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Data consolidation in the company: Definition and advantages

Yvonne Wicke | 27. October 2023

In the digital age, data consolidation is no longer just an option for companies, but a necessity!

The amount of data from various sources such as different systems, databases and departments has increased significantly due to digitalization. A sensible consolidation and cleansing of this data is often a decisive step in obtaining important information and making well-founded decisions.

Data consolidation refers to the process of combining data from various data sources and data silos into a central system or database. The data volume is usually reduced by removing duplicates and cleansing data records. This can be done either manually or automatically, depending on the existing system and the company's specific requirements.

The advantages of data consolidation are many and varied. It enables better business processes, improves data quality and provides an efficient way to use data for analysis, reporting and decision-making. However, it should be noted that consolidating and cleansing data can be a challenge, especially when it comes to data from different and disparate sources.

The consolidation of data is a continuous process and requires a well thought-out approach.

Data quality plays a central role here. It is important to understand that effective data consolidation is not just about consolidating data from multiple sources, but also about effectively cleansing and updating that data so that it provides the most value to the organization.

In the following, we will take a closer look at the topic of data consolidation, its importance for companies and the associated benefits.

Data consolidation - A definition

Data consolidation is a process in which data from different sources is brought together to create a coherent, clean and useful data picture.

This data can originate from different systems, databases and departments and is merged in a central system or database.

The process of data consolidation can be manual or automatic and often includes data cleansing to remove duplicates and improve data quality. By merging and cleansing the data, the company can gain a better overview of its data and use it more efficiently for analyses and decision-making.

Consolidation is often necessary when data is available in several data silos or different departments, as this data is often disjointed and difficult to analyze. By consolidating data, companies can improve the quality and accuracy of their data, resulting in more efficient business processes and a better basis for decision-making.

Data consolidation enables companies to obtain a consistent and accurate picture of their data, which is essential for decision-making. It is an important step in data management and plays a crucial role in many areas, from reporting and analysis to business planning and strategy.

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The challenge: data from different sources

In today's digital world, companies are often confronted with a flood of data from various sources. This data can originate from different systems, databases and departments within the company and presents a challenge when it comes to consolidating it and extracting meaningful information from it.

Data silos are a common problem in many companies. These are isolated data pools within a company that are normally held at departmental level and are not accessible to other parts of the company. These data silos can significantly impair the efficiency and effectiveness of business processes, as they can make access to information more difficult and impair data quality.

The challenge is to consolidate this data from different sources and cleanse it in a way that provides meaningful and accurate insights.

This process of data consolidation is often a time-consuming and complex step, but a necessary one in order to improve data quality and gain valuable insights from the consolidated data.

Consolidating data from different sources also means that the data must be cleansed and checked for consistency in order to obtain high-quality information from the consolidated data. This is often an intensive process that requires expertise and in-depth knowledge of the data and its sources.

Despite these challenges, data consolidation and the cleansing of data from different sources offer considerable advantages. They enable companies to obtain an accurate and complete picture of their data, which is essential for well-founded decisions and efficient business processes.

The process of data consolidation

The process of data consolidation usually begins with the collection of data from various databases and systems. This can be a challenge, as each system and database has its own structure and data standard. These differences must be taken into account in the consolidation process.

Once the data has been collected from the various sources, it is brought together in a central system or database. This step can be performed manually or automatically and depends on the complexity and quantity of the data to be consolidated.

Another important step in the consolidation process is data cleansing. This involves checking and improving the quality of the data collected. This can include, for example, removing duplicates, correcting incorrect or inconsistent data and filling in missing data. Data cleansing is often an intensive and time-consuming process, but is essential to ensure the quality and accuracy of the consolidated data.

Once the data has been merged and cleansed, it can be used for various purposes. This includes creating reports, carrying out analyses, supporting decision-making processes and improving business processes.

The process of data consolidation is an ongoing process that must be carried out regularly to ensure that the consolidated data is always up-to-date and accurate.

Effective and well-executed data consolidation can provide significant benefits to an organization and improve its ability to make data-driven decisions and run efficient business processes.

Advantages at a glance

Data consolidation offers a number of advantages for companies.

Some of the most important ones are listed below:

1. increase in data quality:

Data quality is improved by consolidating and cleansing the data. Duplicates are removed, missing data is filled and inconsistencies are corrected. As a result, companies can access accurate and reliable data, leading to improved business decisions and business processes.

2. centralized data access options:

Successful data consolidation leads to the consolidation of data from different sources into a single, centralized system. This enables companies to access and manage all their data centrally. This increases efficiency and makes it possible to access information quickly and make well-founded decisions.

3. optimization of customer relationships:

By consolidating data, companies can obtain a more comprehensive and accurate picture of their customers. This can include customer data from different departments and systems, for example. By having access to consolidated customer data, companies can improve their customer relationships and offer more personalized services.

Data consolidation is therefore an important step towards improving data quality, facilitating access to information and optimizing business decisions. Despite the challenges associated with the process, the benefits are significant and can help keep a company on the road to success.

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Challenges and solutions

Although data consolidation offers a number of advantages, it also brings with it some challenges. One of these challenges is adapting to different data sources. Data often comes from different departments and systems within the company, each of which has its own standards and formats. This means that before the data is consolidated into a central system, it often has to be converted or adapted to make it compatible.

Another challenge is the technical and organizational considerations that go hand in hand with data consolidation.

On the one hand, implementing a standardized, centralized system that is able to process and store data from different sources can be technically complex and costly.

On the other hand, there may be organizational challenges, such as resistance to change within the company or difficulties in cooperation between different departments.

There are various possible solutions.

First of all, the use of specialized software for data integration and consolidation can help to overcome the technical challenges. These tools can help to collect data from various sources, clean it up and store it in a central system.

Data quality can also be improved by establishing clear guidelines and processes that describe how data should be collected, stored and managed. This can help to ensure that data consistency and quality is maintained and that the data can be used effectively for analysis and decision-making.

Last but not least, it is important to promote a corporate culture that recognizes the value of data and encourages its use.

This can help to overcome organizational obstacles and ensure that data consolidation is successfully implemented.


Data consolidation is a key process for companies to get the most out of their data. By merging and cleansing data from different sources, companies can improve their data quality, provide centralized access to information and optimize their business processes.

Despite the challenges associated with data consolidation - such as adapting to different data sources and technical and organizational considerations - the benefits are significant. Companies that consolidate their data effectively can make more informed decisions, improve their customer relationships and make their business processes more efficient.

In conclusion, data consolidation is crucial for companies in today's data-driven world.

It enables companies to use and manage their data effectively and provides the basis for data-driven decisions and business strategies. With the right tools and approaches, data consolidation can become a powerful tool for business success.

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