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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Data Analysis: This section of the exam measures skills of a Reporting Analyst and includes foundational knowledge of statistical methods such as averages, variances, and standard deviation. It covers how to use data to find patterns, track performance, and make predictions. This domain also introduces hypothesis testing, regression, correlation, and different types of analysis like exploratory and trend analysis. Candidates should also be aware of common tools used for analysis, including Excel, SQL, Python, R, and popular BI platforms like Tableau and Power BI.
Topic 2
  • 5.0 Data Governance, Quality, and Controls
Topic 3
  • 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 4
  • 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.
Topic 5
  • Data Mining: This section of the exam measures skills of a Business Intelligence Analyst and covers how data is collected, cleaned, and prepared for analysis. It explains methods like ETL and ELT for data integration, as well as web scraping, API use, and survey data collection. Candidates are expected to identify issues like missing or duplicated data and apply techniques like filtering, sorting, merging, and normalizing. The section also touches on query optimization strategies to improve data handling efficiency.

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CompTIA Data+ Exam Sample Questions (Q163-Q168):

NEW QUESTION # 163
A data analyst is creating a new dataset that involves bringing together the following datasets:
Name
ID
Date of birth
Frank
23525
3/19
Martha
11290
6/13
Ellen
12141
11/4
ID
Address
City
State
23525
1234 Harding
Chicago
IL
11040
935 Terrace Hills
Chino
CA
11290
2 Speedway
Miami
FL
Which of the following would be the output if the data analyst does a FULL JOIN?

Answer: A

Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on database operations like joins. A FULL JOIN combines all rows from both tables, including matches and non-matches, filling in NULLs where there's no corresponding data.
* The first table has IDs: 23525 (Frank), 11290 (Martha), 12141 (Ellen).
* The second table has IDs: 23525, 11040, 11290.
* A FULL JOIN includes all IDs: 23525, 11290, 12141, 11040.
* 23525 matches (Frank with 1234 Harding, Chicago, IL).
* 11290 matches (Martha with 2 Speedway, Miami, FL).
* 12141 has no match in the second table, so Address, City, and State are NULL.
* 11040 has no match in the first table, so Name and Date of birth are NULL.
* Option A: Incorrect; it includes a row for Ellen with "2 Speedway," but Ellen's ID (12141) doesn't match any address, and 11040 is missing.
* Option B: Identical to Option A, so incorrect for the same reasons.
* Option C: Incorrect; it mismatches addresses (e.g., Ellen with 935 Terrace Hills, which belongs to
11040).
* Option D: Correct; it includes all IDs, with NULLs for non-matching rows (Ellen has no address, and
11040 has no name).
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," such as performing joins in relational databases.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 164
A data analyst is analyzing the following dataset:
Transaction Date
Quantity
Item
Item Price
12/12/12
11
USB Cords
9.99
11/11/11
3
Charging Block
8.89
10/10/10
5
Headphones
50.15
Which of the following methods should the analyst use to determine the total cost for each transaction?

Answer: C

Explanation:
This question falls under theData Analysisdomain, focusing on calculating new values from existing data.
The task is to determine the total cost per transaction, which involves multiplying Quantity by Item Price.
* Parsing (Option A): Parsing involves breaking down data (e.g., splitting a string), not calculating totals.
* Scaling (Option B): Scaling adjusts numerical values to a common range (e.g., normalization), not relevant for calculating totals.
* Compressing (Option C): Compressing reduces data size, not applicable to calculating costs.
* Deriving (Option D): Deriving involves creating new data fields by performing calculations on existing ones (e.g., Total Cost = Quantity × Item Price), which fits the task.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," such as deriving new fields through calculations to analyze data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 165
A data analyst is working on an initial analysis of the dataset in the following table:

Which of the following issues should the analyst flag in the data report?

Answer: B

Explanation:
The value 245 is significantly higher than the other counts, indicating an outlier that should be flagged for further investigation.


NEW QUESTION # 166
A data analyst is helping a company achieve its strategic goals. Which of the following types of analytics should the analyst incorporate into the dashboards and tools delivered to the company?

Answer: C

Explanation:
Prescriptive analytics provides recommended actions based on data insights, directly supporting decision-making and helping organizations achieve their strategic goals.


NEW QUESTION # 167
Which of the following data structures would a data engineer most likely receive when using a get command?

Answer: C

Explanation:
JSON (JavaScript Object Notation) is a common data structure returned by GET requests in APIs and web services. It provides a lightweight, structured format for exchanging data between systems and is widely used for transmitting records, objects, and arrays.


NEW QUESTION # 168
......

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