Data management - the key to success for companies

from | 20 September 2021 | Basics

Data is an important asset for companies. To make the most of the potential of data, good data management is essential. In this blog post, we want to highlight the challenges of data management and present best practices on how companies can generate the most value from their data.

Data management as a competitive advantage

The term data management covers the creation, maintenance, securing and use of data. Within a company, all elements of the information cycle are interconnected. The aim is for employees to have access to and use correct, up-to-date data.

The better the data is managed, the more effectively the different teams can interact with each other and the faster decisions can be made, which, not least, form the basis for new business models. Good and professional data management is therefore a decisive competitive advantage.

Basics of data management: data creation, quality assurance and processing

A coordinated approach is recommended for effective data management. Not only master data management, but also comprehensive quality control and sensible structuring of data are important.

Master data management - the basis for effective decisions

The core of data management is master data management. This ensures that companies base their decisions on a single, correct database. Information from all existing sources is brought together centrally. The quality and reliability of the data are elementary.

Quality management - ensuring uniform, correct data

To ensure the quality of the data, it must be checked. This includes, for example, searching for and correcting duplicate or incorrect entries. The processing of the data is based on data management guidelines.

Data warehousing - structuring the masses of data

Companies generate an enormous amount of data every day. In order for this to be used effectively, structuring is important in addition to quality. Through a Data Warehouse Management the infrastructure is provided to store, aggregate, analyse and meaningfully process the collected information.

Data volume, lack of experience and knowledge silos as a challenge

For many companies, the implementation of data management is a challenge. The large amount of data already in the company and the daily growth lead to excessive demands. The problem is complicated by so-called ROT data (Redundant, Obsolete, Trivial). This means that many duplicates and superfluous information are stored in the company. On the one hand, this takes up valuable storage space, but on the other hand it also makes it difficult to keep track of and focus on the important data.

In addition, internal knowledge silos exist in many companies. Data is not stored centrally, but is only available to individual employees. As a result, not all sources of information are known. In the first implementation phase of data management, it is therefore important to identify all sources and storage locations. The goal is to connect them with each other and thus make the data available to the entire company.

Another challenge is the lack of expertise and experience in data management. Correspondingly qualified employees are not available in many companies. Therefore, it is worthwhile to involve experienced specialists and experts. They can analyse the situation in the company and provide targeted support in creating a concept. This concept determines how and according to which criteria the data should be prepared, sorted, sifted and categorised. Through the targeted training of employees and management, data management can be established smoothly and sustainably.

Intelligent data management is based on the right mindset and appropriate solutions

Companies should not be deterred by the initial challenges of data management. Once these have been overcome, the successful handling of data provides a strategic competitive advantage. The following recommendations and best practices provide valuable support.

Data management serves many purposes

It is essential not to view data management as a solution to a particular problem. Rather, it should be seen as a way to make all data transparently available. In this way, information management serves many purposes - for example, developing new business models, securing information in the event of a claim and complying with legislation.

Use appropriate data management software

Data management software enables processes to be managed easily and quickly. Templates allow users to manage data without errors, and data protection aspects are monitored and ensured by the system. The selection of a suitable solution should be based on a catalogue of requirements.

Reduce storage costs

The increasing amount of data also increases the consumption of infrastructure resources. This has a direct impact on costs. It is therefore advisable to look for ways to reduce storage costs. Storage management solutions can transparently display the costs incurred. This allows potential savings to be identified, e.g. in the form of deleting ROT data or migrating to more cost-effective storage.

Reduce sources of error

Another prerequisite for good and effective management of one's own data is the lowest possible susceptibility to errors. In this context, it is advantageous if the number of human interventions in the processes is kept as low as possible in order to avoid errors.

For this reason, quality assurance according to the four-eyes principle also makes sense in order to sustainably reduce the number of errors in data management and to ensure a reliable and qualitative database.

Powerful AI ensures smooth processes

On the basis of Artificial intelligence and machine learning can be used to automate and optimise many processes. Therefore, the use of a Data management solution in conjunction with AI particularly rewarding. One use case, for example, is to automatically check the input of data for errors. AI can also be used to automatically enrich product data, for example, which speeds up data entry many times over.

Data management and data security - keeping an eye on the GDPR

The management of personal data is aligned with the General Data Protection Regulation. Professional data management ensures DSGVO-compliant storage and use. In addition, compliance-related reports can be easily created through the centrally collected data.

With the right management, companies benefit from the asset of data

Companies need to adapt to the demands of the current times. Reliable data is becoming increasingly important for making safe and good decisions and developing new business models. Good data management supports companies sustainably in managing and using all relevant data and creates competitive advantages.



Our AT editorial team consists of various employees who prepare the corresponding blog articles with the greatest care and to the best of their knowledge and belief. Our experts from the respective fields regularly provide you with current contributions from the data science and AI sector. We hope you enjoy reading.

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