- Descriptive Analytics:
Descriptive analytics focuses on summarising historical data to gain an understanding of what has happened in the past. This type of analysis provides a snapshot of the current state of affairs and is primarily concerned with answering the question, “What happened?” Common techniques used in descriptive analytics include data aggregation, data visualisation, and basic statistical analysis. Businesses often use descriptive analytics to track key performance indicators (KPIs) and assess overall performance.
- Predictive Analytics:
Predictive analytics involves using historical data and statistical algorithms to forecast future outcomes. By identifying patterns and trends, organisations can make informed predictions about future events. This type of analysis is essential for anticipating customer behaviour, market trends, and potential business risks. Machine learning and statistical modelling are commonly employed in predictive analytics to build models that can make accurate predictions based on historical data.
- Prescriptive Analytics:
Prescriptive analytics goes beyond predicting future outcomes by recommending actions to achieve desired results. This type of analysis takes into account various possible scenarios and suggests the best course of action to achieve specific objectives. Prescriptive analytics is particularly valuable in decision-making processes, providing actionable insights that can optimise business processes and strategies. It considers the impact of different decisions on outcomes and helps organisations make informed choices.