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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 5.0 Data Governance, Quality, and Controls
Topic 2
  • 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 3
  • 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 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 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 (Q85-Q90):

NEW QUESTION # 85
Which of the following best explains the purpose of data lineage?

Answer: C

Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on the purpose of data lineage. Data lineage involves tracking the lifecycle of data.
* To see the steps and path of data flow through different systems (Option A): This describes a data flow diagram, not data lineage, which focuses on transformations rather than just flow.
* To better understand the granularity of data variable relationships (Option B): This relates to data modeling, not the purpose of data lineage.
* To track data transformations from acquisition through reporting (Option C): Data lineage tracks the journey of data, including transformations (e.g., cleaning, aggregation) from its source to its final use in reporting, which is its primary purpose.
* To look up data definitions, ensuring consistent use across business units (Option D): This describes a data dictionary, not data lineage.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and data lineage specifically tracks transformations across the data lifecycle.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 86
The sales department wants to include the composition of total sales amounts across all three sales channels in a report. Given the following sample sales table:
Sales channel
Month
Sales (million $)
Digital
January
135
Store
February
145
Online
March
165
Store
April
200
Store
May
125
Online
June
155
Digital
July
120
Online
August
145
Digital
September
160
Which of the following visualizations is the most appropriate?

Answer: C

Explanation:
This question pertains to theVisualization and Reportingdomain, focusing on selecting the appropriate visualization for a specific requirement. The task is to show the composition of total sales across three channels, which involves showing proportions.
* Pivot table (Option A): A pivot table summarizes data but isn't a visualization; it's more for data exploration.
* Pie chart (Option B): A pie chart shows the proportion of total sales for each channel (Digital, Store, Online), which is ideal for displaying composition.
* KPI card (Option C): A KPI card displays a single metric, not suitable for showing composition across multiple channels.
* Box plot (Option D): A box plot shows data distribution (e.g., quartiles), not proportions.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a pie chart is best for showing the composition of totals.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.


NEW QUESTION # 87
A data analyst creates a report that identifies the middle 50% of the collected data. Which of the following best describes the analyst's findings?

Answer: D

Explanation:
This question pertains to theData Analysisdomain, focusing on statistical measures. The middle 50% of a dataset refers to a specific statistical concept related to data distribution.
* Interquartile range (Option A): The interquartile range (IQR) is the range between the first quartile (Q1, 25th percentile) and the third quartile (Q3, 75th percentile), representing the middle 50% of the data, which matches the description.
* The difference between mode and median (Option B): This measures the spread between two central tendency metrics but doesn't represent the middle 50% of the data.
* Mean variance (Option C): Variance measures data dispersion around the mean, not the middle 50%.
* Skewness from the slope (Option D): Skewness measures data asymmetry, and "slope" is irrelevant here.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and the IQR is the standard measure for the middle 50% of a dataset.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 88
A data analyst creates a report, and some of the fields are empty. Which of the following conditions should the analyst add to a query to provide a list of all the records with empty fields?

Answer: A

Explanation:
This question falls under theData Analysisdomain, focusing on SQL queries to identify data issues. The task is to find records with empty fields, which in SQL means NULL values.
* WHERE [ColumnName] = NULL (Option A): In SQL, NULL cannot be compared using "="; this syntax is incorrect.
* WHERE [ColumnName] IS NULL (Option B): This is the correct SQL syntax to identify NULL values, which represent empty fields.
* WHERE [ColumnName] IS NOT NULL (Option C): This finds non-empty fields, the opposite of the requirement.
* WHERE [ColumnName] = 'NULL' (Option D): This checks for the string "NULL," not a true NULL value, which is incorrect.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," such as identifying NULL values with IS NULL.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 89
Which of the following best enables the retrieval and manipulation of data that is stored in a relational database?

Answer: C


NEW QUESTION # 90
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