EMT Practice Test

1. Question Content...

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Question1: Refer to the exhibit.

Refer to the exhibits.
The first table shows the source table (Original table).
This data represents the stocks stored every month for each product:
* The relevant fields are productid, qty, and date.
* The date field represents the calendar months using
* The qty field shows the product stock fluctuation from the current month versus the previous month. If there is no fluctuation between months, there are no new entries in the table.
The second table shows a Pivot table visualization the data analyst needs to create in the app displaying per each product the monthly trend of available stock.
For performance reasons, the data analyst requests the data architect to calculate the running stock quantity of each product for every month in the script.
Which approach should the data architect use?

Question2: Refer to the exhibit.

A data architect is loading the tables and a synth key is generated.
How should the data architect resolve the synthetic key?

Question3: Refer to the exhibit.

A Human Resources Director needs an app to analyze organizational structure. The Directory is particularly interested in the longest levels of line management.
Two table loads are required. Both use the same basic structure.

Which two table load prefixes are needed?

Question4: Refer to the exhibit.

A data architect is creating an app using three tables. After executing the script, a warning displays Which two steps should the data architect do to resolve this warning? (Select two.)

Question5: Multiple department fields in a dataset require a description
A data architect needs to add the department descriptions or a default value when the department does NOT have a description Which strategy should the data architect use to meet these requirements?

Question6: A data architect needs to write the expression for a measure on a KPI to show the sales person with the highest sales The sort order of the values of the fields is unknown When two or more sales people have sold the same amount, the expression should return all of those sales people Which expression should the data architect use?

Question7: A data architect needs to upload data from ten different sources, but only if there are any changes after the last reload When data is updated, a new file is placed into a folder mapped to E A439926003 The data connection points to this folder.
The data architect plans a script which will:
1. Verify that the file exists
2. If the file exists, upload it Otherwise, skip to the next piece of code The script will repeat this subroutine for each source. When the script ends, all uploaded files will be removed with a batch procedure.
Which option should the data architect use to meet these requirements?

Question8: Refer to the exhibit.

The Section Access security table for an app is shown. User ABC\PPP opens a Qlik Sense app with a table using the field called LEVEL on one of the table columns.
What is the result?

Question9: A data architect needs to create an app that combines employee data from the Sales system and the Human Resources (HR) system.
These systems identify employees differently Employees in the HR system are identified with an alpha-numeric key Employees in the Sales system are identified using an integer key.
The Human Resources manager creates a table that maps these keys to another, called Associations.
The resultant data model must meet the following requirements:
* Associations must be valid
* The model must be optimized for performance
* The option must support multiple tables added
Which solution should the data architect use to meet these requirements?

Question10: A data architect needs to revise an existing app.
The number of data rows has grown rapidly recently. While the app is in production, users are becoming increasingly unhappy about the response times when they make selections Which two methods should be used to improve performance? (Select two.)

Question11: A data architect of an organization that has implemented Qlik Sense on Windows needs to load large amounts of data from a database that is continuously updated New records are added, and existing records get updated and deleted. Each record has a LastModified field.
All existing records are exported into a QVD file. The data architect wants to load the records into Qlik Sense efficiently.
Which steps should the data architect take to meet these requirements?

Question12: A data architect wants to combine data on present and historic sales performance. The historic data is stored in a de-normalized archive, and the present data is maintained in a database. The output must be contained in a single table.
Which script should the data architect use?
A)

B)

C)

D)

Question13: A data architect executes the following script.

Which values does the OrderDate field contain after executing the script?

Question14: Refer to the exhibit.

A data architect must classify each product into a price group. The price groups must be the same width by default and allow users to dynamically change the width of the bucket during analysis.
Which feature should the data architect use to meet these requirements?

Question15: A data architect needs to develop a script to export tables from a model based upon rules from an independent file. The structure of the text file with the export rules is as follows:

These rules govern which table in the model to export, what the target root filename should be, and the number of copies to export.
The TableToExport values are already verified to exist in the model.
In addition, the format will always be QVD, and the copies will be incrementally numbered.
For example, the Customer table would be exported as:
What is the minimum set of scripting strategies the data architect must use?

Question16: A company has a stream with multiple apps One of the apps is a multi-regional sales app.
A data architect must set up security for users to access the stream, enter the app, and view specific sheets and data.
Which features should the data architect use to meet these requirements?

Question17: A company generates 1 GB of ticketing data daily. The data is stored in multiple tables Business users need to see trends of tickets processed for the past. 2 years Users very rarely access the transaction-level data for a specific date. Only the past 2 years of data must be loaded which is 720 GB of data Which method should a data architect use to meet these requirements?