Practical Quiz: Self-Reflection: Business use of data

Overview

Now that you have been introduced to the role of a data analyst, you can pause for a moment and think about what you are learning. In this self-reflection, you will consider your thoughts about how industries use data and respond to brief questions.

This self-reflection will help you develop insights into your own learning and prepare you to connect your knowledge of a data analyst’s responsibilities to real-world business scenarios. As you answer questions—and come up with questions of your own—you will consider concepts, practices, and principles to help refine your understanding and reinforce your learning. You’ve done the hard work, so make sure to get the most out of it: This reflection will help your knowledge stick!

How a business uses data

In this self-reflection, you’ll consider the businesses you interact with day-to-day and reflect on how they use data to improve their customer experience.

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, or your favorite smartphone app.

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 occur.

Try to avoid broad problems and think of specific issues. A good example of a problem would be that the meal you ordered from a delivery service arrived cold.

Reflection

Consider the company, service, or product you chose in this reflection:

• How could it use data to improve customer experience?
• What kinds of data would it need to collect?
• How could insights from that data solve a problem?

Now, write 2-3 sentences (40-60 words) in response to each of these questions. Type your response in the text box below.

Explain: Great work reinforcing your learning with a thoughtful self-reflection! A good reflection on this topic would consider how a specific kind of data can help a company, product, or service improve its customer service experience.

For example, consider a restaurant that delivers cold food to customers. More data about the delivery process, such as the average delivery time or the average number of daily deliveries, could help the restaurant streamline the process and deliver food on time.

Data analytics helps businesses make better decisions, but getting there is a process. It begins with analyzing a business problem, identifying data about that problem, and then using 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.

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

OR

If you don’t have a Google account, you can download the template directly from the attachment below.

Test your knowledge on data analyst roles

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.

Industry data example:

Use geographic data to power GPS technology in cars. -> Technology

Use demographic data to target advertisements for a new consumer product for youths. -> Marketing

Use stock market data to determine which portfolios to invest in. -> Finance

Use bed occupancy data to determine the number of nurses and orderlies to schedule on a given shift. -> Healthcare

Use past booking data to accurately anticipate levels of demand for hotel rooms. -> Hospitality

Use population data to determine which communities need federal funding. -> Government