Duplicate Data.
While invalid, redundant, or missing data are all valid concerns, data about people exists in two of the six systems. As such, Jhon needs to account for duplicate data issues.

This is because a chi-squared test is a type of statistical method that tests the association or independence between two or more categorical variables, such as gender, race, or occupation. A chi-squared test can be used to compare the observed frequencies of the categories with the expected frequencies under the null hypothesis of no association or independence. For example, a chi-squared test can be used to determine if there is a relationship between smoking and lung cancer. The other statistical methods do not require two or more categorical variables. Here is why:
Simple linear regression is a type of statistical method that models the relationship between a continuous dependent variable and a continuous or categorical independent variable, such as height, weight, or education level. A simple linear regression can be used to estimate the slope and intercept of the best-fitting line that describes how the dependent variable changes with the independent variable. For example, a simple linear regression can be used to predict the weight of a person based on their height.
Z-test is a type of statistical method that tests the significance of the difference between a sample mean and a population mean, or between two sample means, when the population standard deviation or the sample sizes are large enough. A z-test can be used to compare the average scores of two groups of students on a standardized test.
Two-sample t-test is a type of statistical method that tests the significance of the difference between two sample means when the population standard deviation is unknown or the sample sizes are small. A two-sample t-test can be used to compare the average salaries of two groups of employees in different departments.

The invalid data type is the best description for the issue in which character values are mixed with integer values in a data set column. Invalid data type means that the data does not match the expected or required format or structure for a given variable or attribute. For example, if a column is supposed to store numerical values, but some rows contain text values, then those rows have an invalid data type. References: CompTIA Data+ Certification Exam Objectives, page 10

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.

Create a dashboard with views for team, individuals, and management. Configure permissions to control access. This is because a dashboard is a type of visualization that displays multiple charts or graphs on a single page, usually to provide an overview or summary of some data or information. A dashboard can be used to provide visibility of current sales numbers, pipeline, and team performance by showing different metrics and indicators related to these aspects. By creating a dashboard with views for team, individuals, and management, the analyst can customize the content and layout of the dashboard for different audiences and purposes. By configuring permissions to control access, the analyst can ensure that the confidential information, such as individuals' earned commissions and projected commissions based on sales, is only visible to the authorized users. The other ways are not the best way to provide this visibility. Here is why:
Creating a dashboard displaying a data refresh date so users know the current sales numbers and configuring permissions to control access would not be sufficient to provide visibility of pipeline and team performance, as well as individuals' earned commissions and projected commissions based on sales. The dashboard would only show the current sales numbers and the date when the data was updated, which would not give a comprehensive or detailed view of the sales situation.
Creating a dashboard for sales numbers, pipeline, and team and individual performance for the management team would not be appropriate to provide visibility for the sales team, as they would not have access to the dashboard or the information they need. The dashboard would only be available for the management team, which would limit the transparency and collaboration among the sales team members.
Creating a dashboard with filters for the overall team, individuals, and management would not be secure to provide visibility of confidential information, such as individuals' earned commissions and projected commissions based on sales. The dashboard would allow users to filter and see the data they want, which could expose sensitive or personal information to unauthorized users.