Question 2 - CompTIA DataX DY0-001 Real Exam Questions [Jan 2026 Update]

Q: 2

SIMULATION

A client has gathered weather data on which regions have high temperatures. The client would like a visualization to gain a better understanding of the data.

INSTRUCTIONS

Part 1

Review the charts provided and use the drop-down menu to select the most appropriate way to standardize the data.

Part 2

Answer the questions to determine how to create one data set.

Part 3

Select the most appropriate visualization based on the data set that represents what the client is looking for.

If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.

Your Answer

Correct Answer:

PART 1: STANDARDIZE DATA

SELECT TABLE 2. VARIABLE: ZIP CODE. ACTION: CORRECT. (THIS WOULD INVOLVE CHANGING 'NAN' TO '7003' BASED ON THE 'CENTRAL' REGION IN TABLE 1).

SELECT TABLE 2. VARIABLE: TEMPERATURE/SCALE. ACTION: CORRECT. (THIS INVOLVES CONVERTING THE '50 °C' VALUE TO '122 °F' TO CREATE A UNIFORM '°F' SCALE FOR COMPARISON).

PART 2: MERGE DATA

METHOD: DATA MATCHING

VARIABLE: ZIP CODE

PART 3: VISUALIZATION

SELECT THE CHOROPLETH MAP (THE TOP-LEFT CHART OPTION).

Explanation

To prepare the data, you must first standardize the disparate values. The '50 °C' in Table 2 must be converted to 122 °F to match the '°F' scale of all other temperature data. The 'NaN' (Not a Number) zip code for the 'Central' region must be corrected to '7003' by referencing Table 1.

In Part 2, Data matching (a database Join) is the correct method to combine tables by adding columns from one to another based on a shared key. A 'Union' would incorrectly stack rows. Zip code is the correct join variable as it is a unique identifier (a primary/foreign key) for each location, whereas 'Region' is too general.

In Part 3, the Choropleth Map is the most appropriate visualization. After standardizing, the data includes high-temperature outliers (e.g., 122°F for Virginia). The choropleth map correctly plots the temperature data by state/region (e.g., VA as '75°F+', NY as '60-75°F'), directly answering the client's request to see which regions have high temperatures.

References

On Data Standardization (Unit Conversion & Missing Data):

Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1-23. (Section 3.3 discusses standardizing variables, which includes converting units for valid comparison, and Section 3.2 addresses missing values, such as 'NaN').

DOI: https://doi.org/10.18637/jss.v059.i10

On Merging Data (Join vs. Union):

MIT OpenCourseWare. (2008). 6.830 Database Systems, Lecture 3: Relational Algebra. (This lecture material formally defines the 'Join' (Data matching) operation as the method for combining tables based on common attributes, contrasting it with 'Union', which requires tables to have identical schemas and appends rows).

Reference: See "Join" and "Union" operators in the Relational Algebra lecture notes.

On Visualization (Choropleth Maps):

The University of Chicago. (n.d.). Geographic Data: Visualization. (This resource from the UChicago Library Data Services explains that choropleth maps are used to "show data aggregated for geographic regions... by coloring those regions," making them ideal for visualizing data like temperature by state or region, as requested by the client).

Reference: Section on "Choropleth Maps."

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