CHAPTER 11Transforming Data in Access
Data transformation generally entails certain actions that are meant to “clean” your data—actions such as establishing a table structure, removing duplicates, cleaning text, removing blanks, and standardizing data fields.
You'll often receive data that is unpolished or raw—that is, the data may have duplicates, there may be blank fields, there may be inconsistent text, and so on. Before you can perform any kind of meaningful analysis on data in this state, it's important to go through a process of data transformation or data cleanup.
In this chapter, we introduce you to some of the tools and techniques in Access that make it easy for you to clean and massage your data without turning to Excel.
Finding and Removing Duplicate Records
Duplicate records are absolute analysis killers. The effect duplicate records have on your analysis can be far reaching, corrupting almost every metric, summary, and analytical assessment you produce. For this reason, finding and removing duplicate records should be your first priority when you receive a new data set.
Defining duplicate records
Before you jump into your ...
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