Given the table below:
Which of the following variables can be considered inconsistent, and how many distinct values should the variable have?
Correct Answer:
B
The table provided shows an inconsistency in the ??Gender?? column, which lists three distinct
values: Male, Female, and College. This is inconsistent because ??College?? is not a gender category. The ??Gender?? column should only have two distinct values, typically ??Male?? and ??Female??, to accurately represent gender data. This error could be due to a data entry mistake or a misclassification during data collection.
In data analysis, it??s crucial to ensure that categorical variables like gender are consistent and correctly classified, as this can significantly impact the analysis results. Data cleaning processes often involve identifying and correcting such inconsistencies to maintain the integrity of the data set.
References:
✑ Data quality management principles emphasize the importance of consistency in data values, especially for categorical variables like gender1.
✑ Best practices in data cleaning include checking for and rectifying inconsistencies or misclassifications in data sets2.
✑ The importance of accurate data classification is highlighted in data analysis literature, as it directly affects the validity of the analysis results3.
An analyst is working with a data set that lists individuals' first and last names in separate columns. Which of the following processes should the analyst use to combine the first and last names into a single spreadsheet cell?
Correct Answer:
C
A data analyst is designing a dashboard that will provide a story of sales and determine which site is providing the highest sales volume per customer The analyst must choose an appropriate chart to include in the dashboard. The following data is available:
Which of the following types of charts should be considered?
Correct Answer:
D
The best type of chart to display the data is D. Include a column chart using the site and sales to average sales per customer.
A column chart is a good choice for comparing categorical data with numerical data, such as the site and sales to average sales per customer. A column chart can show the relative differences between the sites and highlight the site with the highest sales volume per customer. A column chart can also be easily labeled and formatted to make the data clear and understandable.
A line chart is not suitable for this data, because it is used to show trends or changes over time, which is not relevant for the site and sales to average sales per customer data. A line chart would also be confusing and misleading, as it would imply a connection or correlation between the sites that does not exist.
A pie chart is also not a good choice for this data, because it is used to show the proportion of a whole, not the comparison of different categories. A pie chart would also be difficult to read and interpret, as it would require labels or legends to identify the sites and their sales to average sales per customer. A pie chart would also not be able to show the exact values of the sales to average sales per customer, only their relative sizes.
A scatter chart is another inappropriate option for this data, because it is used to show the relationship or correlation between two numerical variables, not between a categorical and a numerical variable. A scatter chart would also be cluttered and unclear, as it would plot each site as a point on a coordinate plane, without any labels or axes. A scatter chart would also not be able to show the differences or rankings between the sites and their sales to average sales per customer.
A financial analyst is creating a daily billing report for a company. One night, the company's data warehouse did not update the data, which caused the data to be reported incorrectly the next day. Which of the following documentation elements should the analyst add to catch this error?
Correct Answer:
B
A data refresh is a documentation element that indicates when the data was last updated or refreshed from the source. A data refresh can help the analyst to catch the error of the data warehouse not updating the data, as it will show a discrepancy between the expected and actual date of the data update. A data refresh can also help the users of the report to verify the timeliness and accuracy of the data, and to avoid making decisions based on outdated or incorrect data
Which of the following is a characteristic of a relational database?
Correct Answer:
C
It is structured in nature. This is because a relational database is a type of database that organizes data into tables, which consist of rows and columns. A relational database is structured in nature, which means that the data has a predefined schema or format, and follows certain rules and constraints, such as primary keys, foreign keys, or referential integrity. A relational database can be used to store, query, and manipulate data using a structured query language (SQL). The other characteristics are not true for a relational database. Here is why:
It utilizes key-value pairs. This is not true for a relational database, because key-value pairs are a way of storing data that associates each value with a unique key, such as an identifier or a name. Key-value pairs are typically used in non-relational databases, such as NoSQL databases, which do not have tables, rows, or columns, but rather store data in various formats, such as documents, graphs, or columns.
It has undefined fields. This is not true for a relational database, because fields are another name for columns in a table, which define the attributes or properties of each row or record in the table. Fields have defined names, types, and lengths in a relational database, which specify the format and size of the data that can be stored in each field.
It uses minimal memory. This is not true for a relational database, because memory is the amount of space or storage that is used by a database to store and process data. Memory usage depends on various factors, such as the size, complexity, and number of tables and queries in a relational database. A relational database can use a lot of memory if it has many tables with many rows and columns, or if it performs complex or frequent queries on the data.
