Data Management

Data Management

In a world full of information, it is important to properly deal with this information. We create and manage your data warehouse and build relevant data marts accordant to your needs. The stored information is essential for further use in context of marketing and controlling.
Today, focus on the protection is on a similar priority level as the subsequent meaningful use of this data for market analysis and new or existing customer relations.

Why clean data

The customer data of a company is often stored in different databases. A core requirement for successful database marketing, however, is to save all the information for every customer in one place. This makes the merging of data from different data sources into a common marketing database necessary. Hereby we often come across the problem of data pollution or data integrity.

Concepts and Solutions

  • Process information (data processing)
  • Cleaning Information (Data Cleansing, Data Engineering)
  • Consolidate Data (deduplication)
  • Build and maintain information processes
  • Explore ideas and possibilities of existing information by enrichment

What services can we offer you with address details?

  • Duplicate check
  • Spell check
  • Address validation and cleanup
  • Structure check
  • Case-sensitive test
  • Testing for hyphenated words
  • Testing for involuntary abbreviated words (too small cells)
  • Testing for non-advertised umlauts
  • Check for special characters
  • Testing for import and export errors
  • Examination on fantasy values ​​and dummy entries
  • Check for duplicate entries
  • Examination of the flag salutation
  • Testing and standardization of the title
  • Cleanup and standardization of all phone numbers
  • Check for relocated contacts (relocation matching)
  • Check for mortality data
  • Examination on advertising ban (Robinson list / Nixie list)
  • Examination on credit issues, home addresses
  • Check for bankruptcies or debt collection proceedings, business addresses

What can we offer you for the rest of the data?

  • Statistical identification of outliers
  • Detecting incorrect field contents
  • Determination of incorrect checksums and formula errors
  • Identify errors in missing contents / deleted contents

The management of data is not just for big data a basic prerequisite for the further use