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1. Learn more about the Ask phase of the process in the Ask Questions to Make Data-Driven Decisions course.
2. Learn more about the Prepare phase of the process in the Prepare Data for Exploration course.
3. Learn more about the Process phase of the process in the Process Data from Dirty to Clean course.
4. Learn more about the Analyze phase of the process in the Analyze Data to Answer Questions and Data Analysis with R Programming courses.
5. Learn more about the Share phase of the process in the Share Data Through the Art of Visualization and Data Analysis with R Programming courses.
6. Learn more about the Act phase of the process in the Google Data Analytics Capstone: Complete a Case Study course.

Note: The course links are for you to preview and not complete the courses at this time. You may mark this activity as complete after you understand how the courses align to the data analysis process.

By now, you have started to think about data in your daily life and how you use this data to make decisions. Earlier in this course, you completed a learning log where you recorded some data from your daily life. Next, you will consider how to organize this data. In this activity, you’ll write an entry in your learning log to track your thinking and reflections about how to organize data. By the time you complete your entry, you will understand how to create and format a table to store the data that you collect. Tables are one of the most common ways data is organized for analysis. This foundational skill will help you more easily analyze data, and will serve as a go-to tool in your data analyst’s toolkit.

To get started, consider the data you have collected in your learning log entries so far in this course. Now, take a moment and prepare to organize this data. One of the simplest ways to add structure to your data is to put it in a table.

To record your data in a table, you need to understand how a table is structured:

• A table consists of rows and columns
• Each row is a different observation
• Each column is a different attribute of that observation

For example, here is a collection of observations in a learning log about how many cups of coffee are consumed each day:

1. 10/19, 2.5 cups of coffee
2. 10/20, 2 cups of coffee
3. 10/21, 1 cup of coffee
4. 10/22, 1.5 cups of coffee
5. 10/23, 1.5 cups of coffee

There are five data points. Each piece of data consists of a date and the number of cups of coffee consumed that day. You can structure this as a table with six rows and two columns. This includes five rows of data and one header row with titles:

Date	Cups of Coffee / Day
10/19	2.5
10/20	2
10/21	1
10/22	1.5
10/23	1.5

You can also create a table with more detailed data. For instance, if your data also contained information about whether there was cream and sugar in the coffee, it might appear like this:

1. 10/19, 2.5 cups, cream, sugar
2. 10/20, 2 cups, no cream, no sugar
3. 10/21, 1 cup, cream, sugar
4. 10/22, 1.5 cups, cream, no sugar
5. 10/23 1.5 cups, cream, sugar

You can represent this by adding two more columns to your table, one titled “Cream” and one titled “Sugar.”

Date	Cups of Coffee / Day	Cream	Sugar
10/19	2.5	yes	yes
10/20	2	no	no
10/21	1	yes	yes
10/22	1.5	yes	no
10/23	1.5	yes	yes

You have been collecting data from the beginning of the course. Take a moment to consider the data you have gathered in your learning log. Now, determine how you could organize your data in a table.

Before you begin, you should decide what software you’d like to use to create your table. We suggest using Google Docs or Microsoft Word for this example; you will have a chance to use tables in spreadsheets later on. You will find detailed instructions on how to create tables when you access your learning log, below.

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: Organize your data in a table

OR

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

You’ve been learning about the six phases of the data analysis process: ask, prepare, process, analyze, share, and act. Based on what you’ve discovered, do you think data analysts find any one step more important than others? If so, which one? And why do you feel that way?

Please submit two or more paragraphs (150-200 words) in your written response. Then, visit the discussion forum to read what other learners have written, and choose two or more posts to comment on and discuss.

The data analysis process phases are ask, prepare, process, analyze, share, and act. What do data analysts do during the ask phase?

A. Create data visualizations

B. Clean the data

C. Define the problem to be solved

D. Collect and store data

The correct answer is C. Define the problem to be solved. Explain: During the ask phase, data analysts define the problem by looking at the current state and identifying how it’s different from the ideal state.

During the process phase of data analysis, a data analyst cleans data to ensure it’s complete and correct. True or False? A. True

B. False

It is true. Because the process phase is all about getting the details right, so data analysts clean data by fixing typos, inconsistencies, and missing or inaccurate data.

During which phase of data analysis would a data analyst use spreadsheets or query languages to transform data in order to draw conclusions?

A. Analyze

B. Prepare

C. Act

D. Process

The correct answer is A. Analyze. Explain: The analyze phase involves using data analytics tools such as spreadsheets and query languages to transform data in order to draw conclusions and make informed decisions.

In which data analysis phase would a data analyst use visuals such as charts or graphs to simplify complex data for better understanding?

A. Share

B. Prepare

C. Process

D. Act

The correct answer is A. Share. Explain: The share phase involves how results are interpreted and shared with others, often through data visualization.

A data analyst shares insights from their analysis during a formal presentation to stakeholders. In a slideshow, they make a data-driven recommendation for how to solve a business problem. What phase of the data analysis process would come next?

A. Ask

B. Process

C. Prepare

D. Act

The correct answer is D. Act. Explain: In this scenario, the data analyst has just shared insights. So, the next phase would be to act and put those insights to work in order to solve the business problem.