The lifecycle of a data science

Posted by Radhika Soni on January 12th, 2021

Data Science is a vast field, there’s lot more to explore in it. We offer best Data Science Courses with core knowledge to our students. Data science lifecycle consists of six different phases that are the discovery phase, data preparation phase, model planning phase, model building phase, operational phase, and result phase.

Phase 1- Discovery Phase

The phase includes the understanding of the problems, available time frame, resources, technology, manpower, and budget. The complex problem is understood and a model is designed to get a required result. A hypothesis is considered and different tools are being considered that should be efficient to provide a result. 

Phase 2- Data Preparation Phase

The phase includes the gathering of data and formulating it in a structured form. This includes data mining and data cleaning with the help of statistical tools like “R”. Once the data is formed and stored, it’s time to use different variables and perform ETLT process that is extracted, transform, load and transform.

Phase 3- Model Planning Phase

In this stage, different methods and techniques are used to create a relationship between different variables.  Exploratory data analytics is applied using statistical tools like statistical formulae and visualization tools. The most common tools being used are R, SQL, and SAS. We help to explore the needed insights with the help of Data Analytics and Data Science Courses, we provide.

Phase 4- Model Building Phase

Under this phase, a dataset is developed for testing purpose. This also includes an understanding of different tools being used and whether it will be sufficient to suffice the requirement of building a model. The tools used for model building are like WEKA, Matlab, Alpine Miner, Statistica, and others. We offer the best with the help of Data Science Trainin

Phase 5- Operational Phase

The operational phase includes the delivery of the final report that includes report briefing, code and technical documents. Even different projects are undertaken and models are run in order to get the desired results. For more practical exposure, Join Fusion Technology Solutions and get the finest learning in the field of data science.

Phase 6- Result Phase

 This is an important stage and needs to be evaluated properly to find if the desired result has been obtained or not. Under this stage, key findings are identified and communicated to the stakeholders. The stage determines the success and failure of the model built.

Overall, the ratio of success has improved in the recent scenario and the success rate of models built has increased owing to the presence of helpful building tools and others statistical methods, however, the success behind the model lies in the hand of a data scientist who plays a critical role in the process.

As due to this pandemic, people are not stepping out from their home, we also provide Online Data Science Courses and Certification.

Radhika Soni

About the Author

Radhika Soni
Joined: January 12th, 2021
Articles Posted: 1

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