The Lifecycle of Data Science

The Lifecycle of Data Science

The major steps in the life cycle of Data Science project are as follows

Problem identification

Problem identification

Domain experts and Data Scientists are the key persons in the problem identification of problem

Business Understanding

Business Understanding

Understanding what customer exactly wants from the business perspective is nothing but Business Understanding

Collecting Data

Collecting Data

Data Collection is the important step as it forms the important base to achieve targeted business goals.

Pre-processing data

Pre-processing data

All these data are extracted and converted into single format and then processed.

Analyzing data

Analyzing data

This understanding comes from analysis of data using various statistical tools available.

Data Modelling

Data Modelling

Data modelling is the important next step once the data is analysed and visualized.

Model Evaluation

Model Evaluation

There may be changes in data while model is being evaluated or tested and the output will drastically change depending on changes in data

Driving insights

Driving insights

The model is used to get the insights which aid in strategic decisions related to business.

Taking a decision based on insigh

Taking a decision based on insigh

When the steps are followed properly then the reports generated in above step helps in taking key decisions for the organization.

Model Deployment

Model Deployment

Once the model is trained with the actual data and parameters are fine tuned then model is deployed.

VISTA ACADEMY

VISTA ACADEMY

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