Data Warehouse Lab Work 9
Final Project Practicum I
Data Cleansing
Data Cleansing is a process of detecting and correcting (or removing) corrupt or inaccurate data sets, tables, and databases. Inaccurate data includes empty data that has no value or contains NULL/NaN values. The goal of data cleansing is to ensure that when the data is processed later, there will be no errors resulting from incomplete or missing data.
In this practicum, students are required to perform data cleansing on the given dataset as the first step of the Final Project Practicum. Below is the module along with the dataset.
Module
Dataset
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