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| Section | Weight | Objectives |
|---|---|---|
| Data Governance, Quality, and Controls | 14% | - Data quality management - Data governance frameworks - Security, privacy, and compliance considerations |
| Visualization | 23% | - Visualization best practices - Chart and dashboard creation - Tool-based visualization techniques |
| Data Concepts and Environments | 15% | - Data concepts and terminology - Data sources and acquisition methods - Data structures and file formats |
| Data Mining | 25% | - Pattern identification and extraction - Data acquisition and cleaning techniques - Data transformation and profiling |
| Data Analysis | 23% | - Trend and correlation analysis - Statistical methods and calculations - Data interpretation and reporting |
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NEW QUESTION # 348
A data analyst is designing a dashboard that will provide a story of sales and determine which site is providing the highest sales volume per customer. The analyst must choose an appropriate chart to include in the dashboard. The following data is available:
Which of the following types of charts should be considered?
Answer: A
NEW QUESTION # 349
A sales analyst needs to report how the sales team is performing to target. Which of the following files will be important in determining 2019 performance attainment?
Answer: A
Explanation:
2019 goal data
To report how the sales team is performing to target, the sales analyst needs to compare the actual sales revenue with the expected or planned sales revenue for the same period. The 2019 goal data is the file that contains the expected or planned sales revenue for the year 2019, which is the target that the sales team is aiming to achieve. By comparing the 2019 goal data with the 2019 actual revenue, the sales analyst can calculate the performance attainment, which is the percentage of the goal that was met by the sales team.
Option A is incorrect, as 2018 goal data is not relevant for determining 2019 performance attainment. The
2018 goal data contains the expected or planned sales revenue for the year 2018, which is not the target that the sales team is aiming to achieve in 2019.
Option B is incorrect, as 2018 actual revenue is not relevant for determining 2019 performance attainment.
The 2018 actual revenue contains the actual sales revenue for the year 2018, which is not comparable with the
2019 goal data or the 2019 actual revenue.
Option D is incorrect, as 2019 commission plan is not relevant for determining 2019 performance attainment.
The 2019 commission plan contains the rules and rates for calculating and paying commissions to the sales team based on their performance attainment, but it does not contain the expected or planned sales revenue for the year 2019.
NEW QUESTION # 350
Which of the following best describes how discrete data differs from continuous data?
Answer: A
Explanation:
Discrete data are data that can only assume specific values that are countable and distinct. For example, the number of books, the number of heads in a coin toss, or the number of patients in a hospital are discrete data. Discrete data cannot have fractional or decimal values, and there are clear spaces between the possible values12.
Continuous data are data that can assume any value within a range and can be meaningfully divided into smaller parts. For example, the weight, height, length, time, or temperature are continuous data. Continuous data can have fractional or decimal values, and there are infinite numbers of possible values between any two points12.
NEW QUESTION # 351
Which of the following describes the use of a representative amount of data from a main repository?
Answer: C
Explanation:
Sampling refers to the process of selecting a representative subset of data from a larger data set or repository.
This technique is used when it is impractical or unnecessary to analyze the entire set of data. A representative sample should accurately reflect the characteristics of the larger population, allowing for analysis and inference about the population as a whole12.
Observation (A) generally refers to the act of monitoring or recording data. Delta load (B) is a term used in data warehousing to describe the process of loading only the changes since the last data extraction, rather than the entire data set. Web scraping is the process of extracting data from websites.
References:
* Understanding the importance of data sampling1.
* The concept of a representative sample in statistics2.
* Data repository management and usage3.
* Benefits and methods of data sampling4.
NEW QUESTION # 352
Which of the following is the best reason to use database views instead of tables?
Answer: D
Explanation:
Database views are virtual tables that provide a specific representation of data from one or more tables. They are powerful tools for simplifying complex queries and enhancing data security.
Option A:Views reduce the need for repetitive, complex data joins.
* Rationale: Views can encapsulate complex JOIN operations and present the result as a single table. This abstraction allows users to retrieve the necessary data without repeatedly writing intricate SQL queries, promoting efficiency and reducing the potential for errors.
Reference: The CompTIA Data+ Certification Exam Objectives highlight the use of views in query optimization, noting their role in simplifying data retrieval and managing complex joins.
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Option B:Views allow for the storage of temporary data, whereas tables do not.
Rationale: This statement is incorrect. Views do not store data themselves; they are virtual representations that display data from underlying tables. Temporary data storage is typically managed using temporary tables, not views.
Option C:Views allow for the joining of multiple data sources, whereas tables do not.
Rationale: While views can represent data from multiple tables or even different databases, the underlying tables themselves can also be designed to include data from various sources through foreign keys and relationships. Therefore, this is not a unique advantage of views over tables.
NEW QUESTION # 353
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