Transformation is the act of taking a set of values from a dataset, processing them in some way (depending on the aims of the research) and arriving at a new set of values with the goal of revealing some aspect of the data from a new perspective. … »

The ability to “play with the data” is a critical capability in analysis. We utilize this technique in many situations: searching for patterns or trends in our observations; or as another preparatory stage for further analysis. Sorting data in some way – alphabetic, chronological, complexity or numerical – is a form of manipulation. … »

Deconstruction is one of the most frequently used and fundamental analysis techniques in our toolkit. It is used as both a preparatory technique to get research data ready for use in other ways; and a powerful technique in its own right as a method of isolating, exposing, and testing assumptions deeply embedded in our mental models. … »

Analysis is that oft-glossed over, but extremely important step in the research process that sits between observation (data gathering) and our design insights or recommendations. In many respects, analysis is crucial to realizing the value of our research since good analysis can salvage something from bad research, but the converse is not so true. This is where the literature tends to fall a little silent, jumping over the analysis techniques straight to a discussion of how best to document and communicate the findings from analysis. This article seeks to begin to redress that imbalance by breaking down the analysis black box into its major sub-techniques. … »