1.1 Data Analysis Categories – Intro to Excel 2016 Data Analysis

Data analysis is the study of various types of data and bringing together various pieces of data to form meaningful relationships. From those relationships, the Excel user can see patterns or trends by aggregating the data and creating visual representations of that data through charting or some other visual representation of the data.
Data Analysis Categories
1. Descriptive Analytics – what happened (Our Excel studies fall primarily in the Descriptive category)
    a. Data aggregation – What is it? Data aggregation is the process of gathering data and presenting it in a summarized format. Examples of aggregating data are                          Excel/Access Data tables, Excel Pivot tables.

1. Once data is gathered, it can be graphed in a chart for printing and/or used in a PowerPoint presentation.

     b. Data mining – sifting needed data from datasets

1. 1. Creating Queries
   2. Pulling data from databases
   3. Tabulating the data and aggregating it through Data tables and Pivot tables.

 2. Diagnostic Analytics – why did it happen
     a. Regression analysis
     b. Filtering
     c. Time-series analysis 
3. Predictive Analytics – what is likely to happen in the future
     a. Regression analysis
     b. Machine Learning 
4. Prescriptive Analytics – what is the best course of action (the most complex)
    a. Algorithms
    b. Machine Learning
    c. Statistical Methods
    d. Computational Modeling