on 06 December 18
For a while now, predictive analytics has been popular with enterprises and it helps them improve their ROI. Predictive Analysis helps businesses flourish, by giving insights into the understanding of trends and the need of the hour. With predictive analytics' by their side, businesses have been able to enhance user experience, and build better products and improve their services.
With entry of Big Data, Predictive analytics is now the rage of the hour. With big data, the data has not only evolved, but has also come out with a lot of hidden characteristics earlier unknown. The question is How Big Data and Predictive Analytics work in unison? One collects the data, and mines them, while the other analyzes the data and helps the enterprises build their future outlook towards their business needs. The large volumes of data is easily processed by big data, while predictive analytics involves modeling, machine learning and data mining to help forecast the future trends. The risk and opportunities are best predicted by these analytics.
Predictive Analytics Models
There are total six models popularly used for predictive analytics'. Let's understand these models, and the techniques they use.
- Linear Model: Linear model or regression technique is the most popular method used for predictive analytics'. This model helps in understanding the relationship that exists between two or more than two independent variables in the business
- Generalized Additive Model: This model does not confirm to the stated assumptions, and is more of a non-parametric regression model
- Logistic Regression Model: In this model the dependent variable is categorical. A relationship between the categorical variable and the response measures is made by predicting a probability that the case belongs to target class
- Survival Analysis Model: This is a survival analysis using a group of techniques where the time duration is modeled till the time one or more events occur and end
- Decision Tree Model: Here the output is a list of rules, which is used to segment the population base into smaller groups for analytics
- Bayesian Method: This is a predictive analysis method which has been developed on Ba'es' method. It is a conditional model which depends on the relationships between the different events
Why Indulge in Predictive Analysis?
Predictive analysis is important for enterprises, and here's why
Technology has grown by leaps and bounds, and you will see a lot of technology trends gaining popularity and acceptance. In fact, technology is now available at a low cost. So, how is predictive analytics' related to technology? Simple, you need high computing powers and better technology environment to run your predictive model. To build efficiency in your predictive model, you need the support of technology.
Predictive analysis has improved and enhanced business intelligence, which has in turn helps businesses derive benefits from the data. Companies are future ready, and flexible with the better business intelligence
Simple and Easy to Use
Predictive analysis is simple and easy to use. It helps improve the operations and future trends for the enterprises.
Big data enabled predictive analytics is the future for the enterprises. It not only helps in mining the data, but also in forecasting the future of the enterprises. Semaphore Software offers big data solutions to match your enterprise needs. Get in touch with us to know more about our services.
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