Updated DA0-001 Dumps Questions Are Available [2023] For Passing CompTIA Exam
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NEW QUESTION # 78
An analyst is required to run a text analysis of data that is found in articles from a digital news outlet. Which of the following would be the BEST technique for the analyst to apply to acquire the data?
- A. ETL
- B. Sampling
- C. Web scraping
- D. Data wrangling
Answer: C
NEW QUESTION # 79
You would like to combine the text in two different strings to form a single string.
What action are you performing?
- A. Trimming.
- B. Case conversion.
- C. Parsing.
- D. Concatenation.
Answer: D
Explanation:
Simply defined, concatenation is the act of linking things together. In Microsoft Excel, the concatenation function is one of many text functions, which allows users to combine data distributed over multiple columns.
The concatenation of two or more numbers is the number formed by concatenating their numerals.
For example, the concatenation of 1, 234, and 5678 is 12345678.
NEW QUESTION # 80
The director of operations at a power company needs data to help identify where company resources should be allocated in order to monitor activity for outages and restoration of power in the entire state. Specifically, the director wants to see the following:
* County outages
* Status
* Overall trend of outages
INSTRUCTIONS:
Please, select each visualization to fit the appropriate space on the dashboard and choose an appropriate color scheme. Once you have selected all visualizations, please, select the appropriate titles and labels, if applicable.
Titles and labels may be used more than once.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
Answer:
Explanation:
Power outages
Explanation
This is a simulation question that requires you to create a dashboard with visualizations that meet the director's needs. Here are the steps to complete the task:
Drag and drop the visualization that shows the county outages on the top left space of the dashboard.
This visualization is a map of the state with different colors indicating the number of outages in each county. You can choose any color scheme that suits your preference, but make sure that the colors are consistent and clear. For example, you can use a gradient of red to show the counties with more outages and green to show the counties with less outages.
Drag and drop the visualization that shows the status of the outages on the top right space of the dashboard. This visualization is a pie chart that shows the percentage of outages that are active, restored, or pending. You can choose any color scheme that suits your preference, but make sure that the colors are distinct and easy to identify. For example, you can use red for active, green for restored, and yellow for pending.
Drag and drop the visualization that shows the overall trend of outages on the bottom space of the dashboard. This visualization is a line graph that shows the number of outages over time. You can choose any color scheme that suits your preference, but make sure that the color is visible and contrasted with the background. For example, you can use blue for the line and white for the background.
Select appropriate titles and labels for each visualization. Titles and labels may be used more than once.
For example, you can use "County Outages" as the title for the map, "Status" as the title for the pie chart, and "Trend" as the title for the line graph. You can also use "County", "Number of Outages",
"Active", "Restored", "Pending", "Time", and "Number of Outages" as labels for the axes and legends of the visualizations.
NEW QUESTION # 81
Which of the following best describes the law of large numbers?
- A. As a sample size decreases, its mean gets closer to the average of the whole population.
- B. When a sample size doubles. the sample is indicative of the whole population.
- C. As a sample size grows, its mean gets closer to the average of the whole population
- D. As a sample size decreases, its standard deviation gets closer to the average of the whole population.
Answer: C
Explanation:
Explanation
The best answer is B. As a sample size grows, its mean gets closer to the average of the whole population.
The law of large numbers, in probability and statistics, states that as a sample size grows, its mean gets closer to the average of the whole population. This is due to the sample being more representative of the population as it increases in size. The law of large numbers guarantees stable long-term results for the averages of some random events1 A: As a sample size decreases, its standard deviation gets closer to the average of the whole population is not correct, because it confuses the concepts of standard deviation and mean. Standard deviation is a measure of how much the values in a data set vary from the mean, not how close the mean is to the population average.
Also, as a sample size decreases, its standard deviation tends to increase, not decrease, because the sample becomes less representative of the population.
C: As a sample size decreases, its mean gets closer to the average of the whole population is not correct, because it contradicts the law of large numbers. As a sample size decreases, its mean tends to deviate from the average of the whole population, because the sample becomes less representative of the population.
D: When a sample size doubles, the sample is indicative of the whole population is not correct, because it does not specify how close the sample mean is to the population average. Doubling the sample size does not necessarily make the sample indicative of the whole population, unless the sample size is large enough to begin with. The law of large numbers does not state a specific number or proportion of samples that are indicative of the whole population, but rather describes how the sample mean approaches the population average as the sample size increases indefinitely.
NEW QUESTION # 82
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. Optimize the dashboard.
- B. Update the dashboard subscribers.
- C. Change the field definitions.
- D. Deploy the dashboard to production.
Answer: A
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 # 83
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 blending
- B. Data merge
- C. Derived variables
- D. Data append
Answer: C
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 # 84
A development company is constructing a new Init in its apartment complex. The complex has the following floor plans:
Using the average cost per square foot of the original floor plans. which of the following should be the price of the Rose Init?
- A. $640,900
- B. $702,500
- C. $690,000
- D. $705,200
Answer: B
Explanation:
Explanation
The correct answer is D. $702,500.
To find the price of the Rose unit, we need to use the average cost per square foot of the original floor plans.
The average cost per square foot is calculated by dividing the price by the square footage of each unit type.
Using the data from the table, we can do the following:
Jasmine: $345,000 / 1,000 = $345 per square foot
Orchid: $525,000 / 2,000 = $262.5 per square foot
Azalea: $375,000 / 1,500 = $250 per square foot
Tulip: $450,000 / 1,800 = $250 per square foot
The average cost per square foot of the original floor plans is the mean of these four values, which is ($345 +
$262.5 + $250 + $250) / 4 = $276.875 per square foot.
To find the price of the Rose unit, we need to multiply the average cost per square foot by the square footage of the Rose unit. The Rose unit has a square footage of 2,535, according to the table. Therefore, the price of the Rose unit is $276.875 x 2,535 = $702,421.875.
Rounding to the nearest whole number, we get as the price of the Rose unit.
NEW QUESTION # 85
Given the following customer and order tables:
Which of the following describes the number of rows and columns of data that would be present after performing an INNER JOIN of the tables?
- A. Nine rows, five columns
- B. Seven rows, eight columns
- C. Five rows, eight columns
- D. Eight rows, seven columns
Answer: B
NEW QUESTION # 86
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, 2019 to October 31, 2020
- C. October 31, 2020 to November 1, 2021
- D. November 1, 2019 to October 31, 2020
Answer: A
NEW QUESTION # 87
A data analyst is asked on the morning of April 9, 2020, to create a sales report that identifies sales year to date. The daily sales data is current through the end of the day. Which of the following date ranges should be on the report?
- A. January 1, 2020 to April 1, 2020
- B. January 1, 2020 to April 9, 2020
- C. January 1, 2020 to April 7, 2020
- D. January 1, 2020 to April 8, 2020
Answer: B
NEW QUESTION # 88
The category PII (Personally identifiable information) includes all of the following, except_________.
- A. Trade secrets.
- B. Medical records.
- C. Browsing habits.
- D. Financial information.
Answer: A
NEW QUESTION # 89
Which of the ing is the correct ion for a tab-delimited spre file?
- A. tar
- B. az
- C. sv
- D. tap
Answer: C
NEW QUESTION # 90
Given the following data:
Which of the following BEST describes the data set?
- A. There is data bias.
- B. The data is outliers.
- C. The data is inconsistent.
- D. The data is incomplete.
Answer: B
NEW QUESTION # 91
Which of the following is used for calculations and pivot tables?
- A. Domo
- B. Microsoft Excel
- C. SAS
- D. IBM SPSS
Answer: B
Explanation:
Explanation
This is because Microsoft Excel is a type of software application that allows users to create, edit, and analyze data in spreadsheets, which are composed of rows and columns of cells that can store various types of data, such as numbers, text, or formulas. Microsoft Excel can be used for calculations and pivot tables, which are two common features or functions in data analysis. Calculations are mathematical operations or expressions that can be performed on the data in the cells, such as addition, subtraction, multiplication, division, average, sum, etc. Pivot tables are interactive tables that can summarize and display the data in different ways, such as by grouping, filtering, sorting, or aggregating the data based on various criteria or categories. The other software applications are not used for calculations and pivot tables. Here is why:
IBM SPSS is a type of software application that allows users to perform statistical analysis and modeling on data sets, such as regression, correlation, ANOVA, etc. IBM SPSS does not use spreadsheets or cells to store or manipulate data, but rather uses data views or variable views to display the data in rows and columns. IBM SPSS does not have pivot tables as a feature or function, but rather has output views or charts to display the results of the analysis.
SAS is a type of software application that allows users to perform data management and analysis using a programming language that consists of statements and commands. SAS does not use spreadsheets or cells to store or manipulate data, but rather uses data sets or tables that are stored in libraries or folders. SAS does not have pivot tables as a feature or function, but rather has procedures or macros that can produce summary tables or reports based on the data.
Domo is a type of software application that allows users to create and share dashboards and visualizations that display data from various sources and systems, such as databases, cloud services, or web applications. Domo does not use spreadsheets or cells to store or manipulate data, but rather uses connectors or APIs to access and integrate the data from different sources. Domo does not have pivot tables as a feature or function, but rather has cards or widgets that can show different aspects or metrics of the data.
NEW QUESTION # 92
Which of the following contains alphanumeric values?
- A. A3J7
- B. 13.6
- C. 0
- D. 10.1E2
Answer: A
NEW QUESTION # 93
While reviewing survey data, an analyst notices respondents entered "Jan," "January," and "01" as responses for the month of January. Which of the following steps should be taken to ensure data consistency?
- A. Filter on any of the responses that do not say "January" and update them to "January".
- B. Sort any of the responses that say "Jan" and update them to "01".
- C. Delete any of the responses that do not have "January" written out.
- D. Replace any of the responses that have "01".
Answer: A
Explanation:
Explanation
Filter on any of the responses that do not say "January" and update them to "January". This is because filtering and updating are data cleansing techniques that can be used to ensure data consistency, which means that the data is uniform and follows a standard format. By filtering on any of the responses that do not say "January" and updating them to "January", the analyst can make sure that all the responses for the month of January are written in the same way. The other steps are not appropriate for ensuring data consistency. Here is why:
Deleting any of the responses that do not have "January" written out would result in data loss, which means that some information would be missing from the data set. This could affect the accuracy and reliability of the analysis.
Replacing any of the responses that have "01" would not solve the problem of data inconsistency, because there would still be two different ways of writing the month of January: "Jan" and "January". This could cause confusion and errors in the analysis.
Sorting any of the responses that say "Jan" and updating them to "01" would also not solve the problem of data inconsistency, because there would still be two different ways of writing the month of January: "01" and
"January". This could also cause confusion and errors in the analysis.
NEW QUESTION # 94
Which of the following will MOST likely be streamed live?
- A. Delimited rows
- B. Key-value pairs
- C. Machine data
- D. Flat files
Answer: D
NEW QUESTION # 95
Which of the following BEST describes the issue in which character values are mixed with integer values in a data set column?
- A. Missing data
- B. Duplicate data
- C. Data outliers
- D. Invalid data type
Answer: D
Explanation:
Explanation
The invalid data type is the best description for the issue in which character values are mixed with integer values in a data set column. Invalid data type means that the data does not match the expected or required format or structure for a given variable or attribute. For example, if a column is supposed to store numerical values, but some rows contain text values, then those rows have an invalid data type. References: CompTIA Data+ Certification Exam Objectives, page 10
NEW QUESTION # 96
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