Successful organizations use data to make big decisions. But (hopefully) you won't see a team leader looking at a spreadsheet with 10,000 random entries to decide where to invest. You'll see him or her looking at a chart with data transformed into information. How do you leverage data to come up with the type of information that empowers leaders to make decisions?
Data integration is the first and perhaps most important step in this process. The scale and reach of data integration within your business will depend on how willing you are to automate processes and unify teams.
There are lots of technicalities in the process of integrating data as well as complexity in the strategy behind it, but here you'll find an overview of the main factors of data integration.
What Is Data Integration?
Data integration is the process of combining data from different sources to transform it into information. Data integration shouldn’t be seen just as a technical process, but also as a business strategy.
There are two aspects of this concept to consider.
First, the fact that data and information are not the same. Call it raw data, big data, or simply data. Without the right process, data are just random elements on a massive scale. Once the data is processed, structured, and presented in the right context, we can talk about information.
The second aspect to consider is that beyond the technicalities required to combine two sources, there must be a strategy in place before integrating data.
Why Is Data Integration Important?
Gartner estimates that through 2020, integration will consume 50% of the time and cost of building a digital platform.
If data integration is so difficult and requires such an enormous amount of resources, why are businesses taking the time to invest in this?
The treasure at the end of the rainbow is the ability to make data-driven decisions.
There was a time when data was only interpretable by computers. In 1970, Edgar Cobb, an IBM scientist, invented something called 'relational database' to make data readily accessible to business users. From that point on, companies have been trying to refine the way they process and integrate databases.
According to a survey, highly data-driven organizations are three times more likely to report significant improvements in decision-making compared to those who rely less on data.
When Is Data Integration Necessary?
Your data is not available where it should be.
Your data is not up-to-date.
You have duplicate data.
You have duplicate data.
You have conflicting data between systems.
Your data is not in the right format.
Challenges of Data Integration
Since there are so many different types of data integration methods, the technical challenges your IT team will come across are unique to each scenario. However, most problems your team might face are due to the combination of external and internal sources, and the use of cutting-edge or legacy systems.
But the real bottleneck of data integration is the lack of a business strategy. According to a survey conducted by PWC, 61% of executives interviewed agreed that their companies could rely on data analysis more and intuition less. The same survey revealed that only 39% of those companies were highly data-driven.
That gap happens because of the difficulties to define and carry out a strategic course of action.
Most of these teams choose to follow a model of data integration. There are many of them, but perhaps the most common one is ETL, a model that follows 3 steps: extract, transform and load data. Within that process, there are 3 agents involved:
Source systems (to extract data)
Data integration (to transform data)
Target database (to load data)
Among the Source Applications, you can have external applications, data services, enterprise applications, unstructured files and/or cloud applications.
Imagine that every cloud app has a locked room with data. The API is a copy of the key to open that door. You can deliver that copy of the key to an iPaaS or to another application for them to access that data and create software integration.
From a Business Strategy Perspective
Regardless of the size of your business, if you've determined you need data integration, these factors will help you come up with a strategic plan for it:
Goals: You should have well-defined goals for data integration and these goals should be part of a wider business objective. For example, having a complete view of your customers could be a business goal. To achieve it, your integration plan should set a goal to integrate the customer data in your service, sales and marketing tools. Defining the goals will also give your IT team clues on which type of data should be integrated and which method to use.
People: If you need to build in-house data integration software, you'll surely need an IT team. But next to those employees, who else do you need onboard? While one of the advantages of integration is expanding the amount of people with access to data, probably not everyone needs to actually handle that data. A lot of employees have access to data they don't need to perform their work. That's why limiting access to data (and not to information) is as important as instructing the people working with data on how to do it properly.
Data Management and Security: Security and data are inseparable. And when integration implies the 'movement' of personal data, especially in the era of GDPR (General Data Protection Regulation), it's important to identify all the systems where you store data about a person or company.
Type of Integration: when it comes to integration, enterprises and small and medium-sized businesses (SMBs) face different challenges, but all of them will have to choose between a variety of integration methods. Though it might seem like the decision depends entirely on the IT team, the right method should already be considered during the planning stage. Using third-party integration software, consolidating data, or building in-house integrations are very different when it comes to budget and resources.
The two first considerations to choose the right software are the size of your company and types of databases.
Typically, enterprises have their own data centers and applications hosted on-premises. These may be using on-premises servers to integrate or third-party service providers focused on enterprise solutions.
On the other hand, SMBs usually choose cloud-based applications and store their data inside these apps. To integrate, they go for in-app integrations or third-party services (iPaaS).
Enterprise Integration Platform
Big company, enormous database. If an enterprise is working with their own data center, they'll probably need an ad-hoc integration solution built by their IT team.
When they are using cloud-based applications or a combination of cloud-resident and on-premises endpoints, they can use an Enterprise Integration Platform as a Service. Using this type of service makes it easier for them to swap out enterprise applications and select new vendors whenever it's necessary.
This type of integration service is usually very specialized and customized. The providers can manage different types of data and typically support at least some of the following:
Cloud service integration
Mobile application integration
These services are backed up with exclusive technical support from the provider, disaster recovery and high standards of security.
More and more businesses are choosing cloud-based business applications and SaaS (Software and a Service) to run their business processes. A few years ago, this type of software was designed for SMBs, and though they are still the main users of iPaaS, the flexibility of some providers opened a window for enterprises to start using their services.
These iPaaS services usually act as a conduit for communication between multiple cloud-based systems.
Unlike other services, they usually work in the background automating flows of data between applications rather than storing data from different sources into a single database.
Most of them are specialized in solving specific integration problems rather than covering all possible data combinations. Top vendors for one-way or trigger-based integration are Zapier,Tray.io and Automate.io, while PieSync offers two-way synchronization for customer data.
Data Integration Is for Everyone
Business decisions are not easy. There are circumstances where intuition comes in handy, but in an ideal scenario, you'll have the right percentage of intuition and data to make the best decisions.
Data integration empowers organizations to make data-driven decisions. There are two key ingredients for a successful data integration: the first one is establishing a strategic plan and the second one is choosing the right integration solution.
Regardless of the size of your business or the resources behind you, processing and managing data the right way enriches the view of your business and customers, as well as enabling you to make the best decisions at the right time.
Originally published Jun 16, 2020 7:53:00 AM, updated June 16 2020