Companies often have a big problem. They have all the necessary data available, but mostly it is spread over many different data sources. There is the data in the CRM system, the data from web traffic and marketing software, data from sales systems or customer applications and many more. For analysis purposes, however, it makes sense to bring all this data together. This can be extensive and time-consuming work for data engineers and also developers.
According to a study from 2020, almost two-thirds of companies are already using data integration. They use it to improve operational efficiency. Almost 60 per cent of companies also use it for faster analyses. For companies, the unification of data sources is very important. With it, they improve their workflow in many areas.
What is data integration anyway?
Figure 1: Especially in e-commerce, companies are confronted with an enormous flood of data. Those who want to remain competitive here need help in collecting and evaluating this data. Pixabay © preis_king (CC0 Public Domain)
Data integration is not just the mere merging of data stored in different systems into one view. During the process of data integration, data is ingested into a target system, cleansed and transformed according to the target system. At the end, meaningful information is available.
Through modern cloud and big data technologies, companies are confronted with an unmanageable flood of information that can only be effectively analysed with the help of professional data integration. In modern companies, competitiveness and decision-making are based on data. For them, data integration is inevitable.
A uniform approach to data integration that is valid for all does not yet exist. However, some elements are repeated again and again, such as the network with the different data sources, a master server with clients. During data integration, the client repeatedly sends requests to the master server. The master server takes the data necessary for the requests from the different data sources, unifies them in such a way that further processing is possible. As a rule, specialists for complex data integration take care of such data integration solutions.
What technology problems does data integration solve?
Big data is a synonym for large and very complex data sets from very different sources. The large volume makes it time-consuming and exhausting to manage big data. With special data integration platforms, these processes can be simplified. The collected information becomes easier to understand.
- Problem data silos
Figure 2: If everyone in a team, in a company can always access the same database, work becomes much more efficient. Pixabay © ronaldcandonga (CC0 Public Domain)
Data silos always arise when a lot of information is stored in different places. This is typical when legacy systems are still in use or related software is in use. Uncommunicative departments in companies can also produce data silos.
With appropriate data integration tools, such data silos can be prevented. The systems help to transfer the data from the older systems into new ones and make it available there. The process of data integration promotes the system across functions, because all teams and systems need to consolidate the data.
- Problem semantic integration
When there are multiple data sources, companies may experience semantic problems and duplicates. For example, two files contain the same information. However, they are in different formats. A data integration application is able to detect variations and remove duplicates. In the end, there is only one data source.
- Accessibility problem
The data integration processes create central data sources in the companies. This means that all stakeholders in a company can always access the same information. This shortens waiting times when someone retrieves data. At the same time, participants make fewer requests because they have all the data available or can find it themselves.
Added value through data integration
Data integration is also very useful when it comes to applications and business processes, keyword Business Intelligence (BI). With the help of BI, companies evaluate critical business data. This helps managers develop strategies and gain insights into the entire operation. But before business intelligence applications can work, they need a unified data foundation, which can only be achieved through data integration. During the data integration process, all data is cleansed, prepared and unified. This ensures that all reports contain accurate, correct and reliable data.
Managers in companies have to make many decisions every day. Good decisions are based on correct and comprehensive information. Data integration can help in decision-making because it helps to ensure that leaders are fully informed.
Data integration also provides companies with important customer information. They get a much better insight into the buying behaviour of their customers. This allows companies not only to improve their customer service, but also to align customer service and sales with customer preferences.
At Cash flow planning , integrations can ensure that information from upstream systems relevant to Cash position is integrated into planning. COMMITLY provides direct integrations, a connection via Zapier and a direct open API for this purpose.