33. Data Analytics - Google Data Analytics Capstone Case Study - Week 1

 Definitions:

Case study // a common way for employers to assess job skills and gain insight into how you approach common data related challenges


Tips:

    - make sure the case study answers the question being asked

    - make sure that you're communicating the steps you've taken and the assumptions you've made about

        the data

    - the best portfolios are personal, unique, and simple

    - make sure that your portfolio is relevant and presentable


What to include in portfolio:

        - Biography // an intro to make audience want to know and meet you

        - Contact Page // all contact information for audience to contact

        - Resume // your resume

        - Accomplishments // career-worthly highlights, certificates, events attended, blogs posted

        - An image of you (optional)


What to include in a case study:

        - Introduction: 

                Make sure to state the purpose of the case study. 

                This includes what the scenario is and an explanation on how it relates to a real-world

                obstacle. Feel free to note any assumptions or theories you might have depending on the

                information provided. 

        - Problems: 

                You need to identify what the major problems are, explain how you have analyzed

                the problem, and present any facts you are using to support your findings.

        - Solutions: 

                Outline a solution that would alleviate the problem and have a few alternatives in mind to

                show that you have given the case study considerable thought. Don’t forget to include pros

                and cons for each solution.

        - Conclusion: 

                End your presentation by summarizing key takeaways of all of the problem-solving you

                conducted, highlighting what you have learned from this.

        - Next steps: 

                Choose the best solution and propose recommendations for the client or business to take.

                Explain why you made your choice and how this will affect the scenario in a positive way.

                Be specific and include what needs to be done, who should enforce it, and when.


Skills to add to resume:

        - Database queries:

                Perform SQL queries

                Sort/filter data using SQL queries

                Convert data types using SQL functions

        - Data Visualization:

                Create data visualization using Tableau

                Create visuals in spreadsheets

                Create presentations from data analysis results

        - Dashboards:

                Identify data needs of users

                Create dashboards using Tableau

                Use design thinking to improve dashboards

        - Reports

                Create data cleaning reports

                Create and maintain change logs

                Create reports in R Markdown

        - Spreadsheets:

                Clean data in spreadsheets

                Sort and filter data in spreadsheets

                Create pivot tables in spreadsheets

        - Programming:

                Install and use tidyverse package in R

                Run scripts in RStudio

                Create data visualizations in RStudio


Additional Resources:

https://www.holistics.io/blog/startup-data-analyst-interview-case-studies/

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