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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
  • 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 3
  • 5.0 Data Governance, Quality, and Controls
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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DA0-002 Exam Vce, Exam DA0-002 Guide Materials

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CompTIA Data+ Exam Sample Questions (Q78-Q83):

NEW QUESTION # 78
Which of the following report types is considered the most important in a legal and compliance context?

Answer: C

Explanation:
Regulatory reports are critical in legal and compliance contexts because they ensure adherence to laws, regulations, and standards.


NEW QUESTION # 79
Which of the following is business intelligence software?

Answer: D


NEW QUESTION # 80
A data analyst receives a new data source that contains employee IDs, job titles, dates of birth, addresses, years of service, and employees' birth months. Which of the following inconsistencies should the analyst identify?

Answer: C

Explanation:
This question falls under theData Governancedomain, focusing on identifying data quality issues. The dataset includes dates of birth and birth months, which suggests a potential inconsistency.
* Redundancy (Option A): The dataset includes both dates of birth (e.g., 1990-05-15) and birth months (e.g., May), which is redundant because the birth month can be derived from the date of birth, indicating a data quality issue.
* Equivalence (Option B): Equivalence isn't a standard data quality term in this context; it might refer to data matching, which isn't the issue here.
* Parallel (Option C): Parallel isn't a recognized data quality term; it might relate to processing, not data inconsistencies.
* Duplication (Option D): Duplication refers to identical records, but the issue here is redundant fields, not duplicate rows.
The DA0-002 Data Governance domain includes "data quality control concepts," and redundancy is a key inconsistency when the same information is stored in multiple forms unnecessarily.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


NEW QUESTION # 81
A recent server migration applied an update to dataset naming conventions. Multiple users are now reporting stale information in an existing dashboard. The date in the dataset confirms a successful data refresh. Which of the following should a data analyst do first?

Answer: D

Explanation:
This question falls under theData Governancedomain, focusing on troubleshooting data freshness issues in dashboards. The dashboard shows stale data despite a successful refresh, and the server migration updated naming conventions, suggesting a potential mismatch.
* Confirm the dashboard is pointed to the newest dataset (Option A): The server migration updated dataset naming conventions, so the dashboard might still be pointing to an old dataset name, causing stale data. Confirming the dataset connection is the first step.
* Filter the data in the dashboard (Option B): Filtering might adjust the view but doesn't address the root cause of stale data.
* Escalate user permissions on the server (Option C): Permissions issues would likely prevent access, not cause stale data, especially since the dataset refreshed successfully.
* Verify that the dashboard subscription is not expired (Option D): An expired subscription might prevent access, but the dashboard is accessible, just showing stale data.
The DA0-002 Data Governance domain includes "data quality control concepts," such as ensuring dashboards connect to the correct, updated datasets after changes like server migrations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


NEW QUESTION # 82
Which of the following is the best language to use in a notebook?

Answer: D

Explanation:
Python is widely used in notebooks due to its simplicity, extensive data analysis libraries, and strong support in environments like Jupyter, making it ideal for data exploration and analysis.


NEW QUESTION # 83
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