CompTIA DataAI (DY0-001) Certification Sample Questions
The purpose of this Sample Question Set is to provide you with information about the CompTIA DataAI exam. These sample questions will make you very familiar with both the type and the difficulty level of the questions on the DY0-001 certification test. To get familiar with real exam environment, we suggest you try our Sample CompTIA DataAI Certification Practice Exam. This sample practice exam gives you the feeling of reality and is a clue to the questions asked in the actual CompTIA DataAI certification exam.
These sample questions are simple and basic questions that represent likeness to the real CompTIA DY0-001 exam questions. To assess your readiness and performance with real time scenario based questions, we suggest you prepare with our Premium CompTIA DataAI Certification Practice Exam. When you solve real time scenario based questions practically, you come across many difficulties that give you an opportunity to improve.
CompTIA DY0-001 Sample Questions:
01. An analyst joins a table of 12,400 match appearances to a table of player contract records on player_id. The contracts table holds one row per player per contract period, and several players have re-signed with the same club. The joined result has 15,880 rows, and every appearance in it carries a matching contract row.
What accounts for the extra rows, and what restores one row per appearance?
a) The contracts table has several rows per player_id; restrict the join to the contract in force on the match date.
b) The appearances table contains duplicate rows for some of the matches; deduplicate appearances on player, match date and competition before the join is run.
c) The player_id columns hold different types in the two tables, so the engine compares them under an implicit conversion; cast both to a common type before joining.
d) The join was written as an outer join that kept unmatched contract rows, padding them with nulls on the appearance side; change it to an inner join keyed on player_id.
02) A data scientist is looking at a distribution of a continuous variable but is unable to draw any conclusions from a histogram of the data. Which of the following should the data scientist do to get a better visual summary?
a) Add high-contrast coloring.
b) Collect additional data.
c) Lower the range of values.
d) Increase the number of bins.
03. A public-benefits agency's retention schedule requires individual claim case files to be destroyed seven years after a claim closes. A data science team wants a longer history so it can model seasonal demand for caseworker staffing, and has asked for an exemption that would keep closed case files indefinitely.
Which response meets the modeling need without weakening the retention schedule?
a) Extend the retention schedule to fifteen years for all closed case files and re-approve it through the agency's governance board.
b) Derive monthly caseload aggregates before each deletion cycle and retain those in place of the case files.
c) Request a formal exemption for the modeling team and store the case files in a separate access-controlled archive.
d) Keep the case files but strip claimant name and address before the deletion date.
04. A data scientist completes an ML project predicting customer churn and wants to document the process for future use. Which of the following should the data scientist include in the documentation?
a) The source code of the model implementation
b) The model's performance metrics on the test set
c) The description of each feature used in the model
d) The customer purchase history used in the model
05. A transit authority scores vehicle arrival predictions from GPS pings. The current design commits each ping to the feature store as it arrives; freshness sits comfortably inside the 2-second target the service level names, but per-record commit overhead now saturates the store at the evening peak. The nightly bulk load the team ran previously was cheap and six hours stale.
Which change removes most of the per-record overhead while still meeting the 2-second freshness target?
a) Return to the scheduled bulk load and serve the last completed snapshot.
b) Commit the stream in fixed sub-second windows, writing each window as one batch.
c) Keep the per-ping commits and add store replicas, spreading the writes across more partitions.
d) Buffer pings until a fixed record count is reached, flushing whenever the buffer fills.
06. A data scientist is trying to predict customer churn. After conducting a literature review, the data scientist identifies several potential models that were successful in similar contexts. Which of the following is the most appropriate next step in selecting a model design for iteration?
a) Choose the model with the most citations in the literature review, as it is the most reliable and accepted.
b) Develop a baseline model and repeatedly implement and compare more complex models, considering interpretability requirements.
c) Select the most recently published model from the literature review since it is likely the most current and effective.
d) Implement all models that were identified in the literature review and choose the one with the highest accuracy on the test set.
07. Which of the following is the best method to handle data imbalance?
a) DBSCAN
b) Binomial logistic regression
c) SMOTE
d) PCA
08. A data scientist is analyzing house prices and observes the following distribution of house counts by price range:
100,000–200,000: 50 houses
200,001–300,000: 30 houses
300,001–400,000: 15 houses
400,001–500,000: 3 houses
500,001–600,000: 1 house
600,001–700,000: 1 house
Which of the following techniques should the data scientist apply to make the data more normally distributed?
a) Box-Cox transformation
b) One-hot encoding
c) Principal component analysis
d) Min-max scaling
09. A hotel group's revenue model is built from a single 900-line script. The same occupancy-rate calculation appears in four places with small differences between the copies, and two analysts working on separate forecasts keep overwriting each other's edits to it. Each incident is resolved by hand and recurs within a fortnight.
Which change addresses the cause of the recurrence rather than its symptom?
a) Add a header comment above each copy recording what it computes, the forecast that relies on it and who last changed it.
b) Give each analyst a separate copy of the script to edit for their own forecast, with a weekly meeting to reconcile the two sets of numbers.
c) Extend the code-review checklist, requiring every pull request that touches the script to be checked for duplicated logic before approval.
d) Extract the occupancy-rate calculation into a single named function in a shared module that both forecasts import.
10. A data science team has a data set consisting of engagements that sales personnel had with customers. Each engagement includes the set of actions taken by the salesperson and whether the customer made a purchase. Which of the following is the best way to find correlations between different sets of actions and customer purchasing behavior?
a) Cluster analysis
b) KNN
c) Association rules
d) Feature importance chart
Answers:
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Question: 01 Answer: a |
Question: 02 Answer: d |
Question: 03 Answer: b |
Question: 04 Answer: c |
Question: 05 Answer: b |
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Question: 06 Answer: b |
Question: 07 Answer: c |
Question: 08 Answer: a |
Question: 09 Answer: d |
Question: 10 Answer: c |
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