Data Quality

With data serving as the basis for making most decisions, poor quality of data can have profound negative effects on your business solutions and performance. High company costs may trace back to inconsistencies in data and could result into ineffective communication with your customers. Data cleansing can rectify the incorrect, missing, or duplicated data that affects the perceived quality and reliability of your business.

Data Cleansing

CloverETL improves data quality through its own specialized transformation language that allows implementing very complex validation rules. Clover Transformation Language (CTL) further broadens the palette of data cleansing focused functionality by offering edit distance, soundex, metaphone, NYSIIS and other functions.

Several transformation components are available in CloverETL’s user interface to perform validation of email addresses or joining and looking up data based on similarity. Furthermore, the standard set of data cleansing functionality is extended through use of specialized address validation and cleansing add-ons such as AddressDoctor.

In additional to our CloverETL solution, Professional Services can assist in cleaning invalid and in accurate data for your enterprise.


  • Improved effectiveness of product
  • Increased cost savings
  • Strengthened customer relations
  • Formulated smarter business decisions
  • Gained competitive edge

Case Study

Read our Data Cleansing Case Study, which shows how our customer improved delivery efficiency through use of CloverETL for data validation and data cleansing.