Data Science Process | The Data Science Process: What a data scientist actually does

Data Science Process:

1. Business Understanding:

• The first step of this process is setting a research goal.
• The main purpose here is marking sure the entire user understand the what, how, and why of the project.
• In every serious project this will result in a project charter.

 

2. Data Understanding:

• The second phase is data retrieval.
• You want to have data available for analysis, so this step includes finding suitable data and getting access to the data form the data owner.
• The result is data in its raw form, which probably needs polishing and transformation before it becomes usable.

 

3.  Data Preparation:

• The data understanding phase starts with an initial data collection and proceeds with activities in order to get familiar with the data, to identify at quality problems.
• To discover first insights into the data, or to detect interesting subsets to form hypotheses for hidden information.

 

4. Modeling: 

• In this phase, various modeling techniques are selected and applied and their parameters are standardized to optimal values.
• Typically, there are several techniques for the same data mining problem type.
• Some techniques have specific requirements on the form of data. Therefore, it is often required to step back to the data preparation phase.

 

5. Evaluation:

• At this stage in the project, you have built a model that appears to have high quality, form a data analysis perspective.
• Before proceeding to final deployment of the model, it is important to evaluate the model thoroughly and review the steps executed to construct the model, to be certain it properly achieves the business objectives.

 

6. Deployment:

• The last step of the data science model is presenting your results and automating the analysis, if needed.
• One goal of a project is to change a process and/or make better decisions.
• You may still need to convince the business that your finding will indeed change the business process as expected.