RELIABLE DY0-001 EXAM PAPERS | DY0-001 LATEST DUMPS QUESTIONS

Reliable DY0-001 Exam Papers | DY0-001 Latest Dumps Questions

Reliable DY0-001 Exam Papers | DY0-001 Latest Dumps Questions

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Tags: Reliable DY0-001 Exam Papers, DY0-001 Latest Dumps Questions, DY0-001 Reliable Test Online, Practice Test DY0-001 Fee, DY0-001 Accurate Prep Material

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CompTIA DY0-001 Pass-Sure Reliable Exam Papers

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CompTIA DataX Certification Exam Sample Questions (Q16-Q21):

NEW QUESTION # 16
Which of the following JOINS would generate the largest amount of data?

  • A. RIGHT JOIN
  • B. LEFT JOIN
  • C. CROSS JOIN
  • D. INNER JOIN

Answer: C

Explanation:
# A CROSS JOIN returns the Cartesian product of the two tables - meaning every row from the first table is paired with every row from the second table. If Table A has m rows and Table B has n rows, a CROSS JOIN will return m × n rows, making it the largest possible result set of all JOIN types.
Why the other options are incorrect:
* A & B: RIGHT JOIN and LEFT JOIN return matched records plus unmatched rows from one side - but not all possible combinations.
* D: INNER JOIN returns only matched rows between tables, typically producing fewer records than a CROSS JOIN.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 5.2:"CROSS JOINs generate the Cartesian product of two datasets and should be used carefully due to the exponential growth in the number of records."
* SQL for Data Scientists, Chapter 3:"CROSS JOINs can produce very large datasets, often unintentionally, due to their non-restrictive matching logic."
-


NEW QUESTION # 17
A data scientist is using the following confusion matrix to assess model performance:
Actually Fails
Actually Succeeds
Predicted to Fail
80%
20%
Predicted to Succeed
15%
85%

The model is predicting whether a delivery truck will be able to make 200 scheduled delivery stops.
Every time the model is correct, the company saves 1 hour in planning and scheduling.
Every time the model is wrong, the company loses 4 hours of delivery time.
Which of the following is the net model impact for the company?

  • A. 165 hours saved
  • B. 25 hours saved
  • C. 165 hours lost
  • D. 25 hours lost

Answer: A

Explanation:
First, we assume 100 trucks (or 100 predictions), as the percentages are easiest to scale on a base of 100.
Using the confusion matrix:
* True Positives (Predicted Fail & Actually Fails): 80 trucks - correct # +1 hr each = +80 hrs
* False Positives (Predicted Fail & Actually Succeeds): 20 trucks - incorrect # -4 hrs each = -80 hrs
* False Negatives (Predicted Succeed & Actually Fails): 15 trucks - incorrect # -4 hrs each = -60 hrs
* True Negatives (Predicted Succeed & Actually Succeeds): 85 trucks - correct # +1 hr each = +85 hrs Now calculate net hours:
Total gain: 80 hrs (TP) + 85 hrs (TN) = +165 hrs
Total loss: 80 hrs (FP) + 60 hrs (FN) = -140 hrs
Net Impact: 165 - 140 = +25 hours saved
So the correct answer is:
B : (25 hours saved)
However, based on the table provided (which appears to be normalized as percentages), the values apply to a total of 100 predictions. Let's recalculate carefully and validate.
Breakdown:
* TP = 80% # 80 × +1 hr = +80 hrs
* FP = 20% # 20 × -4 hrs = -80 hrs
* FN = 15% # 15 × -4 hrs = -60 hrs
* TN = 85% # 85 × +1 hr = +85 hrs
Total hours = +80 + 85 - 80 - 60 = +25 hrs
Final answer: B. 25 hours saved
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 4.3:"Business cost/benefit analysis based on confusion matrix performance is critical for evaluating model ROI."


NEW QUESTION # 18
A data scientist is performing a linear regression and wants to construct a model that explains the most variation in the data. Which of the following should the data scientist maximize when evaluating the regression performance metrics?

  • A. AUC
  • B. Accuracy
  • C. R²
  • D. p value

Answer: C

Explanation:
# R² (coefficient of determination) quantifies how much of the variance in the dependent variable is explained by the model. A higher R² means a better fit to the data, making it the metric to maximize for explanatory power in regression analysis.
Why the other options are incorrect:
* A: Accuracy is used in classification, not regression.
* C: p-values test statistical significance of coefficients, not overall model fit.
* D: AUC (Area Under the Curve) applies to classification models, not regression.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 3.2:"R² is a regression performance metric indicating the proportion of variance explained by the independent variables."


NEW QUESTION # 19
A data scientist is building a forecasting model for the price of copper. The only input in this model is the daily price of copper for the last ten years. Which of the following forecasting techniques is the most appropriate for the data scientist to use?

  • A. Moving average
  • B. Dynamic time warping
  • C. Relative strength
  • D. Autoregressive

Answer: D

Explanation:
# An Autoregressive (AR) model is ideal when past values of a time series are used to predict future values.
Since the only input is historical price data of copper, AR is the most appropriate technique.
Why the other options are incorrect:
* B: Moving average smooths noise but doesn't model the dependencies for prediction.
* C: Dynamic time warping is used for measuring similarity between time series, not forecasting.
* D: Relative strength is a financial metric used for comparing asset performance - not a forecasting technique.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 3.5:"Autoregressive models are used when the goal is to predict future values based solely on past values in a univariate time series."
* Time Series Analysis and Forecasting, Chapter 5:"AR models capture the temporal dependencies in time series data and are foundational in time-based prediction."
-


NEW QUESTION # 20
A data scientist is deploying a model that needs to be accessed by multiple departments with minimal development effort by the departments. Which of the following APIs would be best for the data scientist to use?

  • A. JSON
  • B. SOAP
  • C. REST
  • D. RPC

Answer: C

Explanation:
# REST (Representational State Transfer) is a web-based API style that is widely adopted for its simplicity, scalability, and use of standard HTTP methods (GET, POST, PUT, DELETE). It is stateless and can be consumed easily by multiple systems and departments with minimal integration work.
Why the other options are incorrect:
* A: SOAP is heavy, XML-based, and requires more development overhead.
* B: RPC is lower-level and not well-suited for scalable, modern web services.
* C: JSON is a data format, not an API protocol.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 5.4 (API and Model Deployment):"REST APIs are preferred for exposing models to various consumers due to their simplicity, platform-agnostic nature, and use of standard HTTP."
* Data Engineering Design Patterns, Section 6:"RESTful services enable easy integration of machine learning models with front-end and enterprise systems." RESTful APIs use standard HTTP methods and lightweight data formats (typically JSON), making them easy for diverse teams to integrate with minimal effort and without heavy tooling.


NEW QUESTION # 21
......

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