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CompTIA DA0-001 exam is a multiple-choice exam that consists of 90 questions. DA0-001 exam is designed to test the candidate's knowledge of data management concepts and techniques. DA0-001 Exam is available in English, Japanese, and Portuguese. DA0-001 exam has a passing score of 720 on a scale of 100-900.
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CompTIA DA0-001 Certification Exam is intended for individuals who have a basic understanding of data management concepts and technologies. It is suitable for professionals who are involved in data analysis, data warehousing, data governance, data quality, and data security. CompTIA Data+ Certification Exam certification exam is vendor-neutral, which means that it is not specific to any particular technology or product. CompTIA Data+ Certification Exam certification is recognized globally and is a valuable asset for individuals who are seeking to advance their careers in the field of data management. CompTIA Data+ Certification Exam certification exam consists of 90 multiple-choice questions, and candidates are required to score a minimum of 675 out of 900 to pass the exam.
CompTIA Data+ Certification Exam Sample Questions (Q41-Q46):
NEW QUESTION # 41
Given the following report:
Which of the following components need to be added to ensure the report is point-in-time and static? (Select two).
Answer: B,D
Explanation:
To ensure that a report is point-in-time and static, it should include the date when the report was last accessed and the date on which the report was run. These components confirm the specific time frame the data represents, making the report a fixed reference that does not change with subsequent data updates or accesses.
This is crucial for accurate historical analysis and for maintaining the integrity of the data as it was at the time of the report's creation.
References:
* Best practices in business reporting.
* Importance of time-stamping in data analysis.
* Guidelines for creating static reports in data analytics.
NEW QUESTION # 42
Given the following data tables:
Which of the following MDM processes needs to take place FIRST?
Answer: D
Explanation:
This is because a data dictionary is a type of document that defines and describes the data elements, attributes, and relationships in a database or a data set. A data dictionary can be used to facilitate the MDM (Master Data Management) process, which is a process that aims to ensure the quality, consistency, and accuracy of the data across different sources and systems. By creating a data dictionary first, the analyst can establish a common understanding and standardization of the data field names, types, formats, and meanings, as well as identify any potential issues or conflicts in the data, such as missing values, duplicate values, or inconsistent values. The other MDM processes can take place after creating a data dictionary. Here is why:
Compliance with regulations is a type of MDM process that ensures that the data meets the legal and ethical requirements and standards of the industry or the organization. Compliance with regulations can take place after creating a data dictionary, because the data dictionary can help theanalyst to identify and apply the relevant rules and policies to the data, such as data privacy, security, or retention.
Standardization of data field names is a type of MDM process that ensures that the data field names are consistent and uniform across different sources and systems. Standardization of data field names can take place after creating a data dictionary, because the data dictionary can provide a reference and a guideline for naming and labeling the data fields, as well as resolving any discrepancies or ambiguities in the data field names.
Consolidation of multiple data fields is a type of MDM process that combines or merges the data fields from different sources or systems into a single source or system. Consolidation of multiple data fields can take place after creating a data dictionary because the data dictionary can help the analyst to map and match the data fields from different sources or systems based on their definitions and descriptions, as well as eliminating any redundant or duplicate data fields.
NEW QUESTION # 43
Which of the following is an example of discrete data?
Answer: C
Explanation:
Comprehensive and Detailed In-Depth Explanation:
Discrete data refers to countable, distinct values that cannot be subdivided meaningfully. These values are often whole numbers representing items that can be counted individually.
Option A:The number of employees at a company
* Rationale:This represents discrete data because employees can be counted as individual units. You cannot have a fraction of an employee; thus, the data is countable and discrete.
Option B:The amount of rain that falls in a storm
* Rationale:This represents continuous data, as rainfall can be measured in infinitely fine increments (e.
g., millimeters, inches). The amount can take any value within a range.
Option C:The temperature at a weather station
* Rationale:Temperature is continuous data because it can vary smoothly over a range and can be measured with fine precision (e.g., degrees Celsius or Fahrenheit).
Option D:The power consumption in a building
* Rationale:Power consumption is continuous data, as it can be measured in units that allow for fractional values (e.g., kilowatt-hours) and can vary continuously over time.
NEW QUESTION # 44
A data analyst reviews the following data set:
Which of the following is the range value?
Answer: B
NEW QUESTION # 45
Given the following data table:
Which of the following are appropriate reasons to undertake data cleansing? (Select two).
Answer: A,F
NEW QUESTION # 46
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