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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • This section of the exam measures skills of a Data Governance Associate and introduces principles for keeping data secure, accurate, and compliant. It covers access controls, encryption, classification of sensitive data like PII and PHI, and legal requirements tied to data use. Candidates must know how to apply quality checks, validate data, and manage master data effectively. It also addresses best practices for maintaining integrity through data dictionaries, audits, and standardisation processes.
Topic 2
  • Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
Topic 3
  • Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.

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CompTIA Data+ Exam Sample Questions (Q156-Q161):

NEW QUESTION # 156
Which of the following AI types is the best option for time-series forecasting?

Answer: D

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 # 157
The human resources department wants to know the number of employees who earn $125,000 or more.
However, the department is concerned about duplicates in the dataset. Given the following table:
Employee_ID
Level
Salary
001
1
10000
002
2
20000
003
2
256000
004
2
125000
001
1
10000
002
2
20000
Which of the following SQL statements resolves this issue?

Answer: D

Explanation:
This question falls under theData Analysisdomain, focusing on SQL queries to handle duplicates while counting employees. The task is to count unique employees with a salary of $125,000 or more, addressing duplicates in the dataset.
* Option A: SELECT DISTINCT Employee_ID FROM Employee WHERE Salary >= 125000This lists unique Employee_IDs but doesn't provide a count, which the department needs.
* Option B: SELECT COUNT(DISTINCT Employee_ID) FROM Employee WHERE Salary >=
125000This counts unique Employee_IDs (using DISTINCT) with a salary of $125,000 or more, correctly addressing duplicates and providing the required count (2 employees: 003 and 004).
* Option C: SELECT DISTINCT Employee_ID FROM Employee WHERE Salary > 125000This lists unique Employee_IDs with a salary strictly greater than $125,000 (missing 004), and doesn't provide a count.
* Option D: SELECT COUNT(Employee_ID) FROM Employee WHERE Salary >= 125000This counts all rows without addressing duplicates, resulting in an incorrect count (2 rows, but only 2 unique employees).
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and COUNT(DISTINCT) is the correct method to count unique employees while handling duplicates.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 158
A data analyst is designing a report for a grocery chain and needs to include stores, product placement, and SKUs. Which of the following best describes the data management concept that the analyst is considering?

Answer: A

Explanation:
Hierarchy describes the organization of data into levels or parent-child relationships. In this case, stores, product placement, and SKUs represent related levels within a structured business hierarchy, allowing the analyst to organize and report data according to those relationships.


NEW QUESTION # 159
A data analyst is querying a database. However, the analyst is unfamiliar with the table names, field names, data types, and field definitions. Which of the following is the best place to look for this information?

Answer: B

Explanation:
A data dictionary provides detailed information about database structures, including table names, field names, data types, and definitions, making it the primary reference for understanding the schema.


NEW QUESTION # 160
A data analyst pulls a table similar to the following one:

Which of the following best explains the data issue with TypeID?

Answer: B

Explanation:
The TypeID column contains information that is already present in the Type column. Values such as "Full Time 1", "Part Time 2", and "Full Time 3" repeat the employment type while adding an identifier, resulting in unnecessary duplication of information. This is an example of redundancy because the same data is being stored in multiple places.


NEW QUESTION # 161
......

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