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Which of the following AI types is the best option for time-series forecasting?
A. Robotic process automation
B. Generative AI
C. Foundational models
D. Natural language processing
Answer: C
Explanation:
Foundational models are large AI models trained on vast amounts of data, often exhibiting strong generalization capabilities. While not specifically architected for time-series, their ability to learn complex patterns could potentially be leveraged for forecasting tasks through fine-tuning or specialized architectures built upon them.
In reality, the best AI types specifically designed for time-series forecasting include:
* Recurrent Neural Networks (RNNs), especially LSTMs and GRUs:These architectures are designed to handle sequential data and capture temporal dependencies.
* Transformer Networks:Originally developed for NLP, Transformers have shown remarkable success in time-series forecasting due to their ability to capture long-range dependencies.
* Traditional statistical models:ARIMA, Exponential Smoothing, and other statistical methods remain powerful and interpretable options for time-series analysis.
Therefore, while "foundational models" have some potential, it's important to understand that they aren't the primary or specifically designed AI type for time-series forecasting.
NEW QUESTION # 78
A table contains several rows of cellular numbers with call timestamps, call durations, called numbers, and carriers of the called number. Which of the following allows a data analyst to sort the cellular numbers based on the carriers of the called numbers and include the total call durations?
A. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number, called_number_carrier ORDER BY called_number_carrier;
B. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrier;
C. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number ORDER BY called_number_carrier;
D. SELECT cellular_number, SUM(call_duration) FROM calls GROUP BY call_duration ORDERBY called_number_carrier;
Answer: A
Explanation:
This question falls under theData Analysisdomain of CompTIA Data+ DA0-002, focusing on SQL queries for data analysis. The task requires sorting cellular numbers by the carrier of the called number (called_number_carrier) and calculating the total call durations (SUM(call_duration)).
* Option A: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number ORDER BY called_number_carrierThis query groups by cellular_number only, but called_number_carrier is in the SELECT clause without being in the GROUP BY, which is invalid in SQL (it would raise an error in most databases).
* Option B: SELECT cellular_number, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrierThis query doesn't include called_number_carrier in the SELECT clause, so it cannot be used in the ORDER BY clause, making it invalid. Grouping by call_duration also doesn't align with the task.
* Option C: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number, called_number_carrier ORDER BY called_number_carrierThis query correctly groups by both cellular_number and called_number_carrier (since both are in the SELECT clause), calculates the total call duration with SUM(call_duration), and sorts by called_number_carrier as required.
* Option D: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrierGrouping by call_duration is incorrect because cellular_number and called_number_carrier are in the SELECT clause but not in the GROUP BY, making this query invalid.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and Option C correctly aggregates and sorts the data as specified.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 79
A data company needs a visualization that shows the availability zones from the last ten years and any future availability zones that the company will be using in the next five years. Which of the following is the most appropriate visualization to display this information?
A. Map
B. Mosaic plot
C. Bar chart
D. Pie chart
Answer: A
Explanation:
This question falls under the Visualization and Reporting domain of CompTIA Data+ DA0-002, focusing on selecting the appropriate visualization for a specific dataset. The task is to show availability zones over a
15-year period (past and future), which involves a geographical element since availability zones are typically location-based.
* Bar chart (Option A): Bar charts are good for comparing categorical data but don't effectively show geographical locations or time-based trends across zones.
* Mosaic plot (Option B): Mosaic plots display relationships between categorical variables, not suitable for geographical or time-series data.
* Map (Option C): A map can display availability zones geographically, with annotations or layers to show changes over time (past 10 years and future 5 years), making it the most appropriate visualization.
* Pie chart (Option D): Pie charts show proportions of a whole, not suitable for geographical or time- based data.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a map is the best choice for displaying geographical availability zones over time.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
NEW QUESTION # 80
A data analyst calculated the average score per student without making any changes to the following table:
Student
Subject
Score
123
Math
100
123
Biology
80
234
Math
96
123
Biology
80
345
Biology
88
234
Math
96
Which of the following exploration techniques should the analyst have considered before calculating the average?
A. Grouping
B. Binning
C. Duplication
D. Redundancy
Answer: C
Explanation:
This question pertains to theData Governancedomain, focusing on data quality issues that affect analysis.
The table contains duplicate rows, which would skew the average score calculation if not addressed.
* Student 123: Math (100), Biology (80), Biology (80)- Duplicate Biology score.
* Student 234: Math (96), Math (96)- Duplicate Math score.
* Student 345: Biology (88)- No duplicates.
* Duplication (Option A): The table has duplicate rows (e.g., Student 123's Biology score of 80 appears twice), which would inflate the average if not removed. The analyst should have checked for duplicates before calculating the average.
* Redundancy (Option B): Redundancy refers to unnecessary fields (e.g., storing the same data in multiple columns), not duplicate rows.
* Binning (Option C): Binning groups data into categories, not relevant for addressing duplicates in averaging.
* Grouping (Option D): Grouping (e.g., GROUP BY in SQL) might be part of the solution,but the issue to identify is duplication.
The DA0-002 Data Governance domain includes "data quality control concepts," and checking for duplication is critical to ensure accurate calculations like averages.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
NEW QUESTION # 81
A data engineer needs to create a reporting solution that has predefined filters and the ability to download .csv files. Which of the following is the best solution?
A. Building an email template to request ad hoc reports
B. Generating a weekly executive summary
C. Creating a self-service portal on the company's intranet
D. Developing a dynamic dashboard that refreshes daily
Answer: C
NEW QUESTION # 82
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