CRM Analytics
What is dimension field?
Any field that contains non-numeric characters is identified as a dimension.
What can you do in a Data Prep recipe? A.Combine data from different datasets B.Extract and combine data from different datasets C.Build a dashboard D.Make a data chili
B
What can you do with data sync? A.Extract data from an external CSV file into CRM Analytics B.Extract Salesforce object data into CRM Analytics C.Explore a dataset D.Build a dashboard
B
What is the dataset containing the data you want to prepare or add fields to called? A.Dataflow dataset B.Recipe dataset C.Base dataset D.Source dataset
B
The Join Keys section (2) is where you choose how to match the data. How many key pairs can you choose up to?
5
What is Preparation in creating a dataset?
Preparation involves getting that data into a form that's meaningful to the people exploring it
There are two main stages in creating a dataset. What are they?
extraction and preparation
What is extraction in creating a dataset?
the process of bringing data into CRM Analytics
For preparation, which tool should we use?
use a recipe in the Data Prep visual interface tool.
What recipe information can you see in the Monitor tab of the data manager? A.The status of a recipe B.When a recipe was run C.The duration of a recipe D.All of the above
D
What can you do on the Edit Field Attributes page when uploading a CSV file to CRM Analytics? A.Change a field's name B.Change a field's type C.Change a field's format D.All of the above
D.All of the above
What type of data can a dataset contain? A.Demographic data from a CSV file B.Salesforce opportunity data C.Financial data from a billing system D.Any of the above or a combination
D.Any of the above or a combination
What are the two main steps for creating a dataset? A.Plan and map B.Build and explore C.Run and monitor D.Extract and prepare
D.Extract and prepare
There are two steps to planning a data journey, what are they?
Identifying your data requirements Mapping the data's journey through CRM Analytics
Why is it important to select the right root object when creating a recipe? A.Only data from the root object can be included in the dataset. B.The root object determines what related objects you can add to the dataset. C.The root object determines what app the dataset is saved in. D.The root object determines who can see the dataset.
B
What is a benefit of using a dataset? A.It can send data to an external system. B.It lets you explore large amounts of data quickly. C.It's hexagonal so it won't roll off your desk. D.It automatically cleanses data.
B.It lets you explore large amounts of data quickly.
Why is it important to prepare the data in a CSV file before you bring it into CRM Analytics? A.To add currency symbols to numeric fields B.To make sure CRM Analytics can set the field type correctly C.To remove column headers D.To make sure the content is interesting
B.To make sure CRM Analytics can set the field type correctly
There are various ways you can extract data into CRM Analytics. What are they?
Bring in external data through a CSV file using the CSV upload Bring it in using connectors or the CRM Analytics API
Where can you view the status of a CSV upload in CRM Analytics? A.The CRM Analytics home page B.The Setup menu C.The data manager D.The Create Dataset page
C.The data manager
What is a measure field?
CRM Analytics identifies a numerical field as a measure. A measure is a field that you can perform calculations on, such as sum and average
