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質問 # 177
An analyst has received the requirements for an internal user dashboard. The analyst confirms the data sources and then creates a wireframe. Which of the following is the NEXT step the analyst should take in the dashboard creation process?
- A. Optimize the dashboard.
- B. Get stakeholder approval.
- C. Create subscriptions.
- D. Deploy to production.
正解：B
解説：
Getting stakeholder approval is the next step the analyst should take in the dashboard creation process, after confirming the data sources and creating a wireframe. Stakeholder approval means getting feedback and validation from the intended users or clients of the dashboard, to ensure that it meets their expectations and requirements. This step helps to avoid rework and ensure customer satisfaction. References: CompTIA Data+ Certification Exam Objectives, page 14
質問 # 178
A data analyst for a media company needs to determine the most popular movie genre. Given the table below:
Which of the following must be done to the Genre column before this task can be completed?
- A. Merge
- B. Delimit
- C. Append
- D. Concatenate
正解：B
解説：
The action that must be done to the Genre column before this task can be completed is delimit. Delimit is a process of separating or splitting a string of text into multiple parts based on a delimiter, which is a character or a sequence of characters that marks the boundary between the parts. For example, a comma (,) or a semicolon (;) can be used as a delimiter. In this case, the Genre column contains multiple genres for each movie, separated by commas. To determine the most popular movie genre, the data analyst needs to delimit the Genre column by commas, so that each genre can be counted and compared separately. The other options are not relevant for this task, as they are related to combining or joining strings or tables, not separating them.
Append is a process of adding or attaching one string or table to the end of another string or table. Merge is a process of combining or joining two or more tables into one table based on a common column or key.
Concatenate is a process of joining or linking two or more strings together into one string. Reference: [How to Split Text in Excel - Exceljet]
質問 # 179
According to the empirical rule, what percent of thee values in a sample fall within three standard deviations of the mean in a normal distribution?
- A. 95%
- B. 90%
- C. 68%
- D. 99.70%
正解：D
解説：
According to the empirical rule, 68% of values are within one standard deviation, 95% are within two standard deviations, and 99.7% are within three standard deviations.
質問 # 180
Which of the following descriptive statistical methods are measures of central tendency? (Choose two.)
- A. Mode
- B. Variance
- C. Maximum
- D. Mean
- E. Correlation
- F. Minimum
正解：A、D
解説：
Mean 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.
質問 # 181
A database consists of one fact table that is composed of multiple dimensions. Each dimension is represented by a denormalized table. This structure is an example of a:
- A. star schema.
- B. non-relational schema.
- C. snowflake schema.
- D. galaxy schema.
正解：A
解説：
Explanation
A star schema is a type of database schema that consists of one fact table and multiple dimension tables. The fact table contains the measures or metrics of the business process, such as sales, orders, or transactions. The dimension tables contain the attributes or characteristics of the business entities, such as products, customers, or locations. The fact table is connected to the dimension tables by foreign keys that reference the primary keys of the dimension tables. The fact table is located at the center of the schema, while the dimension tables are located at the edges, forming a star-like shape1.
A star schema is an example of a denormalized schema, which means that the dimension tables are not normalized and may contain redundant or repeated data. This is done to improve the performance and simplicity of queries, as there are fewer joins and tables involved. A star schema is suitable for data warehouses and business intelligence applications that require fast and efficient data retrieval2.
質問 # 182
Which of the following differentiates a flat text file from other data types?
- A. Data is stored in defined rows.
- B. Data is separated by a delimiter.
- C. Data is defined with key-value pairs.
- D. Data is housed in a markup language.
正解：B
解説：
Explanation
A flat text file is a type of data file that contains only plain text without any formatting or markup. Data in a flat text file is usually separated by a delimiter, which is a character that marks the boundary between different fields or values. For example, a comma-separated values (CSV) file is a flat text file that uses commas as delimiters. Other common delimiters are tabs, spaces, semicolons, and pipes. Therefore, the correct answer is A: References: Plain text - Wikipedia, Comparison of document markup languages - Wikipedia
質問 # 183
You would like to measure how well an organization is achieving its goals.
What type of analysis should you perform?
- A. Trend analysis.
- B. Outlier analysis.
- C. Predictive analysis.
- D. Performance analysis.
正解：D
解説：
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.
質問 # 184
An analyst has generated a report that includes the number of months in the first two quarters of 2019 when sales exceeded $50,000:
Which of the following functions did the analyst use to generate the data in the Sales_indicator column?
- A. Aggregate
- B. Logical
- C. Sort
- D. Date
正解：B
解説：
This is because a logical function is a type of function that returns a value based on a condition or a set of conditions. A logical function can be used to generate the data in the Sales_indicator column by comparing the values in the Sales column with a threshold of $50,000 and returning either "Exceeded $50,000" or "Not exceeded $50,000" accordingly. For example, a logical function in Excel that can achieve this is:
The other functions are not suitable for generating the data in the Sales_indicator column. Here is why:
Aggregate is a type of function that performs a calculation on a group of values, such as sum, average, count, etc. An aggregate function cannot generate the data in the Sales_indicator column because it does not compare the values in the Sales column with a threshold or return a text value based on a condition.
Date is a type of function that manipulates or extracts information from dates, such as year, month, day, etc. A date function cannot generate the data in the Sales_indicator column because it does not use the values in the Sales column or return a text value based on a condition.
Sort is a type of function that arranges the values in a column or a range in ascending or descending order. A sort function cannot generate the data in the Sales_indicator column because it does not create a new column or return a text value based on a condition.
質問 # 185
Which of the following data types is best for representing count data?
- A. Continuous
- B. Referential
- C. Discrete
- D. Sequential
正解：C
解説：
Comprehensive and Detailed In-Depth
Count data refers to data that represents the number of occurrences of an event or the number of items in a set, which are whole numbers (integers). Understanding the nature of data types is crucial for accurate data analysis and representation.
Discrete Data: This type of data consists of distinct, separate values. Discrete data is countable and often represents items that can be counted in whole numbers, such as the number of customers, defects, or occurrences. Since count data involves whole numbers, discrete data is the most appropriate representation.
Referential Data: This pertains to data that establishes relationships between tables in a database, often using keys. It is not related to counting occurrences.
Sequential Data: This involves data that follows a specific order or sequence, such as timestamps or ordered events. While it indicates order, it doesn't inherently represent count data.
Continuous Data: This type of data can take any value within a range and is measurable rather than countable, such as height, weight, or temperature. Continuous data is not suitable for representing count data, as counts are discrete by nature.
Therefore, Discrete data is the best choice for representing count data, as it accurately reflects whole number counts of occurrences or items.
質問 # 186
Consider the following dataset which contains information about houses that are for sale:
Which of the following string manipulation commands will combine the address and region name columns to create a full address?
full_address------------------------- 85 Turner St, Northern Metropolitan 25 Bloomburg St, Northern Metropolitan 5 Charles St, Northern Metropolitan 40 Federation La, Northern Metropolitan 55a Park St, Northern Metropolitan
- A. SELECT CONCAT(regionname, ' , ' , address) AS full_address FROM melb LIMIT 5
- B. SELECT CONCAT(address, ' , ' , regionname) AS full_address FROM melb LIMIT 5;
- C. SELECT CONCAT(regionname, '-' , address) AS full_address FROM melb LIMIT 5;
- D. SELECT CONCAT(address, '-' , regionname) AS full_address FROM melb LIMIT 5;
正解：B
解説：
The correct answer is A: SELECT CONCAT(address, ' , ' , regionname) AS full_address FROM melb LIMIT
5; String manipulation (or string handling) is the process of changing, parsing, splicing, pasting, or analyzing strings. SQL is used for managing data in a relational database. The CONCAT () function adds two or more strings together. Syntax CONCAT(stringl, string2,... string_n) Parameter Values Parameter Description stringl, string2, string_n Required. The strings to add together.
質問 # 187
After the daily ETL jobs are completed, the data in the reports does not appear complete, and a lot of data seems to be missing. Which of the following concepts should be used to assess and investigate further?
- A. Cross-validation
- B. Data integrity
- C. Data consistency
- D. Data profiling
正解：D
解説：
Comprehensive and Detailed In-Depth
When encountering issues where reports are incomplete or data appears to be missing after ETL (Extract, Transform, Load) processes, it's essential to assess the quality and structure of the data.Data profilingis the process of examining the data available in an existing data source and collecting statistics and information about that data. This practice helps in understanding the data's condition, identifying anomalies, and ensuring that the data conforms to the expected patterns.
Option A:Cross-validation
Rationale:Cross-validation is a statistical method used to estimate the skill of machine learning models. It is primarily used in predictive modeling to assess how the results of a statistical analysis will generalize to an independent dataset. While valuable in model evaluation, it doesn't address issues related to missing or incomplete data in ETL processes.
Option B:Data profiling
Rationale:Data profiling involves analyzing the data for accuracy and completeness. By performing data profiling, analysts can identify missing values, inconsistencies, and anomalies within the dataset. This process is crucial for diagnosing issues that arise during ETL operations, such as incomplete data loads or transformation errors.
Reference:
partners.comptia.org
Option C:Data integrity
Rationale:Data integrity refers to the accuracy and consistency of data over its lifecycle. While maintaining data integrity is crucial, identifying issues with missing or incomplete data requires an initial assessment through data profiling to pinpoint where integrity may have been compromised.
Option D:Data consistency
Rationale:Data consistency ensures that data remains uniform across different databases and systems. While consistency is vital, the immediate step in addressing missing data post-ETL is to profile the data to understand the scope and nature of the inconsistencies.
In summary, when faced with incomplete or missing data after ETL jobs, initiating an investigation with data profiling is the most effective approach. This process will provide insights into the data's current state, allowing for targeted actions to resolve any identified issues.
質問 # 188
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. Use permissions to ensure users only see certain versions of the submissions.
- B. Confirm the dashboard is adhering to the corporate style guide.
- C. Display the version number next to each submission on the dashboard.
- D. Present a data refresh date at the top of the dashboard.
正解：C
解説：
Explanation
A static report is a type of report that shows a snapshot of data at a specific point in time. A static report does not change or update automatically, unless the data source is refreshed or the report is regenerated. A static report is suitable for situations where the data does not change frequently or where historical data is needed for comparison or analysis. In this case, the 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. This means that the data analyst does not need to show real-time or dynamic data, but rather a fixed and accurate view of the sales data for the second quarter. Therefore, a static report would be the best way to meet this stakeholder requirement.
Therefore, the correct answer is A. References: What are Static Reports? | Sisense, Static vs Dynamic Reports
- What's The Difference? | datapine
質問 # 189
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.
正解：D
解説：
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.
質問 # 190
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
正解：B
解説：
This is because an INNER JOIN is a type of join that combines two tables based on a matching condition and returns only the rows that satisfy the condition. An INNER JOIN can be used to merge data from different tables that have a common column or a key, such as customer ID or order ID. To perform an INNER JOIN of the customer and order tables, we can use the following SQL statement:
This statement will select all the columns (*) from both tables and join them on the customer ID column, which is the common column between them. The result of this statement will be a new table that has seven rows and eight columns, as shown below:
The reason why there are seven rows and eight columns in the result table is because:
* There are seven rows because there are six customers and six orders in the original tables, but only five customers have matching orders based on the customer ID column. Therefore, only five rows will have data from both tables, while one row will have data only from the customer table (customer 5), and one row will have no data at all (null values).
* There are eight columns because there are four columns in each of the original tables, and all of them are selected and joined in the result table. Therefore, the result table will have four columns from the customer table (customer ID, first name, last name, and email) and four columns from the order table (order ID, order date, product, and quantity).
質問 # 191
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?
- A. INNER: 9 rows; LEFT: 6 rows
- B. INNER: 6 rows; LEFT: 9 rows
- C. INNER: 9 rows; LEFT: 15 rows
- D. INNER: 15 rows; LEFT: 9 rows
正解：C
質問 # 192
A database administrator needs to ensure only approved users can access specific database tables to perform financial functions. Which of the following is the best access control method for the administrator to use?
- A. Group-based
- B. Rule-based
- C. Role-based
- D. Discretionary
正解：C
解説：
Comprehensive and Detailed In-Depth
Access control is a critical aspect of database security. The best method for controllingwho can access financial databased onjob rolesisRole-Based Access Control (RBAC).
Option A (Role-based):Correct.RBAC assigns permissions based on a user's role within the organization (e.g., accountants can access financial data, but sales representatives cannot).
Option B (Rule-based):Incorrect. Rule-Based Access Control (RuBAC) enforces policies based on rules, such as time restrictions, rather than user roles.
Option C (Discretionary):Incorrect. Discretionary Access Control (DAC) allows individual users to grant permissions, which can lead to security risks in financial systems.
Option D (Group-based):Incorrect. Group-Based Access Control (GBAC) assigns permissions based on user groups, but RBAC provides finer control for financial functions.
質問 # 193
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?
- A. The new layout has the lowest conversion rates in the United Kingdom.
- B. In general, users who visit the new website are more likely to make a purchase.
- C. In France, the increase in conversion from the new layout was not significant.
- D. In Germany, the increase in conversion from the new layout was not significant.
正解：B
解説：
The conclusion that is accurate at a 95% confidence interval is that in general, users who visit the new website are more likely to make a purchase. A 95% confidence interval means that we are 95% confident that the true difference between the two groups lies within a certain range of values. To calculate the 95% confidence interval, we can use the following formula:
CI = (p1 - p2) ± 1.96 * sqrt(p * (1 - p) * (1/n1 + 1/n2))
where p1 and p2 are the conversion rates for the test and control groups, respectively, p is the pooled conversion rate, n1 and n2 are the sample sizes for the test and control groups, respectively, and 1.96 is the z- score for a 95% confidence level.
Using this formula, we can calculate the 95% confidence interval for each country as follows:
Country | p1 | p2 | n1 | n2 | p | CI United States | 0.12 | 0.11 | 2000 | 2000 | 0.115 | (-0.006, 0.026) Germany |
0.06 | 0.04 | 1000 | 1000 | 0.05 | (-0.002, 0.042) United Kingdom | 0.09 | 0.07 | 1500 | 1500 | 0.08 | (-0.003,
0.053) France | 0.08 | 0.08 | 1200 | 1200 | 0.08 | (-0.024, 0.024) Canada | 0.05 | 0.03 | 800 | 800 | 0.04 | (-0.005,
0.045)
We can see that for all countries except France, the confidence interval does not include zero, which means that the difference between the test and control groups is statistically significant at a 95% confidence level.
However, this does not mean that the difference is practically significant or meaningful for the business. To measure the practical significance, we can use another metric called lift, which is the percentage increase or decrease in conversion rate from the control group to the test group.
Lift = (p1 - p2) / p2
Using this formula, we can calculate the lift for each country as follows:
Country | Lift United States | 9.09% Germany | 50% United Kingdom |28.57% France|0% Canada|66.67% We can see that Canada has the highest lift, followed by Germany and United Kingdom, while France has no lift at all.
To answer the question, we need to look at the overall conversion rate for both groups across all countries, not just for each country individually. To do this, we can use a weighted average of the conversion rates for each country, based on their sample sizes.
Weighted average = (p1 * n1 + p2 * n2) / (n1 + n2)
Using this formula, we can calculate the weighted average conversion rate for both groups as follows:
Group|Weighted average Test|0.084 Control|0.072
We can see that the test group has a higher weighted average conversion rate than the control group by about
16%. We can also calculate the confidence interval and lift for the overall difference as follows:
CI = (p1 - p2) ± 1.96 * sqrt(p * (1 - p) * (1/n1 + 1/n2)) = (0.084 - 0.072) ± system The assistant's response has exceeded the maximum character limit of [500]. Please shorten your response or split it into multiple messages.
質問 # 194
What feature varies on a bubble chart but not on a scatter plot?
- A. Size
- B. Color
- C. Y-position
- D. X-position
正解：A
質問 # 195
Which of the following concepts should be applied if a data set with 40 fields needs to be pared down to 20 fields and contains similar data across multiple fields?
- A. Standardization
- B. Duplication
- C. Compliance
- D. Consolidation
正解：D
質問 # 196
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