Prior to beginning work on this discussion forum, review Chapter 6: Basic Statistical Concepts for Data Science in your course textbook.

Create:

Advancement in the computing technology field has led to widespread use of statistics in real-world applications. Excellent software programs are available for analyzing data. For the first part of this discussion forum, you are required to

• Identify a minimum of two data analysis tools currently available on the market. Some possible choices include: Tableau, SAS, Azure machine learning, and AWS machine learning.
• Pick one of these tools and draw a concept map that shows the following:
  • The different features of this tool
  • How data flows in that tool
  • How the tool fits with overall data analytics

For support on getting started with your concept map, review the Mind Mapping section of Overcoming Writer's BlockLinks to an external site. from the Writing Center. You may use Word or PowerPoint to build your own concept or mind map, or you may use a template tool as long as you can you can upload it to the Canvas classroom in the format of .docx, .pdf, .png, or .jpeg and the file size does not exceed 500MB. Some free options you may wish to consider when creating your map include

• Canva Mind Maps TemplatesLinks to an external site.,
• Canva Concept Maps TemplatesLinks to an external site.,
• Bubbl.us Mind Mapping ToolLinks to an external site. (Note: There is a limited number of mind maps that you can create with the free "Basic" account.), and
• Visme.co TemplatesLinks to an external site..

Write:

For the second part of this activity, you will discuss

• Compare the tool you picked for your concept map against another tool from the list you identified.
• Identify the parameters you used to compare the two tools.
• If you had to purchase one of the tools, which one you would you pick and why? Note: Your approach to this decision should be objective rather than subjective.

reference:

Sahay, A. (2021). Essentials of data science and analytics: Statistical tools, machine learning, and R-statistical software overview. Business Expert Press.