Comprehensive and Detailed In-Depth
The RefNo column contains values that consist solely of digits without any alphabetical characters or special symbols, indicating a numeric data type.

The best format to deliver this report is D. A dashboard with filters at the top that the user can toggle.
A dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance1 A dashboard with filters at the top that the user can toggle would allow the user to easily and quickly access the information they need about various regions, products, and time periods, without having to navigate through multiple tabs, pages, or emails. A dashboard with filters would also enable the user to compare and contrast different views of the data and see how they change over time. A dashboard with filters would also be more interactive and engaging than a static or email report2 A workbook with multiple tabs for each region would not be an efficient way to deliver this report, because it would require the user to switch between different tabs to see the information they need. This would make it harder to compare and contrast different regions, products, and time periods, and also increase the risk of errors or confusion. A workbook with multiple tabs would also be less visually appealing and more cluttered than a dashboard3 A daily email with snapshots of regional summaries would not be an efficient way to deliver this report, because it would limit the user's ability to explore the data in depth and customize their view. A daily email would also be dependent on the frequency and timing of the email delivery, which might not match the user's needs or preferences. A daily email would also be more likely to be ignored or deleted than a dashboard that is always accessible.
A static report with a different page for every filtered view would not be an efficient way to deliver this report, because it would create a very long and cumbersome report that would be difficult to read and understand. A static report would also not allow the user to change or update the filters as they wish, or see how the data changes over time. A static report would also be less interactive and engaging than a dashboard.

Comprehensive and Detailed In-Depth
In this dataset, we can see an issue withincomplete or missing data:
Cameron Smith's "Date of Birth" field is Null, which indicatesmissing datathat needs to be filled in.
The format inconsistency in "Date of Birth" (e.g., "13-Jun" vs. "Dec 14") can also be problematic, requiring standardization.
Option A (Invalid data):Incorrect. The data is not necessarily invalid, but it is incomplete.
Option B (Redundant data):Incorrect. Redundant data means unnecessary duplication, which is not the case here.
Option C (Data outliers):Incorrect. Outliers refer to values that are extremely different from the rest of the dataset, which does not apply here.
Option D (Missing data):Correct.The "Date of Birth" field has missing values (e.g., "Null"), requiring data cleansing.

This is because duplicate data refers to data that is repeated or copied in a data set, which can affect the quality and validity of the analysis. A DISTINCT function is a type of function that removes duplicate values from a column or a table, leaving only unique values. For example, a DISTINCT function in SQL that can achieve this is:

The other data cleansing issues will not be fixed by applying a DISTINCT function. Here is why:
Missing data refers to data that is absent or incomplete in a data set, which can affect the accuracy and reliability of the analysis. A DISTINCT function does not help with missing data, because it does not fill in or impute the missing values.
Redundant data refers to data that is unnecessary or irrelevant for the analysis, which can affect the efficiency and performance of the analysis. A DISTINCT function does not help with redundant data, because it does not remove or filter out the redundant values.
Invalid data refers to data that is incorrect or inaccurate in a data set, which can affect the validity and reliability of the analysis. A DISTINCT function does not help with invalid data, because it does not validate or correct the invalid values.