
***This data is fictional and created for portfolio purposes. It is all for demonstration purposes.
Gilbert Anderson School Distict has data they need assistance with understanding, but it is very inconsistent and is quite difficult to analyze and understand. They require the data to be transformed into a more readable format, a data dictionary, cleaned, and to be analyzed based on specific questions around test scores.

In order to create a more readable data and something easier to explain to each other, students, and report out, the columns and data needed to be readable and easy to understand. A data dictionary is created and provided to Gilbert Anderson School Distict educators and administrators. ***Below is an example of the data dictionary and does not include all data dictionary terms from the field terms in the data.

For Gilbert Anderson School District to report on their data and be able to use their data, it needs to be standardized and clean. If a field is an integer, then it can only contain entries like (5, 23, 41, 80, etc.). It cannot contain entries with letters or alphanumeric entries or numbers with decimals. Step 1 is loading their data into a data prepper and begin the process of cleaning. (The highlighted portions in the picture show data entry inconsistencies that need to be addressed)

The Gilbert Anderson School District data goes through the process of data cleaning and data normalization. All of the inconsistencies, poor data quality, and data redundancies are addressed. All of the fields are renamed in accordance with the data dictionary. The data types have also been changed in order to reflect the kind of data within each field. At this stage, it allows the data to be aggregated and analyzed in various ways the organization would like. (Compared to Step 1 the data looks much more consistent and easier to handle and read)
