Data analytics
Default set
Why
Gain insights by measuring and analysing data. Researching a dataset can give you useful quantitative information about the topic of interest.
How
Collect data that is relevant for your area of research and analyse it. Split your dataset into a training set and a test dataset. Find an algorithm that works with the training data and check whether it is reliable with the test data.
Practice
Applied data science is now done in many fields. For example, it is used in the business domain to predict customer behaviour
Ingredients
- A data collection plan.
- Analysis tooling (e.g. statistical tooling or machine learning algorithms).
- A critical eye on the validity of your data and your conclusions
- Comprehensive data visualisations
Phases
- Analysis
- Design
Trade-offs
InspirationData
ExpertiseFit
OverviewCertainty
Read more about the trade-offs: Inspiration or Data / Expertise or Fit / Overview or Certainty.