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CompTIA DA0-001 Exam Syllabus Topics:

SectionWeightObjectives
Data Mining25%- Data acquisition and integration methods
- Data transformation, manipulation, and enrichment
- Data profiling, cleansing, and validation
- Querying and retrieving data
Data Concepts and Environments15%- Data types, structures, and formats
- Data schemas, dimensions, and attributes
- Structured, semi-structured, and unstructured data
- Data storage systems: databases, data marts, warehouses, data lakes
Visualization and Reporting23%- Selecting appropriate visualizations and charts
- Building dashboards and reports
- Communicating insights and recommendations
- Design principles and best practices
Data Governance, Quality and Controls14%- Data quality standards and measurement
- Data governance frameworks and policies
- Data lifecycle management and controls
- Data privacy, security, and compliance
Data Analysis23%- Descriptive and inferential statistics
- Statistical methods: correlation, regression, hypothesis testing
- Interpreting results and identifying patterns/anomalies
- Analytical techniques: trend, performance, exploratory, comparative

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CompTIA Data+ Certification Exam Sample Questions (Q320-Q325):

NEW QUESTION # 320
A data engineer is creating a database field to capture whether a customer likes vanilla ice cream. Which of the following data types is the best to capture this information?

Answer: D

Explanation:
Comprehensive and Detailed In-Depth
When designing a database field to capture a binary preference, such as whether a customer likes vanilla ice cream, the most appropriate data type is:
Option B:Boolean
Rationale:A Boolean data type is used to represent binary values, typically TRUE or FALSE. In this context, it efficiently captures whether a customer likes (TRUE) or does not like (FALSE) vanilla ice cream.
Option A:Integer
Rationale:While integers represent whole numbers, using them to denote binary choices (e.g., 1 for "likes" and 0 for "dislikes") is less intuitive and can lead to ambiguity without proper context.
Option C:Categorical
Rationale:Categorical data types are used for fields that can take on one of a limited set of values, representing different categories. While "likes" and "dislikes" could be categories, a Boolean is more efficient for binary choices.
Option D:Numeric
Rationale:Numeric data types encompass both integers and floating-point numbers. Using a numeric type for a binary preference is unnecessary and could lead to data integrity issues.
Reference:
partners.comptia.org


NEW QUESTION # 321
A data analyst must separate the column shown below into multiple columns for each component of the name:

Which of the following data manipulation techniques should the analyst perform?

Answer: B

Explanation:
Parsing is the data manipulation technique that should be used to separate the column into multiple columns for each component of the name. Parsing is the process of breaking down a string of text into smaller units, such as words, symbols, or numbers. Parsing can be used to extract specific information from a text column, such as names, addresses, phone numbers, etc. Parsing can also be used to split a text column into multiple columns based on a delimiter, such as a comma, space, or dash1. In this case, the analyst can use parsing to split the column by the comma delimiter and create three new columns: one for the last name, one for the first name, and one for the middle initial. This will make the data more organized and easier to analyze.


NEW QUESTION # 322
A data analyst is helping a retail store categorize its customers into five different groups based on the following information:
* How recently the customers made purchases
* How frequently the customers made purchases
* How much the customers spent
Given the following information:

Which of the following would be most important for the analysis?

Answer: C


NEW QUESTION # 323
What effort has the goal of maintaining a single source of truth for the most important data elements handled by the organization?

Answer: B

Explanation:
Master data management (MDM) involves creating a single master record for each person, place, or thing in a business, from across internal and external data sources and applications. This information has been de-duplicated, reconciled and enriched, becoming a consistent, reliable source. Once created, this master data serves as a trusted view of business-critical data that can be managed and shared across the business to promote accurate reporting, reduce data errors, remove redundancy, and help workers make better-informed business decisions.


NEW QUESTION # 324
A county in Illinois is conducting a survey to determine the mean annual income per household. The county is 427sq mi (2.65q km). Which of the following sampling methods would MOST likely result in a representative sample?

Answer: C

Explanation:
Surveys sent to 100 randomly selected homes that are reflective of the population. This is because a random sample is a type of sample that is selected by using a random method, such as a lottery or a computer-generated number, which ensures that every element in the population has an equal chance of being selected. A random sample can result in a representative sample, which means that the sample reflects the characteristics and diversity of the population. By sending surveys to 100 randomly selected homes that are reflective of the population, the analyst can ensure that the sample is representative of the county's households and their income levels. The other sampling methods are not likely to result in a representative sample. Here is why:
A stratified phone survey of 100 people that is conducted between 2:00 p.m. and 3:00 p.m. would result in a biased sample, which means that the sample favors or excludes certain groups or elements in the population. By conducting the survey only between 2:00 p.m. and 3:00 p.m., the analyst would miss out on people who are not available or reachable at that time, such as those who are working or sleeping. This could affect the representativeness and generalizability of the sample.
A systematic survey that is sent to 100 single-family homes in the county would result in an unrepresentative sample, which means that the sample does not reflect the characteristics and diversity of the population. By sending surveys only to single-family homes, the analyst would ignore other types of households, such as apartments, condos, or mobile homes. This could affect the accuracy and reliability of the sample.
Surveys sent to ten randomly selected homes within 5mi (8km) of the county's office would result in a small sample, which means that the sample size is too low to capture the variability and diversity of the population. By sending surveys only to ten homes within a limited area, the analyst would miss out on many households that are located in different parts of the county. This could affect the precision and confidence of the sample.


NEW QUESTION # 325
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