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Master data management: The lifeblood of your company?

Clean management of data before artificial intelligence

There is a lot of talk about artificial intelligence and data science today without realizing that the basic management of existing data must first be ensured.

Data forms the basis for most business processes and functions. If the data is inconsistent, redundant, incomplete, outdated, incorrect or simply not available, the company's services can hardly be provided optimally. Carefully managed master data management (MDM) is therefore a critical success factor for every company and is becoming a lifeblood.

From a technical perspective, data is also part of knowledge management. As a result, their existence, availability and economization drive both the innovative strength and competitiveness of the company.

High-quality master data as a basis for agile companies

The master data is state-oriented information from customers, suppliers, products and employees that hardly changes over a longer period of time. They generate business benefits for the company when the well-maintained data is immediately usable and accessible. High-quality data increases process quality, supports business decisions and increases the overall agility of the company to react to changes. Master data management is, in a sense, the key to digital transformation; the more data can be reused, the easier it is to implement digital processes, increase productivity and increase business success.

Data governance, the framework

Central components of master data management are data governance, data quality, data protection and IT architecture. Data governance is an upstream management system for defining the handling of data in the organization. It sets standards for how the master data is structured and who may use which data for which purposes. Governance also determines who is responsible for data quality. This in turn consists of the criteria of accuracy, completeness and timeliness.

How do I ensure data quality?

In order to keep data quality as high as possible, it is recommended to measure the quality of the data at regular intervals. The unique identification of a data set is essential here. Appropriate handling of personal data is also crucial for successful master data management.

The right approach to data protection

Privacy must always be protected and data misuse prevented. The easier it is to identify a person, the greater the data protection requirements when collecting and handling the data set. On data protection in Switzerland, taking into account the GDPR, on the occasion of the new Data Protection Act 2018, we have a five-part series of articles published.

Proper management using IT architecture

The last central component of master data management is the IT architecture. This supports business processes in managing data with infrastructure, automation and interfaces. As already mentioned at the beginning, the master data system is the lifeblood of the entire company.

With our know-how in the areas of data management, architecture, collaboration, integration, development, ICT consulting and project management, linkyard accompanies you through all stages of the introduction of master data management, from data analysis and development of a data model to data quality control, data integration, enrichment and control. linkyard is particularly specialized in technically complex integrations and customers with high standards of information security and data protection. The linkyard information security management system is certified in accordance with ISO/IEC 27001:2013. With this set of experience and know-how, we make the lifeblood of your company vibrate again.