Well, in view words, data analytics is communication between meaningful patterns of data. It is mainly applicable in an area where rich sources of data are available. The performance of analytics depends upon the statistics, computer programming and operation of research. Analytics always prefer data visualization to communicate insight.
Numerous firms apply data Analytics to improve the performance of their business. They describe and predict their business requirements from the available data of their business. In the operation like prediction analysis or enterprise decision making, the analytics is highly used. A large number of data is required for analytics, so the extensive computation is required. In computer science, the algorithms and software are recent methods to perform the analytics.
In short, data analytics is a purely scientific method which is used to transform data into insight for better decision making. The main objective of analytics to make better business decisions to improve the outcome of the business.
It is very difficult to create. To design it business intelligence architecture is created which offers a flexible and multi-faceted analytical ecosystem. There are four different types of data analytics available, let’s understand them clearly.
Four Types of Data Analytics
#1. Predictive Analytics
Predictive analytics has very simple responsibility of converting data into valuable action. This analytics use the data to determine the probable outcome of a situation which might occur in the future. In predictive analytics, a variety of different tools are available to perform the function such as modeling, machine, learning, data mining and game theory which analyzes the current and historical facts to predict about the future event.
There are three basic rules of predictive analytics;
- Predictive modeling
- Decision analysis and optimization
- Transaction profiling
#2. Descriptive Analytics
Descriptive analytics studies the past data to predict the future of an event. It analyses the past performance and by undertaking the past figure map out the cause of future success and failure. This type of report is used in different business operations such as sales, marketing, operations, and finance.
Descriptive analytics can be implemented in the group of data or different classified customers. Predictive analytics only focus on the one behavior of customers, whereas descriptive analytics focus on different relationships between the customer and the product.
#3. Prescriptive Analytics
Prescriptive Analytics tackles the data like big data, mathematical science, machine learning, and business rules to predict the future and suggest decision after analysis different type of data. The role of prescriptive data goes beyond predicting future outcomes. It tells the impact of the decision in the due course of the future. This analytics don’t only focus on what and when will happen, it also tells why will happen.
Moreover, prescriptive analytics show the path to take benefit from the decision by eliminating the risk factor.
#4. Diagnostic Analytics
In this data analytics, historical data is preferred over the current data to answer any question. Diagnostic Analytics try to find dependency and pattern in the historical data of the particular problem.
For example, companies use this data analytics to understand the root of a problem and find a solution accordingly. It is very helpful in keeping detailed information about their disposal.
Okay, so we hope that now you have totally get the data analytics and its different types. So, next when you have to analyze lots of data, use the analytics freely without any doubts.