Introduction & Data-Analytic Thinking

Question 1

CRRISP DM

Answer 1

1. business understanding: Define the problem to be solved, the scope
2. Data understanding: what data are available data and its strengths and limitations
3. Data Preparation: aggregated, manipulated, normalised
4. modelling: Create the models, use different data mining techniques
5. Evaluation: assess the outcome of the modelling stage and determine whether the models are useful to help solve the problem
6. deployment: results of the data mining output are put into real use in production

Question 2

Different types of analytics

Answer 2

1. descriptive analytics: what happened? use data visualization, clustering, and co-occurrence grouping
2. predictive analytics: what will happen? use classification, regression, link prediction
3. diagnostic analytics: why did it happen? casual analysis, simulation
4. prescriptive analytics: how can we make it happen? uplift modeling, automation