Our mental model of a dataset changes the way we ask questions. One aspect of that is the shape of the data (long or wide); an equally important issue is whether we think of the data as a collection of rows of numbers that we can aggregate bottom-up, or as a complete dataset that we can slice top-down to ask questions. [Read more…] about Row-Level Thinking vs. Cube Thinking
These articles cover the fundamentals: data, techniques, statistics, etc.
The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it’s important to understand their differences and when each is the right choice. [Read more…] about Spreadsheet Thinking vs. Database Thinking
Conventions in visualization can seem arbitrary, and quite a few are. But there is also a vast body of research, and it is growing every day. Just how does visualization research work? How do we learn new things about visualization and how it can and should be used? [Read more…] about Visualization Research, Part I: Engineering