What is Data Integration?

Data integration aims to combine data from different systems to be used in the same way across your organization. The merged data is usually stored “clean” and enriched in a single central location. By correctly integrating data from different sources, the data you work with becomes more reliable, and it is possible for different departments to use each other's data. In this way, you can find the opportunity to work with more reliable data in management and business processes and plan the future of the company by obtaining accurate results with your analyzes. So what exactly is data integration? Why is it important? How is it applied? Let's take a look at what you need to know about data integration together.

What is Data Integration?

Data integration is a complex process by which data from different data sources and IT systems of a company is combined, enhanced, enriched and cleaned. However, it leaves clear data that can be used by various departments in your organization. As a result of integration, each of the data is displayed clearly, so that a good idea of all available data can be obtained. The “raw” data can thus be easily analyzed and converted into “smart” data that can be used commercially by the company.

Data integration is very useful, for example, when two companies need to merge their databases into one new database. Because it also plays an important role in data migration when creating and managing data warehouses and data lakes or when implementing master data management. By integrating data departments, each other's data can also be utilised. For example, your commercial department may need access to financial data on customers before new quotations are made or orders are delivered. The data from the finance package should then be combined with the data from your CRM system. However, data integration does not play a role in ERP software because the data is always integrated and clear.

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Who is Data Integration Important to?

Data integration is crucial for almost any industry, as it provides always access to existing customer data and less margin of error. But there are also sectors that benefit more from this practice.

• Marketing: Cost loss is avoided as up-to-date data is always needed.
• Sales: Insight into available credit information is gained so that delivery terms can be better negotiated.
• Finance: For a faster credit evaluation process, the system always has access to up-to-date credit information and always has accurate billing information.
• Customers: There is always the right address, the right delivery possibility.

Why Data Integration?

Business processes benefit from accurate and complete data. Not all data necessary for a particular business process is generated in the system that supports this process. Because the system requires connections between different databases, and it is necessary to determine which data is correct and therefore the leader. The same type of data is also found in databases, which can still have different contents. This usually happens with personal and contact information. Data integration focuses on the connection between data sources and the uncertainty of data. Only in this way can you get the most out of data integration.

What Does Data Integration Do?

Many systems lead to a variety of data entered by too many different employees. This piecemeal manual work greatly increases the likelihood of errors in the use of customer data. Data integration enables data to be held and exchanged in an explicit manner, often in a single central location. In addition, the ability to integrate different types of data further increases efficiency in companies.

By integrating customer data with financial data, employees no longer need to manually check the credit worthiness of customers, and also all relevant information about this client can be instantly accessed by anyone within the organization. In this way, the terms of delivery of sales with accurate information are better negotiated and “safer” agreements are established with customers. This ultimately leads to less harm as everyone looks at the same up-to-date financial information.

Data integration ensures that the requested data is complete and accurate, as it enables the collection of data from various sources within the company. Thanks to integration, they have to consult a database or perform complex analysis, even if they have different characteristics (e.g. structured data, unstructured data, flow data, etc.).

Data can be collected manually, for example by copying it from a database and pasting it into a customer file. This method may be useful at one time, but it is not sufficient when data needs to be consolidated on a large scale. Many major software manufacturers therefore offer platforms for data integration. For example, Informatica Intelligent Data Platform, a service of Komtas, includes many services such as data quality, master data management, API & APP integration as well as data integration. Thus, you can use the data in your organisation as you wish, confident of its security.

What are the Uses of Data Integration?

Since the advent of the Internet and applications in the cloud, not only is more data added, but it is also spread more and more across different systems. Most companies may opt for data integration with one of the following objectives in mind:

• Creating data lakes: Some companies want to centralise their data in a raw format. The data is stored in these data lakes before being structured or adapted to other data types.
• Master data management and data consistency: Data integration is often used to connect different business entities and domains. This results in high-quality master data.
• Data migration: When moving from one business application to another, a data migration must occur. Data integration is also done here. Data follows the ETL principle when transferring to the new system. Companies, for example, ensure that the data in the old system is compatible with the new system and that the old ones are integrated with the data in this new system.
• Data replication: Copies of the database are made at certain times in companies. Companies prefer this to make an update or backup, for example. Thus, data security is ensured. In this way, data can be retrieved if something goes wrong in the update or backup. However, making such a copy is not always an easy copying task. Most often, the database system for copying is formatted slightly differently or uses a different SQL variable. In such cases, data integration must occur.
• Centralization of different source data: Companies that want to use data from very different sources often use a data warehouse or data service. This allows users to use it in different applications without having to manually transfer the same data.
• Data preparation for BI systems: For their analysis, BI systems need data from various sources. However, if the format is uniform and not compatible with the BI system, the analyzes will not be correct. Data services are often used for data integration.

What Are the Benefits of Data Integration?

All companies want access to all data at the same time, as it can help them to carry out their business processes in the best possible way. One of the best practices for this is data integration. Business activities can better account for a customer's creditworthiness or overdue payments by integrating customer data with financial data. Thanks to integration, you become more aware of financial risks, and you can find solutions to risks with terms of delivery, additional contracts. With marketing activities, you have better and more reliable contact information so that marketing campaigns can be more successful. You reach customers with the right data, which improves communication. In addition, your finance department can act faster on invoicing and collections.

Komtaş offers a variety of services for all your digitalization processes, including data integration. From your customer relationships to your marketing department, you can leverage data integration, empower your employees to work with more accurate data, and increase profits with the right planning.

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