Qlik QSDA2021 Exam Practice Test Instant Access

Question 1

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.)

AUse dynamic script generation with variables

BDenormalize the schema

CMake sure any Ul variables are preceded by '='

DUse flags in the data model to simplify set analysis

ECreate master items for all complex expressions

Answer : A, D

Question 2

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?

A1 Load the existing data from the QVD
2. Load the new and updated data from the database without the rows that have just been loaded from the QVD and concatenate with data from the QVD
3. Load all records from the key field from the database and use an INNER JOIN on the previous table

B1. Load the existing data from the QVD
2. Load new and updated data from the database Concatenate with the table loaded from the QVD.
3. Create a separate table for the deleted rows and use a WHERE NOT EXISTS to remove these records

C1. Use a partial LOAD to load new and updated data from the database.
2. Load the existing data from the QVD without the updated rows that have just been loaded from the database and concatenate with the new and updated records
3. Use the PEEK function to remove the deleted rows

D1 Load the new and updated data from the database.
2. Load the existing data from the QVD without the updated rows that have just been loaded from the database and concatenate with the new and updated records.
3. Load all records from the key field from the database and use an INNER JOIN on the previous table.

Answer : D

Question 3

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?

A1 Generate a Cartesian JOIN between productid and date in a Combined table
2 RIGHT JOIN the Combined table with the Original table to populate the missing qty values
3. Use PREVIOUS() and RANGESUMQ functions to create the running quantity totals for each product for every month

B1. Generate a Cartesian JOIN between productid and date in a Combined table
2. LEFT JOIN the Combined table with the Original table to populate the missing qty values
3. Use PREVIOUSO and SUM() functions to create the running quantity totals for each product for every month

C1. Generate a Calendar table with all dates between the minimum and maximum date values in an Original table
2. RIGHT JOIN the Calendar table back to the Original table to populate the missing qty values
3. Use PEEK() and RANGECOUNTO functions to create the running quantity totals for each product for every month

D1 Generate a Calendar table with all dates between the minimum and maximum date values in an Original table
2. LEFT JOIN the Calendar table back to the Original table to populate the missing qty values

Answer : D

Question 4

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?

AOption A

BOption B

COption C

DOption D

Answer : C

Question 5

A global retailer has a large database in which millions of sales transactions are added per hour.

Each regional sales manager should only see details for customers in their region. After filtering based on criteria such as region, gender, and income level, sales managers should be able to see the most current detailed transactions.

What should a data architect do to meet these requirements?

ACreate an app for each sales manager with Qlik GeoAnalytics

BUse section access and include a service account in the table

CUse On-Demand App Generation (ODAG) and section access

DUse section access to restrict sales manager access by region

Answer : D

Question 6

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?

ARemove the LineNo field from Shipments and use the AutoNumber function on the

BCreate a composite key using OrdertD and LineNo

CRemove the LineNo field from both tables and use the AutoNumber function on the OrderlC field

DCreate a composite key using OrderlD and LineNo. and remove OrderlD and LineNo from Shipments

Answer : D

Question 7

Users of a published app report incomplete visualizations. The data architect checks the app multiple times and cannot replicate the error. The error affects only one team.

What is the most likely cause?

AAn Omit field has been applied

BSection access restricts too many records

CA security rule has been applied to the sheet object

DThe affected users were NOT added to the Section table

Answer : B

Section access restricts access to certain records, and if too many records are restricted, it can lead to incomplete visualizations. Source: Qlik

Section access is used to control access to the data in an app. If the section access settings are too restrictive, they can prevent certain users or teams from seeing all of the data they need, resulting in incomplete visualizations.

It is possible that the affected team has been assigned a section access that is too restrictive, preventing them from seeing all of the necessary data. This could be a misconfiguration or an oversight in the section access settings.

Qlik QSDA2021 Qlik Sense Data Architect Certification Exam Practice Test