Businesses today are drowning in data, and more driven than ever to make the most of it. When analyzed properly, that data has the power to boost efficiency and dramatically improve an organization’s operations, because it allows teams to base decisions on actual information about how their company works. But raw data isn’t much good to anyone — to be useful, it needs to be consistent, organized, and collected together into a single, unified system. That’s what data integration is all about.
Keep reading, and we’ll explain what data integration is, why companies do it, common struggles to watch out for, and a few of the most common ways to integrate data.
What is data integration?
Data integration is the process of creating a unified system where data can be consulted, by importing business information from disparate sources. These sources can include software applications, cloud servers, and on-premise servers. Businesses typically integrate their data to make it easier to analyze without hopping from source to source.
While there are many different techniques and methods, the goal is ultimately to produce business intelligence; specific, actionable insights about the current state of a business’s operations. Business analytics may also be generated from data. These are similar to business intelligence but have a predictive, rather than descriptive, function.
In general, data integration is accomplished by consolidating the distributed data into one dataset, usually on a single master server, through which users can access, process, and analyze it more easily. While integration is a fairly simple idea, it can be complex and challenging to implement. If you’re involved with a data integration project, you’ll want to know exactly what you’re getting into.
Benefits of data integration
Data integration stems from a need to understand data more deeply, to extract meaning from it, and use that knowledge to make smarter decisions that support the health of the company. That said, this need can come from a variety of use cases.
For example, data integration might allow a company to get to know its customers better by bringing together website activity, purchasing history, and Customer Relationship Management (CRM) system data in one place. In this example, data integration can allow the company to create holistic customer profiles that combine data from multiple sources. These profiles can then empower customer-facing teams and their initiatives.
No matter the use case, data integration has a number of benefits:
- Making it easier for employees across the organization to work with data, no matter the source.
- Avoid wasting time and money on inefficient methods for accessing and analyzing data.
- Cleaning and adjusting the dataset for consistency, making it more accurate and valuable.
Challenges of data integration
Despite its many advantages, data integration can be a very complex process that does come with inherent challenges. Most often, organizations have a general understanding of the goal of their integration process, and the data that it will need to include. The difficult part tends to be around making sure that understanding is nuanced enough, and their plan can be realistically executed within their desired timeframe using the resources they have available.
Some areas where data integration may become challenging include;
- Integrating a wide range of data types, such as information from older legacy systems, and newer ones like sensors and smart devices
- Understanding in detail what will be required to integrate the data. For example, will the company need to contract any specialists like data scientists or engineers, and what will it take to set them up for success?
- Maintenance of the new system. This isn’t a one-and-done job. The company will need to ensure they can continuously update the system with new information so it remains current
Data integration techniques
There are many ways to integrate data, and the best choice for any organization is highly dependent on its individual needs. While there are a host of techniques, disciplines, and methodologies for data integration, here are a few general approaches towards integrating and storing data.
Common storage integration
Also known as data warehousing, common storage integration copies data from its original sources into a new, unified storage system known as a data warehouse. From there it can be analyzed and viewed as a cohesive data set. This is one of the most common methods for data integration.
Uniform access integration
This method creates a unified dashboard through which the data can be analyzed, without actually removing it from its original location. With this style of integration, the new system acts as a portal through which data from disparate sources can be viewed in a clear, organized way.
Application-based integration collects data from various software applications such as messages, tasks, or transaction history, and makes it more accessible. Since these applications may not all speak the same language, an application-based integration tool will need to translate the data from each of them to make it cross-compatible.
Data integration with Unito
When data is spread out over multiple tools, just getting into one place can be a challenge. Sure, you can get a purpose-built data integration tool, but is it really all that efficient when you need to export spreadsheets and tasks from all your tools before importing them into another platform?
With Unito, you can turn disparate data into a cohesive whole. With some of the deepest integrations on the market for the world’s leading work management tools, Unito is the quick, efficient solution for your data integration needs. With just a few clicks, you can set up flows between your tools and break crucial data out of tool silos. Better yet, all your information is automatically updated, no matter which side it’s changed on. No need to export your spreadsheets every week. Pool all your data in one place, wherever that is, and give everyone in your organization the ability to make more informed decisions.
Want to see how it works? Sign up for a free Unito trial today and try it out for 14 days, no credit card required.
Integrate and dominate
Getting the most out of data is essential for companies to compete in today’s business world. That means more people need to become familiar with complicated processes like data integration.
With more and more of our interactions happening online, nearly every stage of a business’s operations generates data — and all of it contains clues as to how those processes can be optimized, streamlined, and made more efficient. For companies, data integration is just one step in the process of using that data to reach their goals.