**statistical analysis**,

**forecasting models**,

**Natural Language Processing**(NLP),

**text mining**, and

**Artificial Neural Networks**(ANNs). It allows users to

**predict**future possibilities and

**discover**hidden

**relationships**to make the most likely

**patterns**.*

Predictive analytics have the ability to anticipate risk and identify relationships that may not be apparent with descriptive analytics. Through **statistical modeling**, **data mining**, and other advanced techniques, predictive analytics can identify hidden relationships or patterns in huge volumes of data. This is integral to group or segment data into meaningful sets for detecting tends or predicting behavior.*

Organisation that are matured in descriptive analytics move into this level where they look beyond what happened and try to answer the question of βWhat will happen?β. Prediction essentially is the process of making **intelligent/scientific estimates** about the future values of some variables like customer demand, interest rates, stock market movements, etc. If what is being predicted is a categorical variable, the act of prediction is called **classification** otherwise it is called **regression**. If the predicted variable is time-dependent, then the prediction process is often called **time-series** forecasting.*

- What is likely to happen?
- What trends are foreseen?
- What are multiple alternatives and scenarios?*

The most common predictive analyzing techniques used are: **classification**, **clustering**, **regression**, **association analyzes**, **graph analyses**, and **decision tree**. These are advanced analytics that provide **self-learning models** that can be used in **real-time **applications and **forecasting**. The use of data, analytics, predictive modeling, **machine learning** help perform complex correlations on data to gain insights and are the future of organizations.*

**no longer confined to statisticians and mathematicians**. Corporate strategic planners utilize it significantly in their decision-making processes. The following are a few of the most common forecasting options:

- Fraud Detection
- Risk Mitigation
- Effectiveness of Marketing Campaigns
- Operational Enhancement
- Clinical Decision Making *