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Last updated on 3/15/23

Get Ready to Navigate the Data-Driven World

Evaluated skills

  • Get Ready to Navigate the Data-Driven World

  • Question 1

    How do you move from data to action?

    • Data → Context → Information → Action

    • Data → Information → Insight → Action

    • Data → Insight → Information → Action

    • Data → Observation → Insight → Action

  • Question 2

    Scenario 1:

    Remember Zara and her wellness quest? Now she wants data on her sleep patterns. Fortunately, her fitness tracker can track the amount of time she spends in bed, and the amount of time she is asleep each night.

    A picture shows a smartphone screen with a sleep tracker app open. The tracker dashboard shows sleep patterns for one day, including time spent in bed (8:30 hours) and time asleep (6:00 hours).

    You add this information to the data pipeline as part of the project plan. Now draw the new data pipeline and then answer the following questions.

    What will the left part of the new data pipeline look like?

    • A picture shows a data pipeline for Zara. The first data source is the fitness tracker app on Zara’s phone. The raw data issued from it are the number of steps and the resting heart rate. The second data source is the health log spreadsheet on Zara’s computer. Raw data issued from it are Zara’s symptoms, the days she cycled and her mood. The third data source is the sleep tracker app on Zara’s phone. Raw data issued from it are the amount of time spent in bed and the amount of time asleep. The operations step for all the seven raw data items is “combine”.

    • A picture shows a data pipeline for Zara. The first data source is the fitness tracker app on Zara’s phone. The raw data issued from it are the number of steps and the resting heart rate. The second data source is the health log spreadsheet on Zara’s computer. Raw data issued from it are Zara’s symptoms, the days she cycled, her mood, the amount of time spent in bed and the amount of time asleep. The operations step for all the seven raw data items is “combine”.

    • A picture shows a data pipeline for Zara. The first data source is the fitness tracker app on Zara’s phone. The raw data issued from it are the number of steps, resting heart rate, the amount of time spent in bed and the amount of time asleep. The second data source is the health log spreadsheet on Zara’s computer. Raw data issued from it are Zara’s symptoms, the days she cycled and her mood. The operations step for all the seven raw data items is “combine”.

    • A picture shows a data pipeline for Zara. The first data source is the fitness tracker app on Zara’s phone. The raw data issued from it are the number of steps and resting heart rate. The second data source is the health log spreadsheet on Zara’s computer. Raw data issued from it are Zara’s symptoms, the days she cycled and her mood. The operations step for all the five raw data items is “combine”. The resulting information from this operation is: the amount of time spent in bed and the amount of time asleep.

  • Question 3

    What might Zara do with the new data pipeline once the sleep data is added?

    Careful, there are several correct answers.

    • Look for ways to improve her sleeping environment so she sleeps better.

    • Combine her sleep pattern data with her symptom data to see if there is a link between her sleep patterns and general health.

    • Combine her sleep pattern data with her yoga practice to see if yoga will help her sleep better.

    • Combine her sleep pattern data with her cycling data to see if she cycles further when she gets more sleep.

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