What is predictive analytics? …and 5 main types of data analysis.

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What is predictive analytics? What are the five types of predictive analytics? What are the applications of predictive analytics in different industries? Why are more and more companies deciding to use predictive analytics? Is this practice of analyzing data necessary for decision-making and strategy formulation? Read the article and learn more about the current ways to predict trends and future events.

Predictive analysis – index:
What is predictive analytics?
5 Main Types of Data Analysis
Examples of application of predictive analysis
Benefits of predictive analytics
What is predictive analytics?
Predictive analytics is also known as advanced analytics and is used to predict what will happen next. All predictive analytics research is based on historical data sets that have already been collected, although the type of benin whatsapp number database used can vary. Nowadays, it is no longer possible to process all the information collected using traditional techniques (such as databases). Data sets are huge and often unstructured. All the hidden patterns we seek are no longer visible at first glance and advanced and complicated techniques need to be used.

People are constantly producing data, Big Data is becoming even bigger, and with this growth, analysis techniques are becoming increasingly sophisticated. Still, to produce meaningful results, increasing the power of computers is crucial. Here, it is worth remembering that the concept of predictive analytics has been around for several decades and has only recently been able to demonstrate its usability.

Why not before? It’s all due to the technological advancement of our societies – we have faster and cheaper computers, easier-to-use software, and finally the ability to collect large volumes of data. Previously, predictive analytics was a domain of interest for statisticians, mathematicians, and scientists, while today business analysts or other specialists can successfully use predictive analytics.

5 Main Types of Data Analysis
We already know what predictive analytics is, but what types of analytics are there? There are five types of analytics that can be used by your business; all of the methods are tightly linked by several detailed techniques and are generally seen as steps in predictive analytics. The five types of analytics include:

Descriptive Analytics – the most common and widely used type of analytics, which analyzes data that arrives in real time, information extracted from social networks and websites. Financial and sales reports are the best-known examples of descriptive analytics.

Diagnostic Analysis – the second most well-known type of analysis, which deals with reasons or factors that affect different occurrences in business.

Predictive Analytics – This type of analytics deals with predictions, where the analyst tries to predict what might happen next based on all the previous patterns or trends.

Prescriptive Analytics – This is an additional step after the other types of analytics, which helps create prescriptions to solve problems using data derived from the results of other types of analytics. One example of prescriptive analytics is the Google Maps app, which is able to help choose the best route based on data related to: distance, traffic and speed.

Cognitive Analytics – combines several different forms of analytics, such as: semantics, artificial intelligence, machine learning algorithms, deep learning models, all of which allow a cognitive application of the software used to improve over time. To derive any conclusions, large sets of structured and unstructured data are being analyzed.

what is predictive analytics
Examples of application of predictive analysis
Predictive analytics is used by high-value industries where risk assessment and prevention of unexpected events are crucial. There are many industries that use predictive analytics methods and it is not possible to list them all, as the field is developing rapidly. Industries worth mentioning include:

Automotive – autonomous vehicles or vehicles with driver assistance technology apply predictive analytics to create better driver assistance algorithms.

Financial services – all types of analytics are used to predict credit risks or future cash flows. All types of financial factors can be forecasted, such as sales, revenues or expenses. Historical data from all financial statements can be used for projections. Here, quantitative tools and machine learning techniques are being used.

Energy Industry – Energy production requires a high level of monitoring of different types of data, such as: weather conditions, seasonal changes, plant availability, energy demand and consumption, all to predict the price and consumption of electricity.

Manufacturing – In industries such as aviation or machine manufacturing, predictions are being made about failures that may occur in machine parts or aircraft engines. The analysis aims to predict the health of machine elements, helping to reduce the cost and time of maintenance and repair. Malfunctions must also be prevented to avoid harmful, risky and dangerous situations. Damage caused by faulty devices can cost millions in repairs, in addition to legal fees in the event of lawsuits and safety claims.

Medicine and healthcare – Highly technical medical devices use all sorts of algorithms at different stages of diagnostic procedures. The healthcare industry invests millions in smart wearable devices that can be worn by patients to collect medical data – all devices use some sort of predictive analytics algorithms to detect and predict bodily reactions, their intensity and the possible need for medication injection.