Power of Data - Qualitative and Quantitative Data

Introduction to Decision Making with Data

  • Data plays a critical role in decision making.

  • Different types of questions require different types of data to answer.

Types of Data

Quantitative Data

  • Defined as objective measures of numerical facts.

  • Answers questions about what, how many, and how often.

    • Examples include measurable statistics, such as the number of commuters taking the train weekly.

  • Used by financial analysts to gain certainty and accuracy in reporting.

  • Visualization of quantitative data often includes charts and graphs.

Qualitative Data

  • Defined as subjective or explanatory measures of qualities and characteristics.

  • Helps answer "why" questions that cannot be measured numerically.

    • Example includes personal metrics such as hair color or preferences for products.

  • Provides context to the numerical data, enhancing understanding of trends.

Combining Quantitative and Qualitative Data

  • As a data analyst, you'll use both types of data depending on the business task.

  • Customer reviews serve as a prime example of how both types can be complementary.

    • Reviews provide quantitative data on ratings and qualitative insights on customer sentiment.

Case Study: Ice Cream Shop

Problem Identification

  • Local ice cream shop notices a decline in online ratings and an increase in negative reviews.

Step 1: Quantitative Analysis

  • Owner analyzes measurable questions:

    • How many negative reviews are there?

    • What’s the average rating?

    • How many reviews mention the same keywords?

  • This analysis confirms customer dissatisfaction and provides numerical clarity.

Step 2: Qualitative Analysis

  • Owner shifts to qualitative questions:

    • Why are customers unsatisfied?

    • How can improvement be achieved?

  • Patterns found in reviews, such as repeated use of the word "frustrated," spark deeper investigation.

Findings and Business Decisions

  • Discovering customers feel frustrated because of out-of-stock popular flavors.

  • Decision to adjust weekly orders based on customer demand.

Conclusion

  • Utilizing both quantitative and qualitative data allows effective response to customer dissatisfaction.

  • Understanding the nuances of both data types is crucial for data detectives.

  • Future discussions will explore creative data representation methods, such as interactive dashboards.