Transforming Data into Information
WHILE DATA IS SOMETIMES VALUABLE ON ITS OWN, its true worth is derived when it becomes meaningful and useful information. The path from data to information is not always apparent nor is it necessarily easy to navigate. By way of a few examples and explanations, this chapter provides some insight into how the value of data can be uncovered. Specifically, we discuss examples of using data analysis to discover pricing trends, target and optimize cost savings opportunities, and drive contract compliance.
After you complete the data collection phase of your initiative, the analysis of that data starts with cleansing the data set, which involves identifying corrupt, invalid, inaccurate, inconsistent, missing, or duplicate data and taking an action according to predefined rules. The action taken differs on a case-by-case basis. For example, duplicates may be deleted and corrupt data may be corrected or tagged.
While cleansing data, it is important to look for variations that a simple matchup in Microsoft Excel might not catch. For instance, a common mistake that many organizations make when entering purchase orders is creating an item that is already in the system, which leads to duplicate data. Although items have identical or similar descriptions in the system, they have unique part numbers. Therefore a sort-and-compare task in Excel is not going to reveal them as duplicate items. This illustrates the importance of human ...