DA0-001 Tested & Approved CompTIA Data+ Study Materials
Validate your Skills with Updated CompTIA Data+ Exam Questions & Answers and Test Engine
CompTIA Data+ Certification Exam covers a wide range of topics, including data storage and management, security, privacy, and ethics. Candidates who pass DA0-001 exam demonstrate their ability to work with different types of data, such as structured and unstructured data, and their understanding of data management best practices.
NEW QUESTION # 20
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?
- A. Real-time
- B. Dynamic
- C. Self-service
- D. Static
Answer: D
NEW QUESTION # 21
Which of the following best describes how discrete data differs from continuous data?
- A. Discrete data applies only to numbers.
- B. Discrete data can only be a finite number of values.
- C. Discrete data cannot create a sloped line.
- D. Discrete data can have decimal points.
Answer: B
Explanation:
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 # 22
A data analyst has a set with more than 40.000 rows in the sample schema below:
The analyst would like to create one column that contains the customers' birth dates. Which of the following data quality dimensions would BEST explain the reason for compilation?
- A. Data accuracy
- B. Data duplication
- C. Data integrity
- D. Data completeness
Answer: C
Explanation:
Explanation
Data integrity is the dimension that measures the consistency and validity of data across different data sources.
In this case, the data analyst wants to create one column that contains the customers' birth dates, but the data is stored in different formats and locations in the sample schema. For example, some customers have their birth dates in the customer table, while others have their birth years in the sales table. To compile the data into one column, the data analyst needs to ensure that the data is consistent and valid across the tables. Therefore, data integrity is the best explanation for the reason for compilation. References: Data Quality Dimensions - DATAVERSITY, The 6 Data Quality Dimensions with Examples | Collibra
NEW QUESTION # 23
A data analyst needs to calculate the mean for Q1 sales using the data set below:
Which of the following is the mean?
- A. $2,667.60
- B. $2,466.18
- C. $12,330.88
- D. $3,082.72
Answer: D
Explanation:
Explanation
The mean is the average of all the values in a data set. To calculate the mean, we add up all the values and divide by the number of values. In this case, the mean for Q1 sales is ($2,000 + $3,000 + $4,000 + $2,500 +
$3,500) / 5 = $3,082.72 References: CompTIA Data+ Certification Exam Objectives, page 9
NEW QUESTION # 24
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. 2019 commission plan
- C. 2018 goal data
- D. 2018 actual revenue
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 # 25
A publishing group has requested a dashboard to track submissions before publication. A key requirement is that all changes are tracked, as multiple users will be checking out documents and editing them before submissions are considered final. Which of the following is the BEST way to meet this stakeholder requirement?
- A. Display the version number next to each submission on the dashboard.
- B. Use permissions to ensure users only see certain versions of the submissions.
- C. Present a data refresh date at the top of the dashboard.
- D. Confirm the dashboard is adhering to the corporate style guide.
Answer: B
NEW QUESTION # 26
Which of the following contains alphanumeric values?
- A. 10.1E²
- B. 0
- C. A3J7
- D. 13.6
Answer: C
NEW QUESTION # 27
A cereal manufacturer wants to determine whether the sugar content of its cereal has increased over the years. Which of the following is the appropriate descriptive statistic to use?
- A. Mean
- B. Percent change
- C. Variance
- D. Frequency
Answer: A
NEW QUESTION # 28
Which of the following is the correct data type for text?
- A. Boolean
- B. String
- C. Integer
- D. Float
Answer: B
Explanation:
Explanation
A string is a data type that represents a sequence of characters, such as text, symbols, numbers, or punctuation marks. Strings are enclosed in quotation marks, such as "Hello", "123", or "!@#". Strings can be manipulated, concatenated, sliced, indexed, formatted, and searched using various methods and functions. A string is different from other data types, such as boolean, integer, or float, which represent logical values (true or false), whole numbers, or decimal numbers respectively. Therefore, the correct answer is B. References: What is a String? | Definition and Examples, Python String Methods
NEW QUESTION # 29
Joe. an analyst. tests the loading time on a dashboard he is preparing to go live and finds it is slower than he would like. Which of the following must occur to decrease the loading time?
- A. Update the dashboard subscribers.
- B. Optimize the dashboard.
- C. Change the field definitions.
- D. Deploy the dashboard to production.
Answer: B
Explanation:
Explanation
Optimizing the dashboard is the process of improving its performance and reducing its loading time by applying various techniques and best practices. Some of the common ways to optimize a dashboard are:
Reducing the size and complexity of the data model, such as removing unnecessary columns, aggregating data at the source, or using data compression techniques12 Leveraging caching strategies, such as setting appropriate cache refresh intervals or utilizing Power BI's built-in caching mechanisms, to minimize data retrieval delays2 Utilizing query folding, direct query, or live connection to enhance data processing efficiency and enable real-time data updates23 Optimizing DAX queries, such as avoiding nested calculations, using variables, or simplifying measures, to improve data calculation speed23 Reducing visualizations and calculations, such as using fewer or simpler charts, filters, or parameters, to speed up dashboard rendering12 Evaluating the impact of custom visuals on dashboard load time and avoiding or replacing those that are slow or inefficient2 Applying aggregation and summarization techniques, such as using extract filters, context filters, or level of detail expressions, to reduce the amount of data displayed on the dashboard1 Troubleshooting and resolving any issues that may cause slow dashboard load, such as network latency, server overload, or hardware limitations24
NEW QUESTION # 30
A data analyst has been asked to create a sales report that calculates the rolling 12-month average for sales. If the report will be published on November 1, 2020, which of the following months shouts the report cover?
- A. October 1, 2019 to October 31, 2020
- B. October 31, 2020 to November 1, 2021
- C. October 31, 2019 to October 31, 2020
- D. November 1, 2019 to October 31, 2020
Answer: A
NEW QUESTION # 31
You would like to measure how well an organization is achieving its goals.
What type of analysis should you perform?
- A. Predictive analysis.
- B. Trend analysis.
- C. Outlier analysis.
- D. Performance analysis.
Answer: D
Explanation:
Performance analysis is the technique of studying or comparing the performance of a specific situation in contrast to the aim and yet executed. In Human Resource, performance analysis can help to review an employee's contribution towards a project or assignment, which they allotted him or her.
NEW QUESTION # 32
Jhon is working on an ELT process that sources data from six different source systems.
Looking at the source data, he finds that data about the sample people exists in two of six systems.
What does he have to make sure he checks for in his ELT process?
Choose the best answer.
- A. Duplicate Data.
- B. Invalid Data.
- C. Missing Data.
- D. Redundant Data.
Answer: B
Explanation:
Explanation
Duplicate Data.
While invalid, redundant, or missing data are all valid concerns, data about people exists in two of the six systems. As such, Jhon needs to account for duplicate data issues.
NEW QUESTION # 33
What subset of Structured Query Language (SQL) is used to add, remove, modify, or retrieve the information stored within a relational database?
- A. DML.
- B. DDL.
- C. DQL.
- D. DSL.
Answer: A
Explanation:
Correct answer D. DML.
The Data Manipulation Language (DML) is used to work with the data stored in a database. DML includes the SELECT, INSERT, UPDATE, and DELETE commands.
The Data Definition Language (DDL) contains the commands used to create and structure a relational database. It includes the CREATE, ALTER, and DROP commands.
DDL and DML are the only two sublanguages of SQL.
NEW QUESTION # 34
Which of the following are reasons to create and maintain a data dictionary? (Choose two.)
- A. To provide continuity through personnel turnover
- B. To remember specifics about data fields
- C. To improve data acquisition
- D. To confine breaches of PHI data
- E. To specify user groups for databases
- F. To reduce processing power requirements
Answer: B,C
NEW QUESTION # 35
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. Recode the variables.
- B. Calculate the standard deviations of the variables.
- C. Normalize the variables.
- D. Calculate the percentiles of the variables.
Answer: B
NEW QUESTION # 36
A cereal manufacturer wants to determine whether the sugar content of its cereal has increased over the years.
Which of the following is the appropriate descriptive statistic to use?
- A. Variance
- B. Frequency
- C. Percent change
- D. Mean
Answer: C
Explanation:
Explanation
This is because percent change is a type of descriptive statistic that measures the relative change or difference of a variable over time, such as the sugar content of cereal over years in this case. Percent change can be used to determine whether the sugar content of cereal has increased over years by comparing the initial and final values of the sugar content, as well as calculating the ratio or proportion of the change. For example, percent change can be used to determine whether the sugar content of cereal has increased over years by finding out how much more (or less) sugar there is in cereal now than before, as well as expressing it as a fraction or a percentage of the original sugar content. The other descriptive statistics are not appropriate to use to determine whether the sugar content of cereal has increased over years. Here is why:
Frequency is a type of descriptive statistic that measures how often or how likely a value or an event occurs in a data set, such as how many times a certain sugar content appears in cereal in this case.
Frequency does not measure the relative change or difference of a variable over time, but rather measures the occurrence or chance of a variable at a given time.
Variance is a type of descriptive statistic that measures how much the values in a data set vary or deviate from the mean or average of the data set, such as how much variation there is in sugar content among different cereals in this case. Variance does not measure the relative change or difference of a variable over time, but rather measures the dispersion or spread of a variable at a given time.
Mean is a type of descriptive statistic that measures the average value or central tendency of a data set, such as what is the typical sugar content of cereal in this case. Mean does not measure the relative change or difference of a variable over time, but rather measures the summary or representation of a variable at a given time.
NEW QUESTION # 37
What symbol is used for the variance of a population of data?
- A. s
- B. 0x2
- C. 2x2
- D. 0
Answer: B
Explanation:
The sample variance is defined by(15.59)We use the symbol sx2 for a sample variance and the symbol ox2 for a population variance.
NEW QUESTION # 38
Consider this dataset showing the retirement age of 11 people, in whole years:
54, 54, 54, 55, 56, 57, 57, 58, 58, 60, 60
This tables show a simple frequency distribution of the retirement age data.
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
Explanation:
A measure of central tendency (also referred to as measures of centre or central location) is a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution.
There are three main measures of central tendency: the mode, the median and the mean. Each of these measures describes a different indication of the typical or central value in the distribution.
What is the mode?
The mode is the most commonly occurring value in a distribution.
The most commonly occurring value is 54, therefore the mode of this distribution is 54 years.
NEW QUESTION # 39
Which of the following data types would a telephone number formatted as XXX-XXX-XXXX be considered?
- A. Text
- B. Date
- C. Float
- D. Numeric
Answer: A
NEW QUESTION # 40
A data analyst wants to create "Income Categories" that would be calculated based on the existing variable
"Income". The "Income Categories" would be as follows:
Income category 1: less than $1.
Income category 2: more than $1 and less than $20,000.
Income category 3: more than $20,001 and less than $40,000.
Income category 4: more than $40,001.
Which of the following data manipulation techniques should the data analyst use to create "Income Categories"?
- A. Data merge
- B. Data append
- C. Data blending
- D. Derived variables
Answer: D
Explanation:
Explanation
The correct answer is B: Derived variables Derived variables are variables that you create by calculating or categorizing variables that already exist in your data set.
Data merge is incorrect. Data merging is the process of combining two or more data sets into a single data set.
Data blending is incorrect.
Data blending involves pulling data from different sources and creating a single, unique, dataset for visualization and analysis.
Data append is incorrect. A data append is a process that involves adding new data elements to an existing database.
NEW QUESTION # 41
......
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.
DA0-001 [May-2024] Newly Released] DA0-001 Exam Questions For You To Pass: https://www.vce4plus.com/CompTIA/DA0-001-valid-vce-dumps.html
For your comfort, VCE4Plus provides you the convenience of free CompTIA Data+ braindumps demo: https://drive.google.com/open?id=1ljhs9ioEITd_z0svdEPqBp9n_2rl_pQO