Data Science and Machine Learning [#4] – Data Science Summary Table

In this post, I will show you a summary table that answers the most important points when you need to analyze data (when, why, what, where and who).

Before entering in the field of data science, there are some tools and concepts that you need to know and have organized in your mind to guide your work in the right direction. The following table summarizes the different concepts mentioned in the previous posts and the tools/software that can be used to process the data.

The information is divided into five columns, each detailing different stages of the process of solving tasks working with traditional data, big data, doing business intelligence, applying traditional data science techniques and using unconventional machine learning techniques.

The columns are divided by rows that contain the answers to the following questions. When is this part of the process applied? Why do we need it? What are the techniques related to this activity? Where or in which real-life cases can it be applied? and how is it implemented it using what tools?

This summary table can assist in data processing, with a quick summary of the concepts and tools possible to use.

Bibliography

[1] Udemy – The Data Science Course 2020: Complete Data Science Bootcamp – 365 Careers

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Bruno Silva

Author: Bruno Silva

Portuguese Electrical Engineer with special interest in Data Science, Robotics, Automation and Embedded Systems. With a Master’s degree in Electrical and Computer Engineering in the field of Energy and Automation.

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