DP-600: Explore & Analyze Data (T-SQL, KQL, DAX)
Explore & Analyze Data (T-SQL, KQL, DAX) is one of the skill areas tested on the Fabric Analytics Engineer (DP-600) exam. Below are free DP-600 practice questions with worked answers and a concept diagram — each with a plain-language explanation. Practice the first 10 questions of DP-600 free, no signup.
The concept, in one picture
2 free DP-600 Explore & Analyze Data (T-SQL, KQL, DAX) questions
In a Fabric notebook, you use Matplotlib to plot a histogram titled 'Tip amount distribution' that shows the frequency (Counts) of tip amounts in dollars. What category of analytics does producing this histogram represent?
- predictive
- prescriptive
- ✓ descriptive
- diagnostic
Histograms summarize historical data using descriptive statistics, describing what happened. Building a distribution histogram is therefore an example of descriptive analytics.
A Fabric tenant stores customer churn data as Parquet files in OneLake, including customer demographics and product usage. In a Fabric notebook you load the data into a Spark DataFrame and build column charts comparing the distribution of retained customers versus churned customers by region, products purchased, age, and tenure. Which analytics category does this work fall under?
- prescriptive
- predictive
- ✓ descriptive
- diagnostic
Summarizing past outcomes—here the distribution of retained versus lost customers across attributes—describes what happened, which is descriptive analytics.
Practice DP-600 free
The first 10 questions of every exam are free. No signup, no email wall.
Start practicing →Get a free DP-600 study plan by email
A short plan to work through DP-600 by skill area, plus a note when we add new questions. Optional — the practice above stays free. No spam, unsubscribe anytime.