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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
  • 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 4
  • 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 5
  • 5.0 Data Governance, Quality, and Controls

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CompTIA Data+ Exam Sample Questions (Q203-Q208):

NEW QUESTION # 203
Which of the following explains the difference between a char and an nchar data field?

Answer: A

Explanation:
Both char and nchar are fixed-length data types. The difference is that nchar stores Unicode characters, allowing support for a wider range of languages and symbols. Because Unicode characters typically require two bytes per character, nchar uses twice the storage space of char.


NEW QUESTION # 204
Which of the following is the best tool for database management?

Answer: A

Explanation:
Toad is a database management tool specifically designed for working with databases, including querying, administration, performance tuning, and database development. The other options are primarily development, programming, or data science environments rather than dedicated database management tools.


NEW QUESTION # 205
A data analyst receives the following sales data for a convenience store:

The analyst needs to provide information on the products that contain chocolate.
Which of the following RegEx should the analyst use to filter the chocolate products?

Answer: A


NEW QUESTION # 206
A data analyst pulls a table similar to the following one:

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

Answer: A

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 # 207
Given the following table:

Which of the following data types should an analyst use for the numeric values in the Value column?

Answer: C

Explanation:
A double is the most appropriate data type because the Value column contains very large numbers in scientific notation as well as decimal values that require high precision. A double- precision floating-point type can accurately store both large and fractional numeric values.


NEW QUESTION # 208
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