What is data integration?

Data integration describes the process of consolidating data from different sources for increased availability and easier processing.

Data integration automatically brings data from countless different locations together to create a unified view that businesses can then refine into meaningful insights and actionable comprehension. If managed correctly, data integration can help reduce costs, improve data quality, and promote IT innovation without upending existing data structures.

Graphic outlining the strategies for data integration.

Occasionally, businesses confuse data integration with the concepts of application integration and extract, transform, and load (ETL). But while these approaches may share some similarities, there are important distinctions to be aware of.

Application integration is the process of synchronizing multiple applications by allowing data to move freely between them. For example, multiple systems that share customer records may rely on application integration to ensure that there are no discrepancies between the records, and that changes in one system are immediately reflected in the other.

ETL is a larger umbrella term that encompasses both application integration and data integration. ETL refers to the process of collecting data from a source system, transforming it into another format, and depositing it at a new destination.

At its heart, data integration is about data transparency and availability. Rather than siloing data into individual systems and tools, organizations can access all relevant data through an entire company network, sharing information seamlessly across systems and departments.

Data integration also goes further, converting the data into a usable format that users at all levels can more easily digest and put to work.

This provides several advantages for businesses that correctly apply data integration solutions:

Increased ROI

Many business systems tend to operate in isolation, failing to integrate effectively to share data between them. Unfortunately, when data becomes siloed, other departments and systems have difficulty accessing it, reducing the effectiveness of every system on the network. Data integration eliminates those barriers, allowing data to flow freely and improving the return on investment (ROI) of individual systems.

Higher data quality

When data integration relies on manually locating, converting, and moving data, data quality suffers. Automated data integration preserves data quality as it moves between systems, by applying automated data transformation governed by predefined business rules.

Better decision making

With reliable data always at hand, organizations have a solid foundation for making informed, fact-based decisions. Confident in the knowledge that their data is accurate and up-to-date, teams across the organization can improve their decision-making capabilities.

Enhanced operational efficiency

Manually collecting, transforming, and combining data is not only imprecise; it is also extremely time consuming. Data integration takes this responsibility out of employee hands, freeing them up to concentrate on more strategic concerns and provide better value to the company.

Improved business relationships

Without a completely holistic view of the data, account executives lack a necessary resource for interacting with customers and partners. Data integration empowers these professionals with the information they need to build, secure, and improve vital business relationships.

Here we address some of the possible hurdles to successful data integration and how to recognize them:

There are too many different sources

Many modern businesses rely on a range of systems, applications, and tools to manage accounts and guide decisions. Billing, marketing, lead generation, and customer service are only a few, and each system creates data. In many cases, these different systems are being maintained by different teams without any unified processes for managing that data. When data is not standardized, it runs the risk of duplication, improper formatting, and being overlooked.

The data is not available where it’s needed

Information silos are a major threat to data transparency. As different departments gather data and store it in their own systems, other departments may be looking for insights relevant to that information with no way of knowing that the data they require has already been collected. Data must be easily available to any authorized department that needs it, regardless of where it originates.

There is too much data to work with

Many companies take a more-is-better approach to data collection. But too much data may not necessarily be a good thing, potentially making the valuable hidden gems of data more difficult to identify and extract. Without proper data management, collecting data from multiple channels can create data clutter, burying the vital data that could otherwise be turned into actionable business insights.

The software is not sufficient for the organization’s needs

Unfortunately, not all data integration software is the right fit for every use case. And even with the right software, some companies create problems for themselves by failing to use it correctly. Understanding data-integration solutions and how best to apply them can help ensure that the data is where it needs to be and in the right format.

Because data availability and transparency are so important, it’s no surprise that there are several distinct kinds of data integration tools available. Some of the most widely used types of data integration include the following:

  • On-premises data integration
  • Cloud-based data integration
  • Open-source data integration
  • Proprietary data integration

Although each business will have its own specific data integration needs, top data integration tools share certain similarities in their functionality. When choosing a data integration solution, consider the following:

How many data sources are supported?

Most modern organizations rely on a range of different systems to facilitate their business processes. Any effective data integration solution must be capable of supporting every data source on the business network, otherwise the organization risks developing data silos.

Is the solution scalable?

Businesses are not static; they grow and change to meet evolving needs, objectives, and markets. The right data integration solution must be likewise dynamic, capable of scaling along with the business it supports.

What security/compliance protections are in place?

There is a lot at stake whenever an organization handles sensitive data. Before committing to any data integration solution, it’s vital to take an in-depth look at how it addresses security and compliance. Otherwise, it may be exposing the business and its customers to potential problems down the road.

Is the data available in real time?

Having access to data from multiple sources is only beneficial when that data is fully up to date. The data integration tool must be capable of delivering real-time data solutions, so that the decision makers can take action with confidence.

How does the solution address data transformation?

A key aspect of data integration is ensuring that any data collected is presented in the correct format. Simply gathering and moving data is not enough; that data must be standardized so that all authorized users can easily interpret and apply it.

To remain competitive in an increasingly information-centric world, businesses in all industries depend on available, transparent, actionable data. Unfortunately, eliminating data silos and making essential information accessible across systems and departments in real time can be a challenging task. Data integration tools can help optimize the process, but only if they have the right functionality. ServiceNow, the leader in IT management solutions, has the answer: Integration Hub.

ServiceNow Integration Hub is the bridge connecting and empowering ServiceNow products to accelerate data availability and workflow connectivity across any system. Scalable, secure, simple to use, and easy to customize, Integration Hub employs out-of-the-box ‘spokes’ for unmatched time to value without the need for specialized integration resources. The end results? Lower integration costs, improved IT productivity, and fewer barriers standing in the way of developers, IT generalists, and no-code builders alike.

See Integration Hub in action; watch the demo, and get ready to experience true data transparency, with ServiceNow.

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