Advanced data analytics comprises the development and use of a range of tools and processes for analysing and learning from raw data. We can solve problems and understand relationships better on the basis of observations. The tools of advanced data analytics are based on statistics, maths and information technology. Advanced data analytics is a step-by-step process of grouping, compiling, organising and analysing data rather than a single software solution.
The more data you have available, the better your analysis will be – provided that your data is of good quality. Advanced data analytics can, for example, uncover trends that would otherwise have been undetected in the mass of information. Although the analysis processes can be carried out manually, the majority are now automated. Using the software available from various cloud services makes it a lot simpler than before to analyse and gain greater insight into complex data sets.
Data streaming makes it possible to carry out analysis in real-time and to react more quickly, or entirely automatically, to the results of the analysis. Advanced data analytics therefore opens the door to numerous new opportunities. Here are some example applications:
1. Insurance companies and banks can understand variations in risk for their insurance and loan portfolios.
2. Broking firms can gain deeper insight into fluctuations in equity and energy markets.
3. Manufacturing companies can optimise their energy consumption, warehouse management, orders and use of machinery.
4. Content providers and online shops can use insights to understand what is required for us to continue to watch, read, click or buy.
5. The health sector can gain deeper insight into cell metabolism, the spread of infectious diseases and how patient flows can be made more efficient.
6. The airline industry uses advanced data analytics to plan their fleets and routes and to manage their inventories.
7. Uber combines advanced data analytics with data streaming when calculating its variable prices.
As it has become easier to access large quantities of data, advanced data analytics has become a high-growth area. The real driver for its development, however, is companies’ desire to optimise their operations by finding new growth opportunities, increasing customer satisfaction and improving their commercial processes.