Chapter 5, Problem 1DQ

Program Plan Intro

Data cleansing:

Data cleansing or scrubbing is a step in the data reconciliation process.

• In this step, the problems or the errors in the data are identified and rejected.
• Then, to fix the errors, the flag message is sent back to the source.

Common tasks in data cleansing:

• The data are decoded in such a way that it suits the form of the data warehousing applications.
• Breaking the text fields into constituent parts.
• Represent the data in the required standardized formats.
• Format the data type of the data with the standard data type format.
• Same attribute on different time is added with the timestamp.
• Convert the different units in the data into a same unit.
• For each row, the primary key is generated in the table.
• Matching data are extracted and grouped together.
• Logging errors are detected and fixed.
• The missed data are found out to continue the subsequent loading.

Program Plan Intro

Data cleansing:

Data cleansing or scrubbing is a step in the data reconciliation process.

• In this step, the problems or the errors in the data are identified and rejected.
• Then, to fix the errors, the flag message is sent back to the source.

Common tasks in data cleansing:

• The data are decoded in such a way that it suits the form of the data warehousing applications.
• Breaking the text fields into constituent parts.
• Represent the data in the required standardized formats.
• Format the data type of the data with the standard data type format.
• Same attribute on different time is added with the timestamp.
• Convert the different units in the data into a same unit.
• For each row, the primary key is generated in the table.
• Matching data are extracted and grouped together.
• Logging errors are detected and fixed.
• The missed data are found out to continue the subsequent loading.