Master Data Management

Accurate master data is the basis for smooth business processes and valid decisions.

Master Data Management (MDM) includes all organizational and/or technology-based activities for the sustainable improvement of company-wide master data. These take place in close cooperation between the individual business units and the IT department. In this way you ensure good data quality in your business processes and your entire company.

Company-wide master data form the basis for the strategic and operational management of every organization. They describe the core business objects. They are clear and consistent. They are used across departments and have a high value.

The goal of master data management is to create a uniform view of the data, to determine correct data records (golden records) and make them available in one place (single point of truth).

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Check out our tool for master data management


Overview of the typical master data domains in a company

Customer master data
Customer master data
Read your customers’ wishes from their lips, enable a correct personal approach, think of your customers for their birthday and support them in case of problems with a quick and easy solution. Furthermore, well maintained customer data is the basis for your customer analysis and customer value calculation.
Material master data
Material master data
Ensure a smooth supply chain and keep track of your resources. In addition, take advantage of the savings potential from larger procurement volumes in purchasing and prevent capital commitment and increased process costs.
Product master data
Product master data
Manage the data streams in your merchandise management and shop systems efficiently and noticeably increase the data quality in your online shop. Rely on valid and high-performance reporting through reliable product data.
Supplier master data
Supplier master data
Systematically build the central foundation for effective management, negotiation and control of your suppliers. Meet the high expectations of your customers: a smooth user experience (e.g. perfect search results) and purchase processing (correct shipping) – both dependent on maximum data quality.
Financial master data
Financial master data
The central organization and administration of your financial and accounting data ensures the highest data quality for accounts receivable, accounts payable and assets as well as other accounting data. The optimization of data quality results in simplified invoice verification and further invoicing. It also creates the basis for cost controlling.


Do you have problems with incomplete, incorrect or duplicate master data? This can not only tie up valuable resources, but can also have a significant impact on your business decisions.


Advantages of master data management

Master data is used throughout the company in a variety of processes, for example to optimize materials management, resource allocation in the organization or to create reports and decision bases for corporate development. The close integration of master data thus requires excellent management and optimal data quality.

Cross-departmental advantages of master data management:

Master data management creates the following advantages in your company:

Illustration of the relationships between data from different sources

Data from different applications are interdependent and can be made visible by means of rules (mapping). Mapping is derived from corporate strategies and the resulting definition of structures and relationships. In this way, consistency in data records and terminology can be maintained.

Which turnover was achieved with the “right” customer Peter Müller?

Identification of “golden records” in the entire data landscape

When merging master data from different systems or applications, data records that are incomplete, redundant or inconsistent are unified. As a result, all company-wide information is displayed centrally.

Find out if Peter Müller and Peter Mueller are the same person.


Control over responsibilities and interactions

Using the same master data records from different departments and persons is an organizational challenge. For this reason, the definition of roles, authorizations and workflows guarantees an overview of changes and thus enables high data quality to be maintained.

Define that only Mr. Müller’s personal customer advisor is allowed to change his master data.


Master data management with DataRocket

DataRocket is the master data management software to improve your data quality.

DataRocket is our multi-domain master data management software that consolidates and cleans up your databases. Simple operation and clear design provide uncomplicated and lastingly improved data quality throughout the company. With our complete solution you can optimize your data management across all domains. Whether customer data, material data, creditor data or other master data, with DataRocket you can manage your data streams in a structured way.

Master data management with innoscale Benefit-1


DataRocket focuses on improving data quality in master data and provides comprehensive reports and insights.

Master data management with innoscale Benefit-2


DataRocket offers users a visual user interface that can be operated in the browser without programming knowledge.

Master data management with innoscale Benefit-3


DataRocket functions as a hub between different databases and applications, which can be easily integrated into the IT architecture.


Project progress

Introduction and optimization of master data management in your company

The introduction and development of optimum master data management is divided into different project phases. MDM requires close cooperation between the individual business units and the IT department.

From our experience, we have identified four project steps to ensure the best data quality and a high level of MDM maturity in your company.

Screening of the data landscape

The first step in introducing master data management is the structured recording of customer requirements and company goals (screening of the data landscape). For this purpose innoscale AG offers the DataCanvas, a workshop format for determining the maturity of your master data.

Checking of data sets

To optimize your data landscape, it is necessary to determine the quality level of your data. In a starter project, this will give you an overview of the number of duplicates, errors, fill levels and other individual quality criteria. This forms the basis for a targeted approach to improve your data quality.

Cleanup projects

Use the knowledge about the weaknesses in your databases and clean up your data. DataRocket can manually or automatically cleanse and merge your data based on workflow. Thus you receive a quality-tested data stock and golden records.

Real-time quality assurance

Protect your data stock from a decline in data quality during the daily work in the company. Using DataRocket as a central hub provides a single point of truth. Here you have the data from all systems in use in one place and can manage targeted processing and access to data. The software checks all new installations or changes to your data stock directly during entry. Regular reports give you an overview of the good data quality in your company and always in real time the basis for good business decisions.