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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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 4
  • 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 5
  • 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.

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CompTIA Data+ Exam Sample Questions (Q49-Q54):

NEW QUESTION # 49
Which of the following is business intelligence software?

Answer: A

Explanation:
This question falls under theVisualization and Reportingdomain, focusing on identifying tools used for business intelligence (BI), which typically involves data visualization and reporting.
* SAS (Option A): SAS is a statistical analysis software, not primarily a BI tool focused on visualization.
* Python (Option B): Python is a programming language, not a BI software, though it can be used for data analysis with libraries.
* Notepad++ (Option C): Notepad++ is a text editor, not a BI tool.
* Tableau (Option D): Tableau is a leading BI software designed for data visualization, dashboards, and reporting, making it the correct choice.
The DA0-002 Visualization and Reporting domain includes understanding "the appropriate visualization in the form of a report or dashboard," and Tableau is a recognized BI tool for this purpose.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.


NEW QUESTION # 50
A manager wants a report that contains the days off for each direct report. The manager needs this report to always be up-to-date with the latest data. Which of the following describes the refresh frequency that the manager is requesting?

Answer: A

Explanation:
Real-time refresh ensures the report is continuously updated with the latest data as changes occur, keeping it always current.


NEW QUESTION # 51
A data engineer needs to add a process that will run after an employee table is loaded. The engineer does not know the name of the process that loads employee data. Which of the following is the best document for the engineer to review to find this information?

Answer: A

Explanation:
A data lineage report documents the movement and transformation of data throughout systems and processes. It shows where data originates, how it is processed, and the dependencies between processes. Reviewing the data lineage report would help the engineer identify the process responsible for loading the employee table and determine where to add the subsequent process.


NEW QUESTION # 52
A data analyst calculated the average score per student without making any changes to the following table:

Which of the following exploration techniques should the analyst have considered before calculating the average?

Answer: C

Explanation:
Duplicate records in the dataset would skew the average score calculation, so identifying and handling duplication should be done before performing the analysis.


NEW QUESTION # 53
A data analyst is building a new report using data from a sales column. Upon review, the analyst finds that the sales date is stored as a character type. Which of the following function types should the analyst use to filter by a specific month?

Answer: C

Explanation:
Since the sales date is stored as a character (text) data type, the analyst must use string functions to extract or identify the month portion of the date value before filtering. String functions are designed to manipulate and analyze text data stored in character fields.


NEW QUESTION # 54
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