Small businesses everywhere are also starting to take advantage of data driven insights to improve their operations and make better decisions.

"In analytics I feel like the key to success is being able to blend the personal side with the technical side." - Joey, Analytics program manager at REWS

Self-Reflection: Business use of data

Question 1

Previously, you learned that industries use data in all kinds of different ways. Now let's analyze the businesses you interact with day-to-day and reflect on how they use data to improve their customer experience.

Ways a business uses data

Pick a company, service, or product that you've had personal experience with that uses data to improve its customer service. Some examples are local restaurants, health care providers, internet providers, etc. Then, think of a specific customer experience problem this company, service or product might have that you suspect could be addressed with data. This could be something like a restaurant tracking sales of a new product, or internet service providers trying to figure out where outages are occurring. Try to avoid broad problems and think of specific issues. For example, the meal you ordered from a delivery service arrived cold.

In the text box below, write 1-3 sentences (20-60 words) on the company, service or product you chose and how they could use data to improve customer experience.

All sorts of industries can benefit from using data to solve business problems, including improving overall customer experience.

Question 2

Next, we’ll think about the type of data that needs to be collected and how the data will be used. In the example of the restaurant, let’s pretend the problem that will be solved is delivery food arriving cold to customers' homes. More data about the delivery process could help the restaurant streamline the process and deliver food on time.

In the text box below, write 1-3 sentences (20 to 60 words) reflecting on what types of data could be used to resolve the problem referenced in the question above.

Data analytics helps businesses make better decisions, but getting there is a process. It begins with an analysis of a business problem, identifies data that can provide insights about that problem, and then uses data analysis to arrive at an answer. Sometimes you get an answer that solves your business problem, but it’s often just as likely that you discover other questions to investigate further, with more data analysis.

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"For any analyst, for any person that's honestly at the early stages of their career, understanding data, respecting data and knowing how to work with data is incredibly important because, my vision is that every role in some form or fashion will involve data and its use in learning how to extract insights from it will be at the core of any critical role across any company organization." - Tony, Finance Program Manage at Google

Learning Log: Reflect on the data analysis process

Overview

By now, you have started getting familiar with the data analysis process. Now, you’ll complete an entry in your learning log reflecting on your experience with the data analysis process and your progress in this course. By the time you complete this activity, you will have a stronger understanding of how to use the steps of this process to organize data analysis tasks and solve big problems with data. This framework will continue to help guide you through your own work in this course--and as a junior data analyst!

The data analysis process so far

Take a moment to appreciate all the work you have done in this course. You identified a question to answer, and systematically worked your way through the data analysis process to answer that question—just like professional data analysts do every day!

In reviewing the data analysis process so far, you have already performed a lot of these steps. Here are some examples to think about before you begin writing your learning log entry:

• You asked an interesting question and defined a problem to solve through data analysis to answer that question.
• You thought deeply about what data you would need and how you would collect it in order to prepare for analysis.
• You processed your data by organizing and structuring it in a table and then moving it to a spreadsheet.
• You analyzed your data by inspecting and scanning it for patterns.
• You shared your first data visualization: a bar chart.
• Finally, after completing all the other steps, you acted: You reflected on your results, made decisions, and gained insight into your problem--even if that insight was that you didn't have enough data, or that there were no obvious patterns in your data.

As you progress through the rest of the program, you will continue using and revisiting these steps to help guide you through your own analysis tasks. You will also learn more about different tools that can help you along the way!

Access your learning log

To use the template for this course item, click the link below and select Use Template.

Link to learning log template: Reflect on the data analysis process

Reflection

In your learning log, write 2-3 sentences (40-60 words) reflecting on the data analysis process and your experiences so far by answering each of the questions below:

• Which part(s) of the data analysis process did you enjoy the most? What did you enjoy about it?
• Processing and Analyzing Data are the most enjoyable parts for me. These parts require more practical processes and actions. I like these things that I have to do myself.
• What were some of the key ideas you learned in this course?
• The key idea I learned in this course is that it is super important to ask good questions. It's like the alpha and omega in data analysis.
• Are there concepts or portions of the content that you would like to learn more about? If so, what are they? Which upcoming course do you think would teach you the most about this area?
• I would like to learn more about how to effectively visualize data.
• Now that you’ve gained experience doing data analysis, how do you feel about becoming a data analyst? Have your feelings changed since you began this course? If so, how?
• I became more interested in becoming a data analyst and felt that this field suited me well.

When you’ve finished your entry in the learning log template, make sure to save the document so your response is somewhere accessible. This will help you continue applying data analysis to your everyday life. You will also be able to track your progress and growth as a data analyst.

Roles of a data analyst

Multiple choice exercise

Which industry is it?

Select the industry that matches the example of how an analyst uses data.

• Use geographic data to power GPS technology in cars.
  • Technology relies on software and hardware to function.
• Use demographic data to target advertisements for a new consumer product for youths.
  • Marketing uses audience insights to make decisions.
• Use stock market data to determine which portfolios to invest in.
  • Finance relies on daily market trends for insight.
• Use bed occupancy data to determine the number of nurses and orderlies to schedule on a given shift.
  • Healthcare involves reviewing hospital traffic to inform staff decisions.
• Use past booking data to accurately anticipate levels of demand for hotel rooms.
  • Hospitality looks at seasonal trends to predict demand.
• Use population data to determine which communities need federal funding.
  • Government relies on demographic information in order to provide proper support.