Bardess will assist your entire organization in the cleansing, editing and improvement of data in your legacy databases or from extracted source data during data migrations.

The Cleansing Activities are aimed at improving enterprise data quality and integrity and optimizing the success of transformation and integration processes during data migrations.

The Improvement Processes enhance the data in order to provide higher quality information to business users.

Bardess Cleanses Dirty Data

Bardess will develop and implement a complete data cleansing and improvement program or augment your current efforts with targeted activities. Data cleansing and improvement programs begin with a review of the remediation plans developed through a comprehensive data assessment process. Cleansing data without a thorough data assessment may produce ad hoc, incomplete or incorrect results.

Our consultants will work closely with your business process owners and/or your data quality teams in IT performing the following tasks while ensuring that the process yields the desired results.

With Business owners

Specify data cleansing business requirements based upon Data Remediation and Improvement plans. Identify cleansing rules including:

  • Data structure
  • Matching criteria
  • Error/exception disposition
  • Record consolidation criteria

Review and validate cleansed data output to ensure that it meets the previously defined business requirements and rules, clarifying and refining the business requirements and rules throughout the remainder of the development lifecycle.

With IT Professionals

  • Assist in the development of data cleansing plans, processes and procedures.
  • Build scripts to update selected data based upon business rules.
  • Select tools for cleansing based upon business requirements.
  • Train in the use of data cleansing and improvement tools (e.g., D&B, FirstLogic, Trillium, etc.).
  • Perform defined data clean up activities.
  • Develop a cross-reference between original records and cleansed/updated records.


  • Data Cleansing and Improvement Plan Development
    • Requirements
    • Process and Procedures
    • Priorities and Schedule
  • Cleansing Rule Development
  • Enhancement Rule Development
  • Automated Cleansing Routines
  • Tool Identification and Selection
  • Data Cleansing Implementation
  • Data Enhancement Implementation
  • Data Error Prevention
  • Validations