lifecycle and make personalized decisions based on multiple touchpoints.
  3. Supply chain management: By connecting data from suppliers, manufacturers, logistics, and inventory systems, supply chain organizations can become more efficient, optimize inventory levels, reduce lead and delivery times, and more.
  4. Healthcare modernization: Healthcare organizations can leverage data integration to combine patient records from diverse sources, including electronic health records (EHRs), laboratory systems, and billing platforms. Unifying this data gives these organizations a comprehensive and accurate view of patient medical history, allowing them to deliver better healthcare outcomes.

Choosing the right integration method for your business

Selecting an application integration or data integration is a case-by-case decision. Your choice should be based on which data bottlenecks you’d experience for each set of tasks performed in your organization.

Each integration type specializes differently to help you manage:

  • Network and computing bandwidth
  • Infrastructure upkeep costs
  • Data age
  • Data compatibility

Let’s explore some use cases for each form of integration to help you identify what fits your needs.

When should I consider application integration?

Application integration, or A2A integration, introduces real-time information access to keep data actionable at low upkeep costs. However, the connections are often ad hoc, meaning your IT team will have to configure the direct connection between each of your applications. Data connectivity software providers like CData make application integration faster and easier by providing a vast library of standards-based connectors that enable users to set up integrations in just minutes without the need for code.

Real-time application integration solutions like those from CData show the most up-to-date data from one source directly within another, meaning your data team has access to the latest, most accurate information to fuel workflows like sales forecasting and financial reporting.

When should I consider data integration?

Data integration prepares large sets of diverse data to support large transactions, operational workflows, and other tasks. The integrations can be scheduled to automatically deliver mass volumes of data to a single repository in batches, which may result in slightly delayed data access when compared with real-time delivery.

Data integration pipelines are often expensive and time-intensive to build and maintain, so organizations often lean on data integration specialists to produce out-of-the-box solutions that allow data teams to easily create ETL processes and offload integration maintenance.

Building your integration mix

In short, application integrations connect live data between sources, while data integrations unify data sources within a single repository. Each process has its own set of benefits, whether that’s ease of use and flexibility, or comprehensive data management.

CData specializes in universal data connectivity. Whatever your preferred method of connecting data, we’re here to help. Building or using an application integration solution? Check out our CData Drivers. Ready for a data integration platform? CData Sync is your answer.

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