A beginner’s guide to data integration

Today, most businesses depend deeply on data. Data drives everything from customer support to business strategy. Businesses collect unprecedented data loads from a growing number of sources. 

Legacy systems, sensors, log files, mobile devices - all of these generate data that give companies business intelligence and insight. They can become a strong competitive advantage. That’s the good news. 

The bad news is that someone needs to make sense of this overwhelming amount of data. This is where data integration solutions come into play. But what is data integration and how is it working? 

This quick data integration guide will get you acquainted with the basics of data integration.  

What is data integration?

Simply put, data integration is the “art” of combining information from disparate sources into something useful. Data integration combines data from different sources and provides users with a unified view. 

Take the example of a website where users can search for a variety of information about cities (traffic statistics, weather, hotels, demographics, etc.). The information may come from different sources/databases (traffic statistics, weather statistics, etc). This data has to be consolidated in order to be used in one single application.

Anybody who’s tried to fetch information from multiple systems for reporting purposes understands the importance – and the complexity - of data integration. It doesn't get easier with large volumes of data, in the era of big data. 

When a business grows, new locations, new revenue streams and changing priorities will increase the amount and affect the form of its data. It will also challenge data quality, making data integration more and more important. It will also make it more and more complex.

How is data integration best handled?

The need for consolidating data has existed for a long time – much before modern data integration tools were developed. IT executives have been fighting data siloes ever since IT systems have started collecting data in different systems.

The solution has always been a data integration strategy. However, in the beginning, integrating multiple data sources typically meant a lot of ad-hoc hand coding between different data sets. This resulted in an expensive solution, with difficult maintenance. 

Often, these integrations were developed from scratch in-house or by a partner. They were poorly documented. And, if the developer who developed them left the company, updating or modifying the integration was a nightmare. A general advice: if you can, avoid hand coded, homemade solutions.

Today, modern data integration tools have been developed to handle the data collecting, data transformation, and data provisioning functions. They are created to do this in an efficient, transparent and highly adaptable manner. 

Data integration systems such as RapidiOnline come out-of-the-box with a number of pre-configured integration points between pre-defined systems. This could be for example Salesforce’s CRM and Microsoft Dynamics’ ERP. 

This is ideal because data driven companies that wish to integrate two (or more) systems always have common ways of working and therefore similar requirements.

How can companies benefit from data integration?

The benefits of 2 systems (for example an ERP and a CRM) taken separately are undeniable. They can by themselves make a huge difference in a company’s operations. 

Combined together however, these two systems can potentially help companies take an exponential leap. Data integration benefits are numerous.

Let’s take the ERP-CRM integration example. Companies typically benefit from a CRM-ERP integration by:

• Reducing manual data entry (prone to errors), which frees their resources to focus on value-adding tasks.
• Optimizing and automating business processes, for example their sales process, by giving real-time, instant access to business-critical data.
• Providing with a true 360-degree view of customers. The better insight they get into their customer base, the better they will be able to build lasting relationships with customers. This will also allow them to determine where there is potential for future growth.
• Securing high system ROI , via sky high user adoption. Securing well integrated systems gives users the ability to always find information in their systems. With integrated systems, they will never have to go back to alternative ways to find data to perform their daily tasks.

Why is data integration challenging?

Many of the companies that embark on a data integration project find themselves faced with serious challenges. Typically, it is because the complexity of a data integration project typically grows with:

• The number of systems used : Data volumes tend to increase with the number of data sources and data warehouses you have. Some enterprises have hundreds of systems. Some run on multiple platforms (for instance a combination of on-premise, Cloud and private hosting), in various versions and different geographical locations.
  When data resides in so many silos it adds a whole new complexity and security dimension to a data integration project.
  
  
• The customizations made to the systems : Many systems and applications come out-of-the-box with role-tailored functionality. However, most implementation projects include extra customization and development efforts to support enterprise-, division- or user-specific working processes and habits.
  This can result in hundreds of custom modules or features. This can easily become a maintenance and upgrade nightmare. It is also a challenge when you have to integrate the different systems.
  
  
• The lack of a consolidated approach to data integration : In some cases, data integration is approached as a multitude of point-to-point custom integration scripts without a common direction. In that case, the data integration project is doomed to fail to deliver the desired business critical single view of data.
  Data must be synchronized in an automated and reliable manner across all platforms for a company to have one version of the truth. Errors caused by inconsistent data and manual data entry can prove very costly for companies and disrupt business activities.

Top criteria when selecting a data integration solution

The above-described challenges can easily be solved if you choose the right data integration solution. Making the right choice is vital. This will allow you to bring all these elements together and deliver the desired one view on your data.

When evaluating a solution, you need to make sure that:

• The solution is proven, stable and reliable.
• The solution will be easy and quick to build.
• The solution is easy to understand on a technical level, and intuitive and simple to use for your business users.
• The solution is able to connect to your various data sources and be able to consume your various data types.
• Mistakes and errors are inevitable. The solution needs to be able to monitor data integration transfers and proactively alert your administrators when an error occurs.
• The solution can scale with your business and the addition of new data sources.

Learn more about data integration

Would you like to learn how easily you can integrate your CRM, ERP and any other systems or end-points? Download our data integration handbook and get all the answers.