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Table Of Contents
Data Wrangling with SQL
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In this chapter, we will delve into the crucial aspects of dealing with missing data and NULL values during the data analysis process. We will explore the profound impact that these gaps in data can have on the accuracy and validity of our analyses if not appropriately addressed. By emphasizing the significance of data validation and cleaning prior to analysis, we will highlight the importance of ensuring accurate, complete, and relevant data in drawing meaningful conclusions and facilitating informed decision-making.
We will begin by unraveling the distinction between NULL values and 0, shedding light on their different meanings within the context of data analysis. Recognizing this distinction serves as the foundation for comprehending the different ways to handle NULL values effectively. Throughout this chapter, we will outline various methods for managing missing data in SQL, empowering you to make informed decisions when dealing with these data gaps.
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