Qlik Sense Data Architect (QSDA) Certification Exam Sample Questions
Welcome! Preparing for the Qlik Sense Data Architect (QSDA) certification exam can be a daunting task, but we're here to make it easier for you. Here are the sample questions that will help you become familiar with the Qlik QSDA exam style and structure. We encourage you to try our Demo Qlik Sense Data Architect Certification Practice Exam to measure your understanding of the exam structure in an environment that simulates the actual test environment.
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Qlik QSDA Sample Questions:
01. Finance wants a sales report that shows each sales rep's commission percentage as it was at the time each historical sale occurred, even though a rep's commission rate has changed several times since.
What kind of requirement is this?
a) A granularity requirement, since it only concerns how finely the fact table's rows are broken down.
b) A slowly changing dimension requirement, since a historical attribute value must be preserved as of the transaction date.
c) A simple overwrite requirement, since only the sales rep's single current commission rate needs to be stored going forward.
d) A connectivity requirement, since it depends on which connector is used to load the sales rep table itself.
02. A data architect at Bluepeak Retail reloads a data model and notices an unintended synthetic key has appeared between the Orders and Returns tables, formed from two shared fields that were not meant to be a joint key.
Which two actions would resolve this without discarding needed data?
(Choose two.)
a) Build a deliberate composite key by concatenating the shared fields, often wrapped in AutoNumber(), and drop the original fields.
b) Apply a WHERE NOT EXISTS clause when concatenating the Returns load against the existing QVD so only new or changed rows are appended.
c) Delete the Returns table from the data model entirely so no association can form.
d) Reload the tables in reverse order so the Orders table associates first.
e) Rename or comment out the accidental shared field in one of the two tables so only the intended key remains.
03. Compared with only reviewing an existing static report to infer requirements, why is interviewing the actual business users generally more reliable when scoping a new data model?
a) Interviews are generally faster to complete than reading through a single existing report line by line.
b) Interviews remove the need to profile the source data before the model is designed.
c) Interviews let the data architect skip validating the finished data model with users at a later stage.
d) Interviews surface the real decisions users need answered, not just an existing report's layout.
04. The merchandising director at Harrow Retail Group asks a data architect to build a new app so the team can "see how products are doing," without further detail.
What should the data architect do first to determine the primary requirement for the business users?
a) Begin building a star schema immediately, using every field found in the product and sales source tables without further discussion.
b) Meet with the director and the report's actual users to confirm which decisions the app must support.
c) Reuse the data model from an unrelated finance app, since it is already built, tested, and running in production.
d) Ask the IT department to decide which specific metrics the merchandising team should track for the new app.
05. A data architect validating a newly built Customers table wants to confirm that the field intended as the primary key is actually unique and complete before relying on it for associations.
Which validation step directly addresses this?
a) Check that the Customers table's tab name in the script matches the table name shown in the data model viewer.
b) Check that the Customers table was the first table loaded in the script sequence.
c) Check the key field for duplicate values and for nulls or blanks that would leave rows without a usable key.
d) Check that the Customers table sorts correctly when a user clicks the column header in a table chart.
06. Meridian Sports has a Products table where one field stores a comma-separated list of tags for each product, such as 'outdoor,footwear,clearance'.
The data architect wants one output row per product-tag pair.
Which function should be used on the tags field, without specifying a field-index argument?
a) ApplyMap
b) IntervalMatch
c) Crosstable
d) Subfield
07. Basalt Ridge Mining's data architect applies a WHERE clause to a source load that discards roughly a third of the incoming rows, then examines both RecNo() and RowNo() on the rows that remain.
Which two statements correctly describe the result?
(Choose two.)
a) RowNo() values on the surviving rows form an unbroken sequence starting at 1, because it only counts rows that actually make it into the load.
b) Applying a WHERE clause resets RecNo() back to 1 for the first surviving row, the same way it does for RowNo(), since any row-counting function restarts fresh once filtering removes rows.
c) RecNo() and RowNo() always return identical values, because both simply count rows in the order they are loaded.
d) Neither RecNo() nor RowNo() can be used together with a WHERE clause in the same LOAD statement.
e) RecNo() values on the surviving rows can have gaps, because it reflects each row's position in the original, unfiltered source.
08. A data architect builds a composite key by concatenating three long text fields together, producing a key value that is dozens of characters wide. Reload times and memory usage both increase noticeably once this key is added.
Which technique addresses this without changing what the key represents?
a) Split the composite key back into its three original text fields and load each one separately again, undoing the earlier consolidation into a single key.
b) Wrap the composite key in ApplyMap() so its value is looked up from a mapping table rather than stored directly on every row.
c) Wrap the key in AutoNumber(), replacing its long text values with compact sequential integers.
d) Apply NoConcatenate to the load that builds the composite key.
09. Emberwood Foods loads a RegionSales table, then later in the script loads a StoreSales table that happens to have identical field names and count to RegionSales.
The data architect wants StoreSales to remain a separate table rather than being appended onto RegionSales.
What should be added to the StoreSales load to prevent the automatic append?
a) The QUALIFY statement, applied before the StoreSales load
b) The NOCONCATENATE prefix
c) A CROSSTABLE prefix on the StoreSales load
d) A RESIDENT clause referencing RegionSales
10. After reloading a data model, a data architect notices that selecting a specific product on one sheet leaves several customers greyed out who should logically still have purchased that product.
What should the data architect check to validate whether the associations are behaving correctly?
a) Whether the key fields joining the affected tables are spelled, cased, and typed identically.
b) Whether the connection used to load the affected tables has since been renamed by an administrator.
c) Whether the app's dashboard sheets have been published to the correct stream or space.
d) Whether the fact table has been pre-aggregated to a coarser grain than the original source data.
Answers:
| Question: 1 | Answer: b | Question: 2 | Answer: a, e |
| Question: 3 | Answer: d | Question: 4 | Answer: b |
| Question: 5 | Answer: c | Question: 6 | Answer: d |
| Question: 7 | Answer: a, e | Question: 8 | Answer: c |
| Question: 9 | Answer: b | Question: 10 | Answer: a |
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