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The Qlik Sense Data Architect Certification Exam measures your ability to identify requirements for data models, design and build data models, and validate the data. This exam is platform neutral, which means that the content applies to both the client managed and SaaS editions of Qlik Sense. This exam has 50 multiple-choice questions to answer in 2 hours.

Practical experience developing multiple production-quality applications in Qlik Sense

Ability to write Qlik Sense LOAD scripts and validate data

Basic understanding of Extract-Transform-Load (ETL)

Create and use connectors to various data sources

Understand the QVD layer and architecture of the Qlik platform

Ability to architect data to provide optimal performance

Familiar with SQL and relational databases

Determine primary requirements with business users.

Given a scenario, choose stakeholders.

Given a scenario, determine metrics and levels of granularity and aggregation.

Determine dimensionality and need for slowly changing dimensionality support.

Given a scenario, determine the appropriate level of security.

Given a scenario, determine the data sources and connectors needed.

Determine the appropriate method to create connections for data sources.

Given a scenario, determine the measures and attributes from each data source.

Given a scenario, identify the appropriate type of data model.

Determine the correct method to optimize the data model for Qlik Sense.

Determine the correct method to implement data structures efficiently.

Determine the correct method to build data content based on requirements.

Analyze and evaluate null and blank data handling required to support filtering.

Determine the correct method to document Data Load scripts.

Determine the correct method for date handling techniques.

Determine the correct method to perform script organization and cleansing.

Analyze relevant variables to build scripts for incremental loading for extract layer.

Given a scenario, determine the appropriate method to validate and test scripts.

Given a scenario, determine the appropriate method to validate and test data.

1. The data model from an existing Qlik Sense app needs to be reused in another Qlik Sense app.

Which load strategy should a data architect use to transfer this data in the most efficient way?

A. Preceding load

B. QVD load

C. Binary load

D. Generic load

Answer: C

2. A data architect is working on a time and expense app for an organization that has Sales, Marketing, and Finance departments.

Department managers should only be able to view the data for their department's team members.

Where should the data architect apply this security restriction?

A. Expression editor

B. Qlik Management Console

C. Data manager

D. Data load editor

Answer: D

3. Stock levels are stored online in a system that keeps information for the current period only.

What should the data architect do to enable analysis of the trends of the stock levels?

A. Create an app for each period and use a binary load task to create a single app

B. Create an app for each period as it changes and use document chaining

C. Use On-Demand App Generation (ODAG) to create new apps from the selected period

D. Capture the periodic information in an incremental QVD file for use in an app

Answer: D

4. A data architect is developing an app that will generate QVDs for multiple business analysts. The field naming conventions on the source data are NOT business friendly. For every table loaded, multiple fields will require a name change.

An Excel file is maintained centrally that lists all source data field names and the appropriate names as they should appear in the QVDs

Which strategy should the data architect use to meet these requirements?

A.Use the Rename function and a mapping load

B.Create master items using business-friendly names

C.Use the Alias function and a mapping load

D.Load in the Excel file as a data island and use the Peek function

Answer: A

5. A data architect plans to build an app that contains geographically diverse data that must be specific to user run-time selections. The source contains transactional data. The app must have minimal impact on already limited server resources.

Which approach should the data architect use?

A.Loop and Reduce

B.QVDs

C.In-memory

D.ODAG

Answer: B