Master data management and artificial intelligence

Classical methods and tools for master data management (MDM) are usded to improve data quality or data homogenization. The quality of the results depends on micro-managing of rules or manual mappings.

By using MDM systems you can significantly decrease manual adjustments through central storage.

Artificial Intelligence

However, it’s still hard to prevent errors in mapping, typing or duplicate entries. This leads to manual modifications and costly time delays.

Artificial intelligence will help to significantly accelerate and reduce the effort by 80-90% for the processes in the field of masterdatamanagement (MDM). The MDM booster acts as a service (Bot) and provides the SAP, PIM, CRM, Big Data or DWH system with consolidated, enriched or adjusted information about customers, suppliers, products, etc.

Typical information is e.g. validations of weight, location, addresses or classifications (e.g., correct part family). Instead of defining a variety of rules or performing manual checks and data collections, the AI ​​handles most of these tasks.

Use Cases

Purchasing processes, sales, supply chain management – everybody needs correct master data (e.g. article groups, sub-families, suppliers, customers) and will benefit from an error-free and up-to-date database. When developing big data or data warehouse systems a lot effort is spent on master data management and data quality (homogenization and historiography of members inside dimensions, check for duplicates, etc.).

Inside Spend data for the last month we found 524 unknown Suppliers. Only 6 Suppliers must be updated manual. I would argue that machine learning supplier mapping with the MDM-booster is pretty good.

Wow – more than 2500 unknown Adresses in less than 10 Seconds cleaned up. Usually this would have take weeks.

MDM-Booster – the solution for efficient master data management and data quality processes

MDM-Booster minimizes the efforts for initial and continuous maintenance of master data and data quality processes:

  • The artificial intelligence learns from existing data and associations
  • Standardized process (CRISP-DM)
  • No need for meta-databases (i.e. usually necessary for semantic analytics)

Customer of MDM-Booser in medium-sized and large companies were able to reduce the time needed for master data management and data quality tasks from months per year to hours per year.

Benefits:

  • Rules (matching rules) are extracted automatically
  • The methods used can be scaled as desired and are able to perform great with extreme high data volumes and work multilingually
  • No or only minimal manual maintenance necessary

MDM Booster

Web solution and many interfaces to automate your processes

MDM-Booster offers an intuitive web interface for fast and easy usage:

Oberfläche MDM-Booster

To automate your processes, a lot of interfaces and functions are available:

  • RESTFul-Webservice
  • jdbc (Oracle-Databas, SQL-Server, DB2, PostgreSQL)
  • Excel
  • Webservice
  • Integration into SAP Systems

Solutions and Consulting

Do you want to know more about the possibilities of MDM-Booster? Just call us. We will gladly advise you personally.

 

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