CompTIA DA0-001 Real Exam Questions Test Engine Dumps Training With 215 Questions
DA0-001 Actual Questions Answers PDF 100% Cover Real Exam Questions
CompTIA DA0-001 (CompTIA Data+ Certification) Exam is a popular certification exam for professionals looking to demonstrate their expertise in data management and analysis. DA0-001 exam is designed to test candidates' knowledge of data management concepts, tools, and techniques, as well as their ability to analyze and interpret data in a meaningful way.
CompTIA DA0-001 (CompTIA Data+ Certification) Certification Exam is a vendor-neutral certification that is designed to test and validate the knowledge and skills of professionals who are involved in data management. CompTIA Data+ Certification Exam certification is ideal for individuals who are looking to pursue a career in data management, data analysis, and data administration. DA0-001 exam covers a wide range of topics such as data storage, data security, data privacy, and data analysis.
CompTIA DA0-001 certification exam is a multiple-choice exam that consists of 90 questions that must be completed within 90 minutes. DA0-001 exam is designed to test the candidate's understanding of the fundamental concepts of data management and their ability to apply that knowledge in real-world situations. DA0-001 exam is available in English and Japanese, and can be taken at any authorized Pearson VUE testing center around the world.
NEW QUESTION # 123
An analyst needs to provide a chart to identify the composition between the categories of the survey response data set:
Which of the following charts would be BEST to use?
- A. Line
- B. Waterfall
- C. Histogram
- D. Scatter pot
- E. Pie
Answer: E
Explanation:
Explanation
The best chart to use to identify the composition between the categories of the survey response data set is a pie chart. A pie chart is a circular chart that shows the relative proportions of different categories in a whole. A pie chart is divided into slices that represent the percentage or frequency of each category. A pie chart is suitable for displaying categorical data that has a few categories and does not have any hierarchical or temporal relationship. In this case, a pie chart can show the composition of the favorite colors among the survey respondents, as well as the percentage of each color. The other options are not as good as a pie chart for this purpose, as they are more suitable for displaying numerical data that has some kind of distribution, trend, correlation, or comparison. A histogram is a bar chart that shows the frequency distribution of a single numerical variable. A line chart is a chart that shows the change of one or more numerical variables over time or another continuous variable. A scatter plot is a chart that shows the relationship between two numerical variables by plotting them as points on a Cartesian plane. A waterfall chart is a chart that shows how an initial value is increased or decreased by a series of intermediate values, resulting in a final value. Reference:
[Choosing the Right Chart Type - DataCamp]
NEW QUESTION # 124
A customer list from a financial services company is shown below:
A data analyst wants to create a likely-to-buy score on a scale from 0 to 100, based on an average of the three numerical variables: number of credit cards, age, and income. Which of the following should the analyst do to the variables to ensure they all have the same weight in the score calculation?
- A. Calculate the standard deviations of the variables.
- B. Normalize the variables.
- C. Calculate the percentiles of the variables.
- D. Recode the variables.
Answer: B
Explanation:
Explanation
Normalizing the variables means scaling them to a common range, such as 0 to 1 or -1 to 1, so that they have the same weight in the score calculation. Recoding the variables means changing their values or categories, which would alter their meaning and distribution. Calculating the percentiles of the variables means ranking them relative to each other, which would not account for their actual magnitudes. Calculating the standard deviations of the variables means measuring their variability, which would not make them comparable.
References: CompTIA Data+ Certification Exam Objectives, page 10
NEW QUESTION # 125
What test formatting option indicates that a field is required in an entity relationship diagram?
- A. Boldfacing.
- B. Underlining.
- C. Capitalization.
- D. Italicization.
Answer: A
NEW QUESTION # 126
What type of visualization allows the use of a bar chart for continuous variables?
- A. Histogram
- B. Tree map
- C. Waterfall chart
- D. Line chart
Answer: A
NEW QUESTION # 127
Which of the following roles is responsible for ensuring an organization's data quality, security, privacy, and regulatory compliance?
- A. Data custodian.
- B. Data steward.
- C. Data processor.
- D. Data owner.
Answer: B
Explanation:
Correct answer B. Data steward.
A data steward is responsible for leading an organization's data governance activities, which include data quality, security, privacy, and regulatory compliance.
NEW QUESTION # 128
Afinancial institution is reporting on sales performance to a company at the account level. Due to the sensitive nature of the government the does il with, some account information is not shown. Which of the following fields should be masked?
- A. Customer name
- B. Sales volume
- C. Product name
- D. Start date
Answer: A
NEW QUESTION # 129
Which of the following is an example of a discrete variable?
- A. The number of people in an office
- B. The temperature of a hot tub
- C. The height of a horse
- D. The time to complete a task
Answer: A
NEW QUESTION # 130
Given the following data:
Which of the following BEST describes the data set?
- A. There is data bias.
- B. The data is incomplete.
- C. The data is outliers.
- D. The data is inconsistent.
Answer: D
Explanation:
Explanation
This is because inconsistency is a type of data quality issue that occurs when the data does not follow a common format, structure, or rule across different sources or systems, which can affect the efficiency and performance of the analysis or process. Inconsistency can be caused by having different spellings, punctuations, capitalizations, or abbreviations for the same or similar values in a data set, such as "M", "m",
"Male", or "male" for gender in this case. Inconsistency can be eliminated or reduced by using data cleansing techniques, such as standardizing or normalizing the data values. The other options are not correct descriptions of the data set. Here is why:
Data bias is a type of data quality issue that occurs when the data is not representative or proportional of the population or the parameter, which can affect the validity and reliability of the analysis or process.
Data bias can be caused by having a sample that is too small, too large, or too skewed for the population or the parameter, such as having only male customers for a product that targets both genders in this case.
Data bias can be eliminated or reduced by using sampling techniques, such as stratified or cluster sampling.
The data is incomplete is a type of data quality issue that occurs when the data is absent or missing in a data set, which can affect the accuracy and reliability of the analysis or process. The data is incomplete can be caused by various factors, such as human error, system error, or non-response. The data is incomplete can be addressed by using various methods, such as replacing or imputing the missing values with some reasonable estimates, such as mean, median, mode, or regression.
The data is outliers is a type of data quality issue that occurs when the data has values that are unusually high or low compared to the rest of the data set, which can affect the quality and validity of the analysis or process. The data is outliers can be caused by various factors, such as measurement error, natural variation, or extreme events. The data is outliers can be addressed by using various methods, such as removing or filtering out the outliers, or using robust statistics that are less sensitive to outliers, such as median, interquartile range, or box plot.
NEW QUESTION # 131
A data analyst is creating a report that will provide information about various regions, products, and time periods. Which of the following formats would be the MOST efficient way to deliver this report?
- A. A static report with a different page for every filtered view
- B. A dashboard with filters at the top that the user can toggle
- C. A workbook with multiple tabs for each region
- D. A daily email with snapshots of regional summaries
Answer: B
NEW QUESTION # 132
Which of the following describes the method of sampling in which elements of data are selected randomly from each of the small subgroups within a population?
- A. Cluster
- B. Simple random
- C. Systematic
- D. Stratified
Answer: C
NEW QUESTION # 133
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?
- A. 2019 goal data
- B. 2018 goal data
- C. 2018 actual revenue
- D. 2019 commission plan
Answer: A
Explanation:
Explanation
answer: C. 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 # 134
Given the image below:
The data should be cleaned because of the presence of:
- A. multicollinearity.
- B. non-parametric data.
- C. outlier
- D. invalid data.
Answer: C
Explanation:
Explanation
The answer is A. Outlier.
Short explanation: An outlier is a data point that differs significantly from the rest of the data in a dataset. An outlier can indicate an error, an anomaly, or a rare event in the data. An outlier can affect the statistical analysis and visualization of the data, such as skewing the mean, variance, or distribution of the data.
Therefore, data should be cleaned to identify and remove or correct any outliers.
The image below shows a box plot graph with a vertical axis labeled "Customer Calls" and a horizontal axis labeled "Churn". The box plot is blue in color and the median value is around 2. There are 7 outliers above the box plot, ranging from 4 to 8.
image)
A box plot is a type of graph that can show the distribution of data values using five summary statistics:
minimum, maximum, median, first quartile, and third quartile. The box represents the interquartile range (IQR), which is the difference between the first and third quartiles. The median is shown as a line inside the box. The whiskers extend from the box to the minimum and maximum values, excluding any outliers. Outliers are shown as dots or circles outside the whiskers.
In this graph, we can see that most of the customer calls are between 0 and 4, with a median of 2. However, there are 7 outliers that have more than 4 customer calls, up to 8. These outliers may indicate some customers who have more issues or complaints than others, or some errors or anomalies in the data collection or recording process. These outliers can affect the analysis and interpretation of the customer calls and churn relationship, such as making it seem that more customer calls lead to less churn, which may not be true for the majority of the customers. Therefore, data should be cleaned to investigate and handle these outliers appropriately.
NEW QUESTION # 135
Which one of the following values will appear first if they are sorted in descending order?
- A. Molly.
- B. Xavier.
- C. Adam.
- D. Aaron.
Answer: B
Explanation:
Explanation
The value that will appear first if they are sorted in descending order is Xavier. Descending order means arranging values from the largest to the smallest, or from the last to the first in alphabetical order. In this case, Xavier is the last name in alphabetical order, so it will appear first when sorted in descending order. The other names will appear in the following order: Molly, Adam, Aaron. Reference: Sorting Data - W3Schools
NEW QUESTION # 136
Oliver is designing an ETL process to copy sales data into a data warehouse on a hourly basis.
What approach should Oliver choose that would be most efficient and minimize the chance of losing historical data?
- A. Delta load.
- B. Bulk load.
- C. Purge and load.
- D. Use ELT instead of ETL.
Answer: A
Explanation:
Correct answer D. Delta load
Since Oliver needs to migrate changes every hour, a delta load is the best approach.
NEW QUESTION # 137
Which one of the following would not normally be considered a summary statistic?
- A. z-score.
- B. Variance.
- C. Mean.
- D. Standard deviation.
Answer: A
Explanation:
Simply put, a z-score (also called a standard score) gives you an idea of how far from the mean a data point is. But more technically it's a measure of how many standard deviations below or above the population mean a raw score is. A z-score can be placed on a normal distribution curve.
NEW QUESTION # 138
The current date is July 14, 2020. A data analyst has been asked to create a report that shows the company's year-over-year Q2 2020 sales. Which of the following reports should the analyst compare?
- A. Q2 2020 and Q2 2019
- B. A Q2 2020 and Q4 2019
- C. YTD 2020 and YTD 2019
- D. Q2 2020 and Q2 2021
Answer: A
Explanation:
Explanation
To create a report that shows the company's year-over-year Q2 2020 sales, the analyst should compare the sales data from Q2 2020 and Q2 2019. Year-over-year (YoY) analysis is a method of comparing the performance of a business or a financial instrument over the same period in different years. It helps to identify trends, growth patterns, and seasonal fluctuations. Q2 refers to the second quarter of a year, which is usually from April to June. Therefore, the correct answer is C. References: YoY - Year over Year Analysis - Definition, Explanation & Examples, What is an Annual Sales Report: Definition, metrics, and tips - Snov.io
NEW QUESTION # 139
A user imports a data file into the accounts payable system each day. On a regular basis. the field input is not what the system is expecting. so it results in an error for the row and a broken import process. To resolve the issue, the user opens the file, finds the error in the row, and manually corrects it before attempting the import again. The import sometimes breaks on subsequent attempts. though. Which of the following changes should be made to this process to reduce the number of errors?
- A. Have the user manually review the file for data completeness before loading it
- B. Spot-check the file prior to import to catch and correct field errors.
- C. Delete all incorrect inputs and upload the corrected file.
- D. Create a data field to data type validator to run the file through prior to import.
Answer: D
Explanation:
Explanation
A data field to data type validator is a tool or a process that checks if the data in each field of a file matches the expected data type, such as text, number, date, etc. A data field to data type validator can help to identify and correct any errors or inconsistencies in the data before importing it into the accounts payable system. This would reduce the number of errors and broken imports, as well as save time and effort for the user.
NEW QUESTION # 140
Which of the following actions should be taken when transmitting data to mitigate the chance of a data leak occurring? (Choose two.)
- A. Data identification
- B. Data processing
- C. Fata removal
- D. Data masking
- E. Data encryption
- F. Data Reporting
Answer: D,E
Explanation:
Explanation
Data encryption and data masking are two actions that can be taken when transmitting data to mitigate the chance of a data leak occurring. Data encryption means transforming data into an unreadable format that can only be decrypted with a key. Data masking means hiding or replacing sensitive data with fictitious or anonymized data. Both methods protect the confidentiality and integrity of the data in transit. References:
CompTIA Data+ Certification Exam Objectives, page 13
NEW QUESTION # 141
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