Predictive analytics involves the use of statistics, large data, machine knowledge to gather historical information, prediction making, and modeling methods. The business sectors give much value to this method because of the advantages such as knowing the opportunities and possible losses. It can be used in various industries such as energy, insurance, and finance among many others.
What Predictive Analytics Is
Gartner, a consultancy agency, defines predictive analytics as a type of advanced analytics. It evaluates content or data to make it clearer what can happen in the future. Because of the large amount of information, data from various networks can be evaluated so that predictions can be made on how people will behave. This can also be used in different processes and businesses.
Predictive Analytics Process
- Defining the project
- Gathering of data
- Analysis of data
- Validating information
- Developing the predictive model
- Generating reports using the predictive model
- Checking the results if they are in line with the predictions made
The Advantages of Predictive Analytics
The main advantage of predictive analytics is it gives businesses and organizations a chance to learn from their experience through gathered data and apply the things they have learned in the future so that they have higher chances of succeeding. Here are more advantages of predictive analysis:
- Lessens the trouble of manually analyzing data, so errors are lessened
- Gives an edge in the industry because of the trends, challenges, and opportunities identified
- Better customer satisfaction
- Higher chances of success in product launches