Plotting numbers on a chart does not make you a data analyst. Knowing and understanding your data before you communicate it to your audience does. Understanding data is challenging and this chapter is designed to help you understand these important ideas:
- The concept of data aggregation
- How to effectively communicate metrics to your audience
- How to identify and correct mistakes in your analysis
- How to understand and present time series data
Using Appropriate Aggregations
Aggregated data is data combined from several measurements for the purpose of summarization.1 Some of the uses for data aggregation include:
- Understanding higher-level groupings of the data (e.g., sales per region vs. each individual transaction)
- Reducing query times
- Finding patterns, trends, and outliers
- Providing a starting point for deeper data analysis (i.e., identifying problems at a higher level and then drilling into the data to find the specific problem)
This section will help you understand whether data can be aggregated, some basic aggregation methods, and things to watch out for.
Can the Data Be Aggregated?
When working with aggregation, it is important to avoid metrics that aggregate data that is already aggregated. What does this mean?
Aggregating summarized data to a higher level will often work. However, there are aggregations you cannot aggregate further without additional data. It takes time and practice to understand data aggregation. To aid you ...