Data Analytics
What is it?
What Are Prescriptive, Predictive And Descriptive Modelling And How Can They Help Your Business?
Data analytics is the process of examining sets of data to make conclusions about the information it contains. Data analytics techniques are widely used in commercial industries to make key business decisions and by analysts and scientists to verify or disprove scientific theories and hypotheses.
Effective data analytics technologies increase business revenues, become more efficient in the way they run and create an edge over competitors in a similar market. Data that’s analysed can be made up of either historical records or new information from data mining techniques that has been processed for real-time analytics uses. In addition, it can come from a mix of internal systems and external data sources.
Process
Breaking Down Predictive, Prescriptive And Descriptive Analytics
The word ‘analytics’ in ‘predictive analytics’ is a bit of a misnomer. This is because predictive analytics is not considered as a branch of traditional analytics such as reporting or statistical analysis as often mistaken. Predictive analytics derives from finding predictive models which firms deploy to anticipate future business outcomes and/or consumer behaviour. It works by compounding and analysing data mining, statistics, artificial intelligence, machine learning and data modelling.
Descriptive analytics involves capturing things which occur and can be applied to any portion of the business landscape. Descriptive analytics is the foundation on which an algorithm may be developed. Although these metrics are simple and not particularly advanced, they are often too voluminous to manage without proper analytics tools.
Predictive analytics is typically used within dashboards and data reporting in organisations. Although sophisticated, these tools often lack the link between business decisions, process optimisation, customer experience or any other action for that matter. The model is unrivalled in producing insights, although, they are unable to produce explicit instructions on what to do with them. This is where prescriptive analytics is implemented to work alongside the predictive and descriptive analytics. Prescriptive analytics is where the developed insights meet their actions. Essentially, prescriptive analytics calculates the probability of an outcome and what can be done to trigger an influence in the direction which benefits the company; whether that be to make a sale more likely or contributing to the prevention of customer churn.
Our data modelling capabilities
Statistical Analysis & Visualisation
We cover the analytical spectrum - planning, data collection, analysis, reporting and deployment.
Predictive Modelling & Data Mining
Industry-leading model-building, automation and evaluative capabilities.
Decision Management & Deployment
Advanced model management and analytical decision management makes our analytics come to life.
Big Data Analytics
Gain predictive insights to build competitive business strategies.
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Use cases
Why Companies Are Using Data Models & Why You Should Too
Predictive analytics is allowing both SMEs and large organisations to become proactive and forward-looking through the anticipation of outcomes and behaviours, based on the collation of data. Prescriptive analytics can be taken one step further. Based on predictive analytics, prescriptive analytics conducts the optimal decision-making to provide suggestions for businesses to capitalise from their predictions or protect themselves from any arising implications. These tools help you gain a competitive advantage by discovering patterns in data and going beyond knowing what has happened, to anticipating what is likely to happen next.