skills?
• data worker
• data scientist
• data analyst
• data engineer
Which of these is an example of master data management rules?
• Each contact name shall include first name. last name. and middle
initial.
• Each department name will include the department number.
• all of these answers
• All two letter abbreviations for States/Regions/Provinces names
must be in all caps.
Which statements are required in a basic SQL query?
• Select
From
Where
• Select
From
• Select
From
Order By
• Select
• Where
What is part of the data cleaning process?
• removing invalid rows
• creating a slicer
• adding conditional formatting
• publishing the dashboard
, You have been tasked to study profitability of products. Which
questions should you attempt to answer at the start of the project?
• When did this become an issue?
What's the highest markup we can apply?
When can we start a major sales campaign to turn this around?
• Why are the salespeople not selling these products?
When did these products stop being profitable?
Why can't we just mark these products up in the hopes they are
profitable?
• What is the current cost of the products?
What is the current sales price of these products?
What is the current margin of these products?
Which of these products ever been profitable?
Which of the following options is an unlikely response to a data
request when a strong data governance plan is in place, and you
lack access to the data?
• The data owner accepts requests and will query the data you need
based on your parameters and share it to the appropriate
• location.
• The data owner helps you get set up with the system with the
appropriate permissions to access the data.
• The data is sensitive and company policy states no access can be
granted until other requirements and decisions are made.
• The data owner gives you their login information.
What shows by default on the tooltip for any visual you create?
• other visuals
• SQL syntax
• the fields used for the visual
• data source
Determining the count of values and basic transformation
requirements in a data set is known as
• data modeling
• data cleaning
• data profiling