Data Quality



BIS3's expertise is centered around a core competency in Data Warehousing (DW) and Business Intelligence (BI) which has proudly become a proven track record of success for the company. Our approach and methodology to a successful implementation and development lies in developing the proper data architecture. With it in place, it provides the necessary foundation to a successful BI solution and other downstream data-centric application. 

The entire approach revolves around the central theme of "getting the right information to the right person at the right time". This is the core that fuels our wholehearted push toward providing exceptional solutions and service to our valued clients.
Data Cleansing 
A data cleansing tool performs various functions to improve the quality of data, such as:
  1. Duplicate removal: Identifying and removing duplicate records from the data set.
  2. Data standardization: Converting data into a standard format, such as converting all dates into a uniform format.
  3. Data validation: Verifying that data meets certain criteria, such as checking that all email addresses are valid.
  4. Data enrichment: Adding additional information to data, such as geographical information based on postal codes.
  5. Data correction: Fixing errors in data, such as typos or incorrect values.
  6. Data de-duplication: Removing similar records from the data set to avoid redundant information.
  7. Data normalization: Converting data into a consistent format, such as converting all phone numbers into a uniform format.
The goal of a data cleansing tool is to improve the accuracy, completeness, and consistency of data, making it more usable for analysis and decision-making.
  • Duplicate Removal
  • Data Standardization
  • Data Validation
  • Data Enrichment
  • Data Correction
  • Data De-Duplication
  • Data Normalization​