Ask Questions to Make Data-Driven Decisions - Module 2 challenge

Ask Questions to Make Data-Driven Decisions - Module 2 challenge

  1. A data professional at a retail store automates a process to identify their company’s best-selling products. First, a list of all products is compiled. Then, the number of times they have been sold is counted. Finally, the products are sorted, with best-sellers at the top. What does this scenario describe?

    • Data-inspired decision-making

    • Making a pivot table

    • Using a formula

    • Creating an algorithm

  2. Which of the following statements accurately describe qualitative and quantitative data? Select all that apply.

    • The smell of lavender is an example of qualitative data.

    • Quantitative data involves things that cannot be measured using numerical data.

    • The height of a suspension bridge is an example of quantitative data.

    • Qualitative data involves information that can be quantified.

  3. When working with big data, analysts consider the velocity of processing large, complex datasets. What does this entail?

    • Evaluating the quality and reliability of the data

    • Assessing the amount of data to be processed

    • Understanding how quickly the data can be processed

    • Identifying the different kinds of data available

  4. A data team uses a spreadsheet tool to create a visualization that summarizes financial data by region, facility, and time period. What tool are they using?

    • Data validation

    • Pivot table

    • Sort

    • Format

  5. Company decision-makers at a gas utility want to improve business performance. How could they use metrics and a metric goal to help them do so?

    • Establish a metric goal as a single data point. Then, quantify it with metrics.

    • Create a metric goal as the business objective. Then, evaluate it using metrics.

    • Set a metric as the business objective. Then, quantify it using numerous data points.

    • Develop a metric. Then, evaluate it to determine whether it advances performance.

  6. Which of the following statements correctly describe dashboards and reports? Select all that apply.

    • Reports and dashboards are both useful for data visualization.

    • A dashboard could be used to track hourly error rates when programming code.

    • Reports are effective at capturing high-level, historical data.

    • Dashboards are designed and distributed periodically as a reference.

  7. Fill in the blank: ROI is calculated by comparing the two metrics of _____, enabling a company to determine the success of the investment.

    • investment cost and profit

    • value and expenses

    • sales and revenue

    • gross margin and net margin

  8. What are some typical challenges that may be faced by businesses that are beginning to collect and use big data? Select all that apply.

    • There may be gaps in big data business tools

    • Less efficient decision-making time frames

    • Difficulty finding important data

    • Cannot help large organizations spot trends