What problems can data integration solve?

By October 30, 2019 FME
What problems can data integration solve?

Data integration allows you to combine data stored in different formats, coming from multiple sources and collect them in one place. Ultimately and perhaps the most important goal of data integration is to generate valuable and useful information that is beneficial to many companies in troubleshooting and decision making.

But collecting data in one particular location is not worth much. It is necessary to make them constantly available to those who need to use them so that they can use their full potential. Thanks to data integration it is possible to use information that would otherwise be hidden. This may help to improve communication between individual departments in the company, but also provide better customer service, improve our operations or streamline business decision-making.

We present a few problems that can be solved by integrating data in your company. Please, keep in mind that these are only examples, and the difficulties solved by data integration are much more:

This technology is becoming more and more popular. It allows you to work with large data sets. However, managing huge amounts of diverse data is associated with difficulties and problems. Integration of all data dispersed and hidden in the company will help to understand them. No matter if the data is generated internally or collected from external sources.
They refer to a variety of data warehouse that store data in specific locations. In this technology, the problem is caused by older and sometimes inoperable systems. Linking data will help to retrieve data from older systems, which are already in daily use, and to integrate them into new, evolving systems.
By creating one consistent data source, combining data from multiple places, all users in your company will be able to access data and information at all times, without the need for queries. As a result, you will gain wider access to your data and reduce the risk of erroneous replication.
A common problem with using various systems to collect data or having many people collect data is ontology issues. This means having multiple types of data that describe the same thing but are organized differently. An example of this may be the way that dates are stored (“DD/MM/YYYY”, “MM/DD/YYYY”, “Month Day, Year”, etc.). By removing variations and creating a structured data warehouse, you will be able to find your data more easily and analyze patterns.

The solutions to the problems presented above save both time and money. But data integration also allows you to manage data and individual parts of your management processes. Below we present several methods of data management, where integration is truly useful.

This term describes the process of applying technology to analyze business data to make better decisions. Before making the right business decisions, it is essential that data is organized, cleaned and prepared for analysis.
It is extremely important that the decision-makers understand all the necessary information to allow for the proper development of the organization. When data is not structured or difficult to access, it is not possible to make the right decisions and determine what steps to take.
By combining and managing customer information in a structured way, companies are able to provide better customer service. Integrating customer data allows you to create a more efficient management system that allows employees to easily access and search for customer data when needed.
It allows users to access, manipulate, and query data without having to access the actual storage location. In the case of data virtualization, the key to proper data maintenance is a properly created back office structure. This enables the most advantageous functioning of front-end applications and self-service solutions.
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If you are struggling with a growing number of disordered data every day, you could probably use one of the concepts mentioned above.

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