The world is constantly changing and is reflect in various sectors and business areas. Organisations, in addition to dynamic reports and dashboards, that present business information about what has happened or is happening, need data to help decision-makers choose the right path, to recommend actions and show the probabilities associated with each choice.
For faster and better decisions, companies are increasingly turning to sophisticated analytical methods, using predictive analytics and artificial intelligence techniques to model any event and obtain future estimates.
Big Data is a tool that helps companies obtain information that can be use to optimise decision making. All types of data analysis help to make a complete reading of the market.
However, this practice depends on the ability of analysis, as simple data collection is insufficient. By translate them into useful information, which can be adopt in your business, you need to know how to interpret them.
Each of the types of data analysis serves a specific purpose.
Predictive data analytics are the most used because it allows companies to understand some of the metrics they are working. It indicates consumer demographics and allows your company to generate market intelligence and know what product a customer is looking. Companies like Netflix use it to understand exactly what types of shows to recommend to their subscribers. With Big Data and Machine Learning, the streaming site can understand behaviours and find the most suitable series or movies for the customer.
On the other hand, prescriptive analysis is useful to verify the efficiency of processes. This type of analysis is used by companies like Google to understand which websites displayed in the search are relevant to users and to correct the results presented for the right keywords.
Descriptive reviews are done all the time and adopted by credit card companies when someone use features like emergency assessment. In this type of situation, the customer contracts the service that increases his limit if a purchase goes beyond it, according to his consumption profile and the assiduity with which he makes payments. The descriptive analysis is so accurate that it provides an instant response to this demand and approves (or not) a payment and the release of extra credit.
Diagnostic analyses assess the dimension of an action carried out by the business. It helps to compare metrics such as marketing and sales, and relating both to understand their effects.
Another great advantage of automating is free time for employees to focus on activities with high added value. Extracting, transforming and loading data takes many hours, a very repetitive process that require large investment of personnel.
All types of data analysis have a role within organisations. Each of them meets a particular need, guides managers in a direction, and is apply to a particularly context. The help of a data scientist is essential to establish the best analysis system in each case, and hiring this professional is strategic for businesses to be more successful with the information they have.
Data is a company asset and, as an asset, its management and profitability are today a differentiating factor.
Value creation is the essential basis for sustaining a profitable and lasting business. It's what sets apart from the competition, secures long-term customers and gives a brand and solution meaning. Without this, what is offered ends up being more of the same in the eyes of the market.