ou’ve successfully navigated the foundational data management courses (like C752 or C793), but now C797 demands a higher level of critical thinking—transforming raw data into actionable business insights through professional-grade visualizations. This task is notoriously tricky because it’s not just about making charts; it’s about justifying every visual element against a specific business problem.
This guide gives you the exact framework to pass on your first submission.
What’s Inside (Task 1 Breakdown):
Part A: Business Question & Data Selection – Learn how to choose the right dataset (from WGU’s provided sources or approved external ones) and craft a measurable, analytical question that Tableau, Power BI, R (ggplot2), or Python (Matplotlib/Seaborn) can answer.
Part B: Data Preparation & Wrangling – Step-by-step instructions for cleaning missing values, handling outliers, and reshaping data using R dplyr or Python pandas. Includes code snippets for common transformations.
Part C: Static vs. Interactive Visualizations – How to build two distinct visualizations:
Static: Perfect for a report (e.g., correlation heatmap, bar chart with error bars).
Interactive: A dynamic dashboard with tooltips, filters, or a parameter-controlled view (Tableau focus).
Part D: Justification & Analysis (The Hard Part) – Templates for each visual explaining:
Why this chart type (avoiding common evaluator deductions for poor chart choice).
What the visual reveals (trends, clusters, outliers).
How it answers your business question.
WGU C797 TASK 1 | DATA VISUALIZATION FOR DATA ANALYSIS AND ANALYTICS | 2026 UPDATED | 100% CORRECT.
1. In which type of analytics would you analyze customer purchase history to identify buying patterns? Prescriptive analytics
2. What type of analytics aims to identify the reasons behind past performance? Predictive analytics
3. Which type of analytics would be most useful for determining future customer churn rates based on historical data? Prescriptive analytics
4. The use of historical information to predict what could happen in the future describes prescriptive analytics: false
5. In data visualization, what does "Veracity" refer to? The speed of data transmission
6. Which "V" of data visualization refers to the amount of data being processed and analyzed? Velocity
7. Binning: numerical to categorical transformation
8. Sub setting: not a transformation method
9. Dummy variable: Categorical to Numerical Transformation
10. Reduction: Categorical to Numerical Transformation
11. Imputation: This is not a Transformation Method
12. Which combination of pre-attentive attributes can help in differentiating groups in a bar chart? Color and Length
13. What is the main advantage of using pre-attentive attributes in data visualization? They facilitate quicker understanding of data without conscious effort
14. What is the purpose of using "Hierarchies" in Tableau? To organize data into levels
Of detail for drilling down and analysis
15. What is the Tableau feature that allows users to combine multiple visualizations into a single layout for presentation? Dashboards
16. What is the purpose of using "Show Me" feature in Tableau? To generate recommended visualizations based on selected data
17. Product inventory: numerical; discrete
18. Business Analytics Types ("Descriptive", "Diagnostic", "Predictive", "Prescriptive"): categorical, nominal
19. Cars in a parking lot: numerical; discrete
20. Promotional offers: categorical, nominal
21. Which visualization method would you use if you want to examine sales performance ("High", "Medium", "Low") by region ("North", "South", "East", "West")? Contingency table
22. Which visualization method would you use if you want to display player salary, points per game, and number of games played data for NBA players-
: bubble plot
Content preview
WGU C797 TASK 1 | DATA VISUALIZATION FOR
DATA ANALYSIS AND ANALYTICS | 2026
UPDATED | 100% CORRECT.
1. In which type of analytics would you analyze customer purchase
history to identify buying patterns? Prescriptive analytics
2. What type of analytics aims to identify the reasons behind past
performance? Predictive analytics
3. Which type of analytics would be most useful for determining future
customer churn rates based on historical data? Prescriptive analytics
4. The use of historical information to predict what could happen in the
future describes prescriptive analytics: false
5. In data visualization, what does "Veracity" refer to? The speed of data
transmission
6. Which "V" of data visualization refers to the amount of data being
processed and analyzed? Velocity
7. Binning: numerical to categorical transformation
8. Sub setting: not a transformation method
9. Dummy variable: Categorical to Numerical Transformation
10. Reduction: Categorical to Numerical Transformation
11. Imputation: This is not a Transformation Method
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