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[Hardware] Pass DA0-001 Exam with Trustable Exam DA0-001 Pass Guide by PracticeVCE

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【Hardware】 Pass DA0-001 Exam with Trustable Exam DA0-001 Pass Guide by PracticeVCE

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CompTIA DA0-001 or CompTIA Data+ Certification Exam is a certification that is designed to validate the skills and knowledge of an individual in the field of data management. CompTIA Data+ Certification Exam certification is offered by the Computing Technology Industry Association (CompTIA), which is a non-profit organization that provides IT certifications and training to individuals who want to pursue a career in the IT industry.
CompTIA DA0-001 Certification Exam is a comprehensive test that assesses the candidate's knowledge and understanding of various concepts related to data management. It consists of 90 multiple-choice questions that need to be completed within 90 minutes. DA0-001 Exam is available in English, Japanese, and Portuguese languages, and it can be taken at any authorized Pearson VUE testing center worldwide. DA0-001 exam is considered to be moderately difficult, and candidates are advised to prepare thoroughly before attempting it.
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CompTIA Data+ Certification Exam Sample Questions (Q209-Q214):NEW QUESTION # 209
A data analyst needs to perform a full outer join of a customer's orders using the tables below:

Which of the following is the mean of the order quantity?
  • A. 81.5
  • B. 78.8
  • C. 73.5
  • D. 76.5
Answer: A
Explanation:
The correct answer is D. OUTER JOIN, seven rows.
An OUTER JOIN is a type of SQL join that returns all the rows from both tables, regardless of whether there is a match or not. If there is no match, the missing side will have null values. An OUTER JOIN can be either a LEFT JOIN, a RIGHT JOIN, or a FULL JOIN, depending on which table's rows are preserved1 Using the example tables, a FULL OUTER JOIN query would look like this:
SELECT Cust_id, Order_id, Order_qty FROM Sales_table FULL OUTER JOIN Order_table ON Sales_table.
Order_id = Order_table.Order_id;
The result of this query would be:
Cust_id | Order_id | Order_qty --------±---------±--------- 1 | 1 | 100 2 | 2 | 50 3 | 3 | 25 4 | 4 | 75 NULL | 5 | 10 NULL | 6 | 20 NULL | 7 | 15 As you can see, the query returns seven rows, one for each order in either table. The orders that are not in the Sales_table have null values for the Cust_id column.
To find the mean of the order quantity, we need to sum up the order quantities and divide by the number of rows. In this case, the mean is (100 + 50 + 25 + 75 + 10 + 20 + 15) / 7 = 42.14. Rounding to one decimal place, we get 42.1 as the mean of the order quantity.

NEW QUESTION # 210
'Which of the following is the BEST reason to use database views instead of tables?
  • A. Views allow for the joining of multiple data sources, whereas tables do not.
  • B. Views can be used to restrict sensitive information.
  • C. Views allow for the storage of temporary data. whereas tables do not.
  • D. Views reduce the need for repetitive, complex data joins.
Answer: D

NEW QUESTION # 211
Which of the following data types should an analyst use to provide the most flexibility when recording emails on a form?
  • A. Discrete
  • B. Continuous
  • C. Alphanumeric
  • D. Text
Answer: D
Explanation:
Comprehensive and Detailed In-Depth
When designing a form to record email addresses, selecting the appropriate data type is crucial to ensure data integrity and flexibility.
Alphanumeric: This data type allows for both letters and numbers. While email addresses do contain alphanumeric characters, they also include special symbols such as '@' and '.', which an alphanumeric data type might not support, leading to potential data entry issues.
Text: This data type is designed to handle a sequence of characters, including letters, numbers, and special symbols. It provides the most flexibility for email addresses, accommodating the full range of characters required.
Discrete: This refers to distinct, separate values, often numerical, and is not suitable for the variable nature of email addresses.
Continuous: This pertains to data that can take any value within a range, typically used for measurements, and is not applicable to email addresses.
Therefore, the 'Text' data type is the most appropriate choice for recording email addresses, as it accommodates all necessary characters without restrictions.
Reference:
CompTIA Partners

NEW QUESTION # 212
An organization wants to evaluate whether project activities are within the set projections and in line to meet the desired project targets. Which of the following types of analysis is best suited for this situation?
  • A. Performance analysis
  • B. Exploratory analysis
  • C. Trend analysis
  • D. Descriptive analysis
Answer: A
Explanation:
Performance analysisis used toassess whether activities, projects, or processes are meeting predefined goals. It compares actual performance against benchmarks or expectations.
* Option A (Trend analysis):Incorrect. Trend analysis looks at data over time to identify patterns or movements, but it does not measure progress against goals.
* Option B (Performance analysis):Correct.This type of analysis is specifically used toevaluate progress against projections and targets.
* Option C (Descriptive analysis):Incorrect. Descriptive analysis summarizes historical data but does not evaluate whether targets are being met.
* Option D (Exploratory analysis):Incorrect. Exploratory analysis is used todiscover patterns and anomaliesrather than to track progress against predefined objectives.
Reference:TheCompTIA Data+ Certification Exam Objectiveshighlight performance analysis as an essential tool for project evaluation.

NEW QUESTION # 213
Which of the following is the best reason for removing data outliers?
  • A. Data varies significantly from others.
  • B. Data is duplicated in the whole range.
  • C. Data is missing from the table.
  • D. Data is redundant in the table.
Answer: A
Explanation:
Comprehensive and Detailed In-Depth
Data outliers are observations that deviate markedly from other observations in the dataset. Handling outliers appropriately is crucial in data analysis to ensure the accuracy and reliability of insights derived from the data.
Option Aata varies significantly from others.
Rationale:Outliers are data points that differ significantly from other observations. They can skew statistical analyses, leading to misleading results. Removing or addressing outliers can help in achieving a more accurate representation of the data, ensuring that analyses and models are not unduly influenced by anomalous values.
Reference:
partners.comptia.org
Option Bata is redundant in the table.
Rationale:Redundant data refers to unnecessary repetition of data within the dataset. While removing redundancy is a part of data cleansing, it pertains to duplicate entries rather than outliers.
Option Cata is duplicated in the whole range.
Rationaleuplicate data points are exact copies of existing entries. Removing duplicates is essential for data accuracy but is a separate issue from handling outliers.
Option Data is missing from the table.
Rationale:Missing data refers to the absence of values in the dataset. Addressing missing data is crucial, but it involves different techniques such as imputation, rather than the removal processes associated with outliers.
Conclusion:The primary reason for removing data outliers is that they vary significantly from other data points, which can distort statistical analyses and lead to incorrect conclusions. Properly managing outliers ensures the robustness and reliability of data-driven decisions.
CompTIA Data+ Certification Exam Objectives:
partners.comptia.org
CompTIA Data+ Study Guide: Exam DA0-001:

NEW QUESTION # 214
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