Worksheet: A Beginners Guide To The Data Analysis Process

Comprehension worksheet generated from the video "A Beginners Guide To The Data Analysis Process".

A Step-By-Step Guide To The Data Analysis ProcessCareerFoundryhttps://www.youtube.com/watch?v=lgCNTuLBMK4
A Step-By-Step Guide To The Data Analysis Process

Vocabulary

  • Problem Statement — The objective of a data analysis process, defining the business problem to be solved.
  • First-party data — Data collected directly by an organization from its own customers.
  • Data Cleaning/Scrubbing — The process of preparing collected data for analysis by removing errors, duplicates, outliers, unwanted points, structuring it, and filling gaps.
  • Predictive Analysis — A type of data analysis that allows identifying future trends based on historical data.
  • Prescriptive Analysis — The most complex type of data analysis that allows making recommendations for the future.

Questions

Watch the video carefully and answer the following questions based on the information presented.
1.
In the video, Will discusses a fictional company, “Top-notch Learning,” that is excellent at securing new clients but has much lower repeat business. How did Will suggest reframing the initial question “Why are we losing customers?” to better define the problem?
2.
According to the video, what percentage of their time will a good data analyst spend on data cleaning, and why is this step so crucial?
3.
The video describes three categories of data: first-party, second-party, and third-party. What is the main benefit of using second-party data in your analysis?
4.
Which of the following data analysis categories focuses on understanding why something has happened?
  1. Descriptive Analysis
  2. Diagnostic Analysis
  3. Predictive Analysis
  4. Prescriptive Analysis
5.
In the final step of the data analysis process, “Sharing your results,” Will emphasizes the importance of honest communication. Explain why it is crucial to present all gathered evidence, highlight any gaps in the data, and flag insights that might be open to interpretation when sharing your findings with stakeholders.

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