Data Analytics & Visualization All-in-One For Dummies
by Jack A. Hyman, Luca Massaron, Paul McFedries, John Paul Mueller, Lillian Pierson, Jonathan Reichental, Joseph Schmuller, Alan R. Simon, Allen G. Taylor
Chapter 4
Tweaking Data for Primetime
IN THIS CHAPTER
Understanding the data lifecycle
Addressing inconsistencies with data types, values, keys, structures, and queries
Streamlining data based on queries and naming conventions before data loading
For any data cleansing and transformation to take place, your organization needs analysts and engineers — and detectives. The idea here is that you must first analyze the data before entering the system or after it exists in its intended data store. Simply glossing over the data alone doesn't cut it. You need to follow a rigorous process as you look for those needles in your data haystack. Without a rigorous process, you can't ensure data consistency across all columns, values, and keys. By following a meticulous analysis process, you can engineer optimized queries that help load the data into the system without issues. This chapter helps you develop that process by evaluating the whole lifecycle and the supporting activities the Power BI professional must undertake in order to make their data shine for visualization consumption.
Stepping through the Data Lifecycle
Data is seldom perfect. Unless you’re connecting to a prepared dataset ...