Data cleansing is a key part of big data pre-processing. This book explains the theoretical knowledge and practical applications of data cleansing, and it is divided into 8 chapters: Chapter 1 leads you to a simple understanding of data cleansing; Chapter 2 explains relevant knowledge of ETL technology; Chapter 3 elaborates the basic use of Kettle tool; Chapter 4 illustrates the first step of data cleansing – data extraction; Chapter 5 explains data cleansing and validation; Chapter 6 introduces the knowledge related to data conversion; Chapter 7 illustrates the relevant knowledge of data loading; Chapter 8 uses the knowledge learned in the previous chapters to build a data warehouse for a DVD rental store, the purpose of which is to regularly extract incremental data from the source database sakila, convert it into data that meets business requirements, and finally load it into the data warehouse, so that store managers can make business decisions based on the data.