Initial writeup: Sept 2022. Last update: Sept 2022.

When I worked in a news media, I found out 90% stories can be discovered with a few simple steps. Here's the cookbook of visual analysis methodology, despite which visualization tool one uses.

## Methodology

A common exploratory **visual** analysis process:

- Add a flat table to view actual data. Pick a few dimensions/ metrics to understand the data points.
- Apply 1-dimensional analysis on all (all interested) metrics.
- MIN, MAX, MEDIAN can already tell many stories
- One can make histogram to view the distribution
- You may want to discretise continuous variable sometimes
- You may want to turn textual but ordinal variable into numeric variable sometimes

- Leverage time series if there is a date time dimension
- Pick one metric and check its statistics conditioned on a
**time part**can usually yield insights - Plot a metric over time dimension to observe the trend.
- Use breakdown dimension to compare multiple values.

- Pick one metric and check its statistics conditioned on a
- Leverage bar/ pie for categorical data
- You may want to sort by the metric for most of the time to make the presentation meaningful.
- Stacked bar and 100% stacked bar can emphasise different information

- Map is good to uplevel the presentation but it is same as a bar chart under the hood (one categorical dimension + one metric)
- Map adds value only when the metric distribution is geo related

- Apply 2-dimensional analysis.
- Add controls (filters) as many as possible
- Use controls to filter the view and answer the question: what is A statistics of B metric when C column equals value D

- Further more, leverage scatter plot (2-D) and bubble chart (3-D to 4-D) to visualise more variables in one go.