What are the 4 steps in Predictive Analysis

The Predictive Analytics has been very systematically designed for use. First, one should be aware of why is Predictive Analytics required and then the following processes are carried out. Let’s go through the 4 steps one by one.

1  Problem Definition (Opportunity Identification)

The first step is to decide for what purpose is the predictive analysis going to be used. Its use should have an impact on a strong level.

2  Data Collection

It may seem as a very simple process but it is the input point to the entire analysis process and hence a critical one. There can be cases with missing data, incorrect data, unreliable data and so on. After the data are collected, the missing data needs to be handled.

Here comes the concept of Data Imputation. Data Imputation is the process of filling the missing data. But it is effective only if the missing data is less than 10%. Another important task in data preparation is Data Featuring.  Data Featuring is about deriving new features or variables from existing set of data to generate new meaningful data. Interaction variables is about the Product and Ratio is about the division of two variables.  These variables can provide a better insight to the data prediction.

The prepared data is divided into Training data and Testing data. Normally, Training data is about 70% of the total data and Testing data is about 30% of the data. We use the training data to test the model performance before deploying the model.

3   Model Development

There are several models to be used in predictive analysis. Several models will be developed and the best fit model is selected. Techniques like Association Rule mining, Collaborative Filtering Techniques like cosine similarity or Jaccard coefficient or the like.

The main objective of this stage is to select a model to be deployed on the data.

4  Communication of Result

The results of the model is to be communicated to the top management using dashboards and scorecards. Generally, the findings and inferences are represented visually via graphs, charts and pictures.