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Step 3: Then she moved on to the process step. Here a data analyst is trying to understand their target audience. After that, Maria collected data on the different advertising methods … to determine which was the most popular one with the company’s target audience. Step 2: Next step was the prepare phase, Maria collected data for the upcoming analysis process.įirst she needed to better understand the company’s target audience, i.e., people with video game systems. So the problem is how to determine the best advertising method for its target audience. Step 1: Maria begins by defining the problem that needed to be solved–via collaboration with stakeholders and understanding their needs.Īnywhere Gaming Repair wants to figure out how to bring in new customers. The business owner ask a data analyst, Maria, to make a recommendation. regarding a) suitable media (so, who is the target audience and what media does it use?), and 2) the advertising budget (how much different advertising methods will cost). He knew advertising as a proven way to get more customers, but he wasn’t sure where to start”–esp. “The owner wanted to expand his business. Data in action (the data analysis process)Ī short data analytics case study shows how the six phases of data analysis can be applied to effective problem solving of real world problems: “Anywhere Gaming Repair” is a small business service provider that comes to you to fix your broken video game systems or accessories. Problem solving begins with asking effective questions.įrom issue to action: The six data analysis phases are Ask, Prepare, Process, Analyze, Share, and Act.ġ.2.1. Problem solving and effective questioning

Describe the key ideas associated with structured thinking including the problem domain, scope of work, and contextġ.1.

Explain the data analysis process, making specific reference to the ask, prepare, process, analyze, share, and act phases.

Explain how each step of the problem-solving roadmap contributes to common analysis scenarios.

Discuss the common types of problems addressed by a data analyst.

Explain the characteristics of effective questions with reference to the SMART framework.

You will also learn about effective questioning techniques that can help guide your analysis. In this part of the course, you’ll check out some common analysis problems and how analysts solve them. To do the job of a data analyst, you need to ask questions and problem-solve. This course begins by talking about problem solving and some of the common types of business problems that data analysts help solve. You may also be interested in Google Data Analytics Professional Certificate Course 1: Foundations – Cliffs Notes.

Week 4: Always remember the stakeholder.Coursera Google Data Analytics Professional Certificate Course 2 – Ask Questions to Make Data-Driven Decisions quiz answers to all weekly questions (weeks 1 – 4):

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