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| Section | Weight | Objectives |
|---|---|---|
| Data Mining | 25% | - Data transformation and profiling - Pattern identification and extraction - Data acquisition and cleaning techniques |
| Data Concepts and Environments | 15% | - Data sources and acquisition methods - Data concepts and terminology - Data structures and file formats |
| Data Governance, Quality, and Controls | 14% | - Data governance frameworks - Data quality management - Security, privacy, and compliance considerations |
| Data Analysis | 23% | - Statistical methods and calculations - Trend and correlation analysis - Data interpretation and reporting |
| Visualization | 23% | - Chart and dashboard creation - Tool-based visualization techniques - Visualization best practices |
>> Detailed CompTIA DA0-001 Answers <<
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NEW QUESTION # 384
Which of the following is an example of a discrete variable?
Answer: D
Explanation:
A discrete variable is a variable that can only take on a finite number of values, such as integers or categories.
The number of people in an office is an example of a discrete variable, as it can only be a whole number. The temperature of a hot tub, the height of a horse, and the time to complete a task are examples of continuous variables, as they can take on any value within a range. Reference: CompTIA Data+ (DA0-001) Practice Certification Exams | Udemy
NEW QUESTION # 385
A data analyst is asked to create a sales report for the second-quarter 2020 board meeting, which will include a review of the business's performance through the second quarter. The board meeting will be held on July 15, 2020, after the numbers are finalized. Which of the following report types should the data analyst create?
Answer: C
Explanation:
A dynamic report is a type of report that shows data that changes or updates automatically based on certain criteria or parameters. A dynamic report can allow users to interact with the data, filter it, drill down into it, or visualize it in different ways. A dynamic report is suitable for situations where the data changes frequently or where real-time or near-real-time data is needed for decision making or analysis. In this case, the data analyst is asked to create a sales report for the second-quarter 2020 board meeting, which will include a review of the business's performance through the second quarter. The board meeting will be held on July 15, 2020, after the numbers are finalized. This means that the data analyst does not need to show real-time or dynamic data, but rather a fixed and accurate view of the sales data for the second quarter. Therefore, a static report would be the best way to meet this stakeholder requirement. Therefore, the correct answer is A. Reference: [What are Dynamic Reports? | Sisense], Static vs Dynamic Reports - What's The Difference? | datapine
NEW QUESTION # 386
Which of following is a non-relational database?
Answer: D
Explanation:
Explanation
Neo4j is a type of non-relational database that uses a graph model to store data. A graph database is a database that represents data as nodes and edges, where nodes are entities and edges are relationships between them. A graph database can store complex and diverse data that is not easily structured in tables. A graph database can also perform fast and efficient queries on the data by traversing the connections between the nodes
NEW QUESTION # 387
Which of the following types of dashboards should a business intelligence engineer develop in order to provide information about failed data pipelines?
Answer: C
Explanation:
Comprehensive and Detailed In-Depth
Dashboards are visual tools that provide insights into various aspects of business operations. The type of dashboard developed depends on the intended audience and the nature of information to be conveyed.
Referencing Dashboard: This term is not standard in the context of dashboard types and doesn't correspond to a recognized category.
Strategic Dashboard: Designed for senior management, strategic dashboards provide a high-level overview of key performance indicators (KPIs) aligned with the organization's long-term goals. They focus on overall performance and strategic objectives, rather than detailed operational issues.
Operational Dashboard: These dashboards monitor the real-time operations of an organization. They are used to track immediate metrics and processes, allowing teams to respond quickly to issues as they arise. In the context of data pipelines, an operational dashboard would display the current status, including any failures, enabling prompt action to resolve issues.
Technical Dashboard: While this could pertain to dashboards focused on technical metrics, it's not a standard term. Operational dashboards often encompass technical aspects, especially concerning system operations and processes.
Given the need to provide information about failed data pipelines, an Operational Dashboard is most appropriate. It offers real-time monitoring and alerts for immediate issues within data processes, enabling swift identification and resolution of failures.
NEW QUESTION # 388
Which of the following database schemas features normalized dimension tables?
Answer: C
Explanation:
Explanation
The correct answer is B. Snowflake.
A snowflake schema is a type of database schema that features normalized dimension tables. A database schema is a way of organizing and structuring the data in a database. A dimension table is a table that contains descriptive attributes or characteristics of the data, such as product name, category, color, etc. A normalized table is a table that follows the rules of normalization, which is a process of reducing data redundancy and improving data integrity by organizing the data into smaller and simpler tables12 A snowflake schema is a variation of the star schema, which is another type of database schema that features denormalized dimension tables. A denormalized table is a table that does not follow the rules of normalization, and may contain redundant or duplicated data. A star schema consists of a central fact table that contains quantitative measures or facts, such as sales amount, order quantity, etc., and several dimension tables that are directly connected to the fact table. A snowflake schema differs from a star schema in that the dimension tables are further split into sub-dimension tables, creating a snowflake-like shape13 A snowflake schema has some advantages and disadvantages over a star schema. Some advantages are:
It reduces the storage space required for the dimension tables, as it eliminates the redundant data.
It improves the data quality and consistency, as it avoids the update anomalies that may occur in denormalized tables.
It allows more detailed analysis and queries, as it provides more levels of dimensions.
Some disadvantages are:
It increases the complexity and number of joins required to retrieve the data from multiple tables, which may affect the query performance and speed.
It reduces the readability and simplicity of the schema, as it has more tables and relationships to understand.
It may require more maintenance and administration, as it has more tables to manage and update13
NEW QUESTION # 389
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