Examples of BA uses include:

  • Exploring data to find new patterns and relationships (data mining)
  • Explaining why a certain result occurred (statistical analysis, quantitative analysis)
  • Experimenting to test previous decisions (A/B testing, multivariate testing)
  • Forecasting future results (predictive modeling, predictive analytics)

Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing, and integration into a single repository such as a data warehouse or data mart. The analysis is typically performed against a smaller sample set of data. Analytic tools range from spreadsheets with statistical functions to complex data mining and predictive modeling applications. As patterns and relationships in the data are uncovered, new questions are asked and the analytic process iterates until the business goal is met. Deployment of predictive models involves scoring data records (typically in a database) and using the scores to optimize real-time decisions within applications and business processes. BA also supports tactical decision making in response to unforeseen events, and in many cases the decision making is automated to support real-time responses.