Understanding data driven intelligence
Analytics is an important tool for all businesses, and examines data to find and then communicate meaningful patterns. It’s not just about analysing information, but finding a use for it too. Advanced analytics deals with data via autonomous or semi-autonomous methods. This can include data mining, machine learning, forecasting, visualisation and neural networks. Advanced analytics has sprung from the wider availability of information facilitated by Big Data, digitalisation and the Internet of Things, and is becoming more important as profit shifts from product to data.
Successful businesses use data analysis to gain valuable insights into consumer markets and how their own company operates, but sophisticated methods give them an edge over competitors. Whereas traditional tools concentrate on historical data, advanced analytics focuses on current and real-time info to predict future events and trends. Predictive analysis, which is enabled by Artificial Intelligence, is therefore a sub-category of advanced analytics. This has obvious advantages for essentially any organisation, as by predicting behaviours they stand a better chance of influencing them.
Advanced analytics may be something of a miracle tool for businesses, however the exploitation of personal data to achieve certain ends has faced criticism. As data is so easily accessible, it’s often impossible to know if your personal information is fuelling targeted campaigns. Organisations should be incredibly careful about how they apply advanced analytics, for the sake of their own image if nothing else.