In every fraction of a second data is generated .Every Smart phone , every sensor ,every banking transaction is producing lot of data .
This information is very useful for for business. On Analyzing this data various business decisions can be made.
Predictive Analytics is a process of using historical data and produce a mathematical model over it to predict future events .
With the increase in Big Data Technologies Predictive analytics has received a lot of attention recently.
Stages of Predictive Analytics
01 Problem definition
What exactly needs to be achieved in the end is defined in this phase .
02 Data Collection
Based on the problem statement data is collected from various sources .It could be database , excel sheets etc depends upon the source of data generation.
03 Data Cleaning
Data which is collected in data collection phase may not be in structured format . For example review comments of a book or a movie . These kind of data just text statements. These statements are processed using Artificial Intelligence . On structured data mathematical model can be applied .
04 Data Analysis
Once data is in place , data analyst Investigate it . The investigation reveal trends of events , behavior of customers ,like and dislike of products or services etc . This initial level of information interpretation can be made at this stage .
05 Predictive Modeling
In this phase some statistical methods are applied on analysed data . Open source programming languages like Python and R are usually used .
The out come of this phase are the rule set which can be applicable to live data.
06 Deployment
Once the Model is created it is integrated live data or daily routines data .
07 Monitoring
Post deployment model can be validated for a certain period . Models are tested and enhanced periodically and to reach required level of accuracy
