Taylor wants to investigate how manufacturing, marketing, and sales expenditures impact overall profitability for her company.
Which of the following systems is the most appropriate?
Correct Answer:
C
A Data mart is too narrow, because Taylor needs data from across multiple divisions. OLAP is a broad term for analytical processing, and OLTP systems are transactional and not ideal for the task. Since Taylor is working with data across multiple different divisions, she will work with a Data warehouse.
The senior management team at a company receives a detailed sales report at the end of each quarter. The report is several pages long and includes data from dozens of offices across the country. The team wants a better way to get a quick snapshot of what is included in the report. Which of the following modifications would best meet this requirement?
Correct Answer:
C
The purpose of an executive summary is to provide a concise and informative overview of a longer report, allowing busy stakeholders to quickly understand the key points and findings without reading the entire document. This summary should highlight the most important data, conclusions, and recommendations, and is typically placed at the beginning of the report for easy access12.
In the context of a detailed sales report for senior management, including a summary section with observations and insights would allow the team to quickly grasp the performance across various offices and identify any significant trends or issues that require attention. This approach aligns with best practices for executive reporting, which emphasize the importance of clear and concise summaries that focus on essential KPIs and actionable insights12.
References: 1: Databox - How to Write an Executive Summary for a Report: Step By Step Guide with Examples 2: LinkedIn - Best Practices for Writing Executive Summaries
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?
Correct Answer:
B
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.
Each month an analyst needs to execute a data pull for the two prior months. Which of the following is the most efficient function for the analyst to use?
Correct Answer:
B
The most efficient function for an analyst to execute a data pull for the two prior months would be the Date function. This function allows for the manipulation and formatting of date values within a database. Using Date functions, an analyst can dynamically calculate the start and end dates for the previous two months, ensuring that the data pull is accurate and automated without manual intervention.
For example, SQL functions like DATEADD and DATEDIFF can be used to determine the exact range of dates needed for the data pull. These functions can calculate the first and
last day of the previous months relative to the current date, which is essential for monthly reporting and analysis.
References:
✑ Discussions on Stack Overflow suggest using SQL date functions
like DATEADD and DATEDIFF to dynamically extract data for previous months, which supports the use of Date functions12.
✑ The use of Date functions is also recommended for ensuring that the data pull is
not only efficient but also accurate, as it avoids potential errors associated with manual date entry3.
A survey asks participants to rate a company on a scale of one to ten. Which of the following best describes the rating variable?
Correct Answer:
B
The rating variable in a survey where participants rate a company on a scale of one to ten is best described as ordinal. This is because the ratings are ranked in order, with each number representing a position on a scale of satisfaction or quality. The numbers are not just labels (which would be nominal), nor do they represent a continuous spectrum (which would be continuous). They also do not fit the definition of categorical, as that implies non- ordered groups or categories. In an ordinal scale, the order of the values is significant and meaningful12.
References:
✑ Qualtrics explains that ordinal scales have answer sets that occur in a logical and systematic order, providing qualitative data.
✑ Zonka Feedback describes a 1 to 10 rating scale survey, indicating that the numbers represent a ranking from most negative to most positive experience, which aligns with the characteristics of an ordinal scale.
