data-cleansing

Vocabulary Word

Definition

The term 'data-cleansing' refers to the process of identifying, correcting or removing bad, inaccurate, or irrelevant parts of datasets. It's like a data hygiene routine, ensuring that data remains accurate, complete, and usable.

Examples in Different Contexts

In data warehousing, 'data cleansing' is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database. A data warehouse engineer might say, 'Data cleansing is critical to ensure that our data warehouse provides a clean, consistent basis for our analytics tools.'

Practice Scenarios

Marketing

Scenario:

We have duplicate entries in our customer list. This could lead to wasteful expenditure on communications and promotions.

Response:

Absolutely, a thorough data-cleansing process can help us remove duplicates and maintain a clean customer database.

Business

Scenario:

Our sales report appears biased due to outdated entries. We need to make sure that we use valid data for performance evaluation.

Response:

Agreed, I will initiate the data-cleansing process to remove outdated sales entries and recompile the report.