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Title: DA0-001 PDF Dumps Feb 27, 2025 Exam Questions – Valid DA0-001 Dumps [Q36-Q53]

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 DA0-001 PDF Dumps Feb 27, 2025 Exam Questions – Valid DA0-001 Dumps
Ultimate DA0-001 Guide to Prepare Free Latest CompTIA Practice Tests Dumps


CompTIA DA0-001 certification exam, also known as the CompTIA Data+ certification, is a vendor-neutral certification that validates the skills and knowledge of professionals working with data. DA0-001 exam is designed to test the candidate's understanding of data management, data analysis, and data reporting. CompTIA Data+ Certification Exam certification is ideal for professionals who work with data in various industries, including finance, healthcare, manufacturing, and technology.
 


Q36. Daniel is using the structured Query language to work with data stored in relational database.He would like to add several new rows to a database table.What command should he use?
 SELECT.
 ALTER.
 INSERT.
 UPDATE.
ExplanationINSERTThe INSERT command is used to add new records to a database table.The SELECT command is used to retrieve information from a database. It’s the most commonly used command in SQL because it is used to pose queries to the database and retrieve the data that you’re interested in working with.The UPDATE command is used to modify rows in the database.The CREATE command is used to create a new table within your database or a new database on your server.Q37. A collections manager has a team calling customers who are past due on their accounts in an attempt to collect payments. The manager receives the call list in the form of a printed report that is generated by the accounting department at the beginning of each week. Consequently, the collections team calls some customers who have made payments in the time since the report was last printed. Which of the following reporting enhancements could the accounting department implement to best reduce the number of calls on current accounts?
 Modify the date range on the report
 Include a time stamp on the report.
 Increase the frequency of report generation.
 Add a report run date to the report.
The best reporting enhancement that the accounting department could implement to reduce the number of calls on current accounts is C. Increase the frequency of report generation.By increasing the frequency of report generation, the accounting department could provide the collections manager with more up-to-date information on the customers who are past due on their accounts. This would help to avoid calling customers who have made payments in the time since the last report was printed, and thus reduce the number of calls on current accounts. Increasing the frequency of report generation would also improve the accuracy and timeliness of the data, and enhance the efficiency and effectiveness of the collections process.Modifying the date range on the report, including a time stamp on the report, or adding a report run date to the report would not be sufficient to reduce the number of calls on current accounts. These enhancements would only provide information on when the report was generated or what period it covers, but they would not change the fact that the report could be outdated by the time it reaches the collections manager. Therefore, these enhancements would not solve the problem of calling customers who have already paid their accounts.Q38. 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?
 73.5
 76.5
 78.8
 81.5
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.Q39. An analyst reviews the following data:735237710Which of the following is the value of the mode?
 3
 5
 7
 10
The mode is the value that appears most frequently in a data set. In the provided data set, the number 7 appears three times, which is more than any other number. Therefore, the mode of this data set is 7.* 3 appears twice, but less frequently than 7.* 5 and 10 each appear only once, so they cannot be the mode.References:* Mode in Statistics – Definition and Examples1* Understanding Measures of Central Tendency2* Mode (statistics) – Wikipedia3Q40. A data analyst has been asked to merge the tables below, first performing an INNER JOIN and then a LEFT JOIN:Customer Table –In-store Transactions –Which of the following describes the number of rows of data that can be expected after performing both joins in the order stated, considering the customer table as the main table?
 INNER: 6 rows; LEFT: 9 rows
 INNER: 9 rows; LEFT: 6 rows
 INNER: 9 rows; LEFT: 15 rows
 INNER: 15 rows; LEFT: 9 rows
ExplanationAn INNER JOIN returns only the rows that match the join condition in both tables. A LEFT JOIN returns all the rows from the left table, and the matched rows from the right table, or NULL if there is no match. In this case, the customer table is the left table and the in-store transactions table is the right table. The join condition is based on the customer_id column, which is common in both tables.To perform an INNER JOIN, we can use the following SQL query:SELECT * FROM customer INNER JOIN in_store_transactions ON customer.customer_id = in_store_transactions.customer_id; This query will return 9 rows of data, as shown below:customer_id | name | lastname | gender | marital_status | transaction_id | amount | date 1 | MARC | TESCO | M| Y | 1 | 1000 | 2020-01-01 1 | MARC | TESCO | M | Y | 2 | 5000 | 2020-01-02 2 | ANNA | MARTIN | F | N | 3 |2000 | 2020-01-03 2 | ANNA | MARTIN | F | N | 4 | 3000 | 2020-01-04 3 | EMMA | JOHNSON | F | Y | 5 |4000 | 2020-01-05 4 | DARIO | PENTAL | M | N | 6 | 5000 | 2020-01-06 5 | ELENA | SIMSON| F| N|7|6000|2020-01-07 6|TIM|ROBITH|M|N|8|7000|2020-01-08 7|MILA|MORRIS|F|N|9|8000|2020-01-09 To perform a LEFT JOIN, we can use the following SQL query:SELECT * FROM customer LEFT JOIN in_store_transactions ON customer.customer_id = in_store_transactions.customer_id; This query will return 15 rows of data, as shown below:customer_id|name|lastname|gender|marital_status|transaction_id|amount|date1|MARC|TESCO|M|Y|1|1000|2020-01-01 1|MARC|TESCO|M|Y|2|5000|2020-01-022|ANNA|MARTIN|F|N|3|2000|2020-01-03 2|ANNA|MARTIN|F|N|4|3000|2020-01-043|EMMA|JOHNSON|F|Y|5|4000|2020-01-05 4|DARIO|PENTAL|M|N|6|5000|2020-01-065|ELENA|SIMSON||F||N||7||6000||2020-01-07 6||TIM||ROBITH||M||N||8||7000||2020-01-087||MILA||MORRIS||F||N||9||8000||2020-01-09 8||JENNY||DWARTH||F||Y||NULL||NULL||NULL As you can see, the customers who do not have any transactions (customer_id = 8) are still included in the result, but with NULL values for the transaction_id, amount, and date columns.Therefore, the correct answer is C: INNER: 9 rows; LEFT: 15 rows.Q41. 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?
 Frequency
 Percent change
 Variance
 Mean
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.Q42. 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 outagesINSTRUCTIONS: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.
 Power outages
 Power
Q43. An e-commerce company recently tested a new website layout. The website was tested by a test group of customers, and an old website was presented to a control group. The table below shows the percentage of users in each group who made purchases on the websites:Which of the following conclusions is accurate at a 95% confidence interval?
 In Germany, the increase in conversion from the new layout was not significant.
 In France, the increase in conversion from the new layout was not significant.
 In general, users who visit the new website are more likely to make a purchase.
 The new layout has the lowest conversion rates in the United Kingdom.
Q44. A data analyst has been asked to derive a new variable labeled “Promotion_flag” based on the total quantity sold by each salesperson. Given the table below:Which of the following functions would the analyst consider appropriate to flag “Yes” for every salesperson who has a number above 1,000,000 in the Quantity_sold column?
 Date
 Mathematical
 Logical
 Aggregate
A logical function is a type of function that returns a value based on a condition or a set of conditions. For example, the IF function in Excel can be used to check if a certain condition is met, and then return one value if true, and another value if false. In this case, the data analyst can use a logical function to check if the Quantity_sold column is greater than 1,000,000, and then return “Yes” if true, and “No” if false. This would create a new variable called Promotion_flag that indicates whether the salesperson has sold more than1,000,000 units or not. References: CompTIA Data+ Certification Exam Objectives, Logical functions (reference)Q45. Which of the following techniques is used to quantify data?
 Decoding
 Enumeration
 Coding
 Structure
Answer C) CodingCoding is a technique that is used to quantify data, especially qualitative data that are not expressed numerically. Coding involves assigning codes, such as numbers, letters, symbols, or colors, to different categories or themes that emerge from the data. For example, if you have a set of survey responses that ask about the satisfaction level of customers, you can code them as follows:Very satisfied = 5Satisfied = 4Neutral = 3Dissatisfied = 2Very dissatisfied = 1By coding the data, you can convert them into quantitative data that can be analyzed using statistical methods, such as calculating the mean, median, mode, frequency, or percentage of each category12.Option A is incorrect, as decoding is not a technique that is used to quantify data, but rather a process of interpreting or translating data from one form to another. For example, decoding can involve converting binary codes into text or images, or decrypting ciphertext into plaintext3.Option B is incorrect, as enumeration is not a technique that is used to quantify data, but rather a process of listing or naming data in a specific order. For example, enumeration can involve listing the names of the states in alphabetical order, or naming the planets in order of their distance from the sun4.Option D is incorrect, as structure is not a technique that is used to quantify data, but rather a property or characteristic of data that describes how they are organized or arranged. For example, structure can refer to the format, type, or schema of data, such as structured, semi-structured, or unstructured data.Q46. A recurring event is being stored in two databases that are housed in different geographical locations. A data analyst notices the event is being logged three hours earlier in one database than in the other database. Which of the following is the MOST likely cause of the issue?
 The data analyst is not querying the databases correctly.
 The databases are recording different events.
 The databases are recording the event in different time zones.
 The second database is logging incorrectly.
The most likely cause of the issue is that the databases are recording the event in different time zones. For example, if one database is in New York and the other database is in Los Angeles, there is a three-hour difference between them. Therefore, an event that occurs at 12:00 PM in New York would be recorded as 9:00 AM in Los Angeles. To avoid this issue, the databases should either use a common time zone or convert the timestamps to a standard format. Therefore, option C is correct.Option A is incorrect because the data analyst is not querying the databases incorrectly, but rather observing a discrepancy in the timestamps.Option B is incorrect because the databases are recording the same event, but with different timestamps.Option D is incorrect because the second database is not logging incorrectly, but rather using a different time zone.Q47. Exhibit.Which of the following logical statements results in Table B?
 
 
 
 
ExplanationThe logical statement that results in Table B is Option D. Option D is a logical statement that uses the AND operator to combine two conditions: Name = “Tom” and Region = “BC”. The AND operator returns true only if both conditions are true, otherwise it returns false. Therefore, Option D will select only the rows from Table A that satisfy both conditions, which are rows 4, 5, 6, and 7. These rows form Table B, as shown below:Name | Gender flag | Level | College | Code | Region Tom | Male | Elementary | A | BC | BC Kim | Female | Elementary | A | BC | BC Pat | Female | Elementary | A | BC | BC Ben | Male | Elementary | A | BC | BC The other options are not correct, as they use different logical operators or conditions that do not result in Table B. Option A uses the OR operator, which returns true if either condition is true, or both. Option A will select all the rows from Table A except row 3, which does not match either condition. Option B uses the NOT operator, which returns the opposite of the condition. Option B will select all the rows from Table A except rows 4, 5, 6, and 7, which match the condition. Option C uses a different condition, Region = “ON”, which does not match any row in Table A. Option C will select no rows from Table A. Reference: [SQL Logical Operators – W3Schools]Q48. An analyst has been tracking company intranet usage and has been asked to create a chat to show the most- used/most-clicked portions of a homepage that contains more than 30 links. Which of the following visualizations would BEST illustrate this information?
 Scatter plot
 Heat map
 Pie chart
 Infographic
This is because a heat map is a visualization that uses colors to represent different values or intensities of a variable. A heat map can be used to show the most-used/most-clicked portions of a homepage that contains more than 30 links by assigning different colors to each link based on how frequently they are clicked by the users. For example, a link that is clicked very often can be colored red, while a link that is clicked rarely can be colored blue. A heat map can help the analyst to identify which links are more popular or important than others on the homepage. The other visualizations are not as effective as a heat map for this purpose. Here is why:A scatter plot is a visualization that uses dots or points to represent the relationship between two variables. A scatter plot cannot show the most-used/most-clicked portions of a homepage that contain more than 30 links because it does not have a clear way of mapping each link to a point on the graph.A pie chart is a visualization that uses slices or sectors to represent the proportion of each category in a whole.A pie chart cannot show the most-used/most-clicked portions of a homepage that contains more than 30 links because it does not have enough space to display all the categories clearly and accurately.An infographic is a visualization that uses images, icons, charts, and text to convey information or tell a story.An infographic cannot show the most-used/most-clicked portions of a homepage that contain more than 30 links because it does not have a consistent or standardized way of representing each link and its click frequency.Q49. Which of the following best describes the process of examining data for statistics and information about the data?Cleansing
 search
 Profiling
 Governance
ExplanationData profiling is the process of examining data for statistics and information about the data, such as the structure, format, quality, and content of the data. Data profiling can help to understand the characteristics, patterns, relationships, and anomalies of the data, as well as to identify and resolve any errors, inconsistencies, or missing values in the data. Data profiling can be done using various tools and methods, such as spreadsheets, databases, or programming languages12.Q50. Which of the following descriptive statistical methods are measures of central tendency? (Choose two.)
 Mean
 Minimum
 Mode
 Variance
 Correlation
 Maximum
ExplanationMean and mode are measures of central tendency, which describe the typical or most common value in a distribution of data. Mean is the arithmetic average of all the values in a dataset, calculated by adding up all the values and dividing by the number of values. Mode is the most frequently occurring value in a dataset.Other measures of central tendency include median, which is the middle value when the data is sorted in ascending or descending order.Q51. An analyst modified a data set that had a number of issues. Given the original and modified versions:Which of the following data manipulation techniques did the analyst use?
 Imputation
 Recoding
 Parsing
 Deriving
The correct answer is B. Recoding.Recoding is a data manipulation technique that involves changing the values or categories of a variable to make it more suitable for analysis. Recoding can be used to simplify or group the data, to correct errors or inconsistencies, or to create new variables from existing ones12 In the example, the analyst used recoding to change the values of Var001, Var002, Var003, and Var004 from numerical to textual form. The analyst also used recoding to assign meaningful labels to the values, such as “Absent” for 0, “Present” for 1, “Low” for 2, “Medium” for 3, and “High” for 4. This makes the data more understandable and easier to analyze.Q52. Which of the following best describes a business analytics tool with interactive visualization and business capabilities and an interface that is simple enough for end users to create their own reports and dashboards?
 Python
 R
 Microsoft Power Bl
 SAS
The best answer is C. Microsoft Power BI.Microsoft Power BI is a business analytics and business intelligence service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. Power BI can connect to multiple data sources, clean and transform data, create custom calculations, and visualize data through charts, graphs, and tables. Power BI can be accessed through a web browser, mobile device, or desktop application and integrated with other Microsoft tools like Excel and SharePoint12 Python is not correct, because Python is a general-purpose programming language that can be used for various applications, including data analysis and visualization. However, Python is not a dedicated business analytics tool, and it requires coding or programming skills to create reports and dashboards.R is not correct, because R is a programming language and software environment for statistical computing and graphics. R can be used for data analysis and visualization, but it is not a specialized business analytics tool, and it requires coding or programming skills to create reports and dashboards.SAS is not correct, because SAS is a software suite for advanced analytics, business intelligence, data management, and predictive analytics. SAS can provide interactive visualizations and business capabilities, but it does not have an interface that is simple enough for end users to create their own reports and dashboards. SAS also requires coding or programming skills to use its features.Q53. The duration of a phone call in milliseconds is an example of:
 ordinal data.
 nominal data.
 boolean data.
 continuous data.
ExplanationThe correct answer is D. Continuous data.Continuous data is a type of quantitative data that can take any value within a range and can be measured with infinite precision. Continuous data can be expressed as fractions, decimals, or percentages. Examples of continuous data are height, weight, temperature, time, speed, etc12 The duration of a phone call in milliseconds is an example of continuous data, because it can take any value within a range (from zero to infinity) and can be measured with infinite precision (up to milliseconds or even smaller units). The duration of a phone call in milliseconds can also be expressed as fractions, decimals, or percentages of a larger unit (such as seconds, minutes, or hours).Ordinal data is not correct, because ordinal data is a type of qualitative or categorical data that can be ordered or ranked according to some criterion. Ordinal data can have a logical order, but the intervals between the values are not equal or meaningful. Examples of ordinal data are grades, ratings, ranks, etc12 Nominal data is not correct, because nominal data is a type of qualitative or categorical data that can be labeled or named without any order or ranking. Nominal data can have a finite number of categories or classes, but the categories have no intrinsic value or hierarchy. Examples of nominal data are gender, color, nationality, etc12 Boolean data is not correct, because boolean data is a type of binary data that can have only two possible values: true or false. Boolean data can be used to represent logical statements, conditions, or outcomes.Examples of boolean data are yes/no, on/off, 1/0, etc. Loading …






	
	

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