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Post by excelrmalaysia on Jul 13, 2019 8:15:05 GMT
What is the lifecycle of data science?
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Post by excelr43 on Jul 13, 2019 8:19:46 GMT
Phase1- Discovery- before starting any project, it is crucial to learn more about the priorities, specifications, required budget and other types of requirements. You need to be certain about the questions you ask and use all the available resources like people, technology, data and time in a very optimum way. This phase also includes framing of the business problem and formulating the initial hypothesis to test. Phase2- Data preparation- This is the phase wherein an analytic sandbox is required to perform analytics for the project and to get the available data into the sandbox, ETLT (extract, transform, load and transform) is performed. Phase3- Model planning- This phase is where all the techniques and methods are used so that relationships can be drawn between variables and this will set a base for all the algorithms to be implemented in the upcoming phase. R, SQL analysis services, SAL/ACCESS are some of the tools used for model planning. Phase4-Model building- Datasets will be developed in this phase for the purpose of training and testing. Here whether the tools will be able to run the models or will require an environment which is more robust will be kept under consideration. Numerous techniques for learning, classification, clustering and association will be analyzed. Phase5-Operationalise- Technical documents, final reports, codes and briefings will be delivered and, also a pilot project will get implemented in a production environment which will be real-time. Phase6- Communicate results- If the goal has been achieved, it is extremely important to evaluate all the planning done in phase 1. This last phase is for identifying the key findings and interacting with the stakeholders to determine whether the criteria decided in the first phase has been successful or has failed.
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marketer19
New Member
https://www.excelr.com/data-science-course-training-in-bangalore
Posts: 10
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Post by marketer19 on Jul 13, 2019 11:09:59 GMT
In the past decade or so no other technology has created the buzz that Data Science has managed to do. Data Science has grown leaps and bounds and now everybody wants a piece of the Data Science pie. With Data Science techniques, companies and business organizations are starting to explore those new paths are often overlooked. High Demand for Data Scientists Almost half of the world’s population will be online by the end of 2019 and this will lead to the amassing of staggering amounts of data. This invariably increases the job opportunities for Data Scientists closing the gap between the demand and supply. If you are still skeptical about choosing Data Science as your career line, its time that you capitalize on this thriving field of technology. www.excelr.com/data-science-course-training-in-hyderabad/
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