Glossary:Data analytics
Data analytics refers to the use of technologies, techniques or software tools for analysing data to extract patterns, trends and insights to make conclusions, predictions and better decision-making with the aim of improving performance (e.g. increase production, reduce costs). There are four primary types of data analytics. Each type of data analytics is used for specific purposes depending on the question a data analyst is trying to answer. These types are:
- Descriptive analytics - helps to answer questions about what happened. This type provides essential insight into past performance and requires the collection of relevant data, processing of the data, data analysis and data visualisation.
- Diagnostic analytics - helps answer questions about why something happened and supplements more basic descriptive analytics. The findings from descriptive analytics are taken and analysed further to find the cause (e.g. why performance got better or worse). Usually this occurs in three steps: a) Identify anomalies in the data; b) Collect data that is related to these anomalies; c) Use t statistical techniques to find relationships and trends that explain these anomalies.
- Predictive analytics - helps answer questions about what will happen in the future, whereby historical data is used to identify trends and to determine if they are likely to recur. Predictive analytical tools provide valuable insight into what may happen in the future and its techniques include a variety of statistical and machine learning techniques, such as: neural networks, decision trees, and regression.
- Prescriptive analytics - helps answer questions about what should be done, namely by using insights from predictive analytics. This allows enterprises to make data-driven (informed) decisions. Prescriptive analytics techniques rely on machine learning strategies that can find patterns in large datasets. By analysing past decisions and events, the probability of different outcomes can be estimated.
Data may be extracted from own enterprise data sources or from external sources (e.g. suppliers, customers, government).
Further information
- ICT usage in enterprises (ESMS metadata file — isoc_e)
- Digital economy and society - dedicated section