Predictive analysis uses data evaluation, Artificial Intelligence, machine learning and statistical models to find patterns that represent trends that help to outline future scenarios, also identifying risks and opportunities.
Based solely on information (we cannot forget that the world is increasingly dependent on data), a company can know the best time of year to launch a product and the marketing strategy that will appeal most to the public. In this content, you will understand what predictive analysis is and how it will help your company achieve the best results.
Summary:
What is predictive data analysis?
After all, how is predictive data analysis done?
What is the relationship between big data and predictive analytics?
How does predictive financial analysis work?
Key Benefits of Predictive Analytics
What is predictive data analysis?
It is a process by which data is used to estimate future outcomes. It works like this: technologies such as AI, machine learning, and statistical models are used to find patterns in databases. Its application is broad. Segments such as commerce, energy, finance, insurance, and cybersecurity, among other examples , can benefit from this model.
Let's look at a classic case: until recently, it was difficult for meteorologists to accurately predict the weather. Nowadays, these predictions are increasingly accurate, allowing people to plan ahead before leaving home.
As the analytical programs used in the area interpret meteorological trends, evaluating variables such as the arrival of cold fronts, among others, meteorologists can predict, with considerable accuracy, even the amount of rain that will fall in a location or region.
Another area that benefits greatly is insurance. Predictive analytics helps detect fraud or risks of taking out insurance for a specific customer profile or product. This undoubtedly helps establish the final price of the insurance and approve or reject a customer.
Marketing is another sector that achieves excellent results with predictive data analysis. By showing trends, it offers insights that allow us to understand the flow of sales of a product, the results of a campaign or even consumer behavior.
After all, how is predictive data analysis done?
Predictive data analysis is based on the evaluation of a large volume of information to predict scenarios. This analysis is possible through the creation of a predictive model.
This model is based on algorithms that point out patterns. With the help of complex mathematical calculations and statistics, the predictive model predicts possible scenarios. It is important to highlight that even in this model, all precautions are taken with regard to data privacy .
This allows companies to prepare for future russian phone numbers challenges or increased demand for a particular product or service.
What is the relationship between big data and predictive analytics?
Big data is the area that studies how to process and analyze a large volume of data. This data serves as input for the analyses that will be performed by the predictive model.
The more sanitized this data is, the more accurate predictive analysis can be in predicting scenarios and trends, as it is working based on quality information and not just quantity.
That's why it's so important to take care of the database. The success of predictive analysis will only be possible if the database meets at least three conditions:
Be varied: the database must contain varied information to allow for deeper analysis;
Stay up to date: there is no point in maintaining a large database if the information is out of date, has gaps or is unreliable;
Allow easy access: for good predictive analysis, data must be easily accessed and processed so as not to compromise the timing of any action.