Welcome

Hi

Welcome to my new blog on "Data Excursions".

With explosive growth of data in the world, Data Science is playing an incredible role to help extract knowledge from this huge resource. It is fast becoming a main stream driver for the fourth Industrial revolution. No wonder data is aptly being captioned as The New Oil.

The field of Data Science is vast and can be challenging , fun and enjoyable. On the contrary, for the uninitiated it soon becomes intimidating and frustrating if not taken up in proper steps in the right direction. This blog is an effort to help navigate this vast field with tidbits of information which I hope helps the seeker to attain his goals.

I welcome you again to this exciting new journey.......

Regards

Manne Someswara Rao

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Data Science life cycle process

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A typical data science life cycle process involves: 1) Business Understanding 2) Data Acquisition and Understanding 3) Modeling 4) Deployment 5) Customer Acceptance A typical interaction diagram is presented below from Azure Studio documentation . Business understanding is the first phase and is crucial to understand what is the problem we are trying to solve. This involves understanding stakeholder expectations, understand the data requirements to address the needs, sourcing the data (internal as well as external) and formulating the business goal to be achieved. In the Data acquisition and understanding phase we concentrate on getting the data and this involves interaction with other application teams and external sources. This involves interaction with the ETL team to acquire, clean, transform and analyze the data (including visualization techniques). The modeling phase is the one where a Data Scientist or a machine learning engineer typically work on their own. Fe
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