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NEW QUESTION # 26
Exhibit.
Refer to the exhibit.
A data architect is loading two tables into a data model from a SQL database. These tables are related on key fields CustomerlD and Customer Key.
Which script should the data architect use?
Answer: B
Explanation:
In the scenario, two tables (OrderDetails and Customers) are being loaded into the Qlik Sense data model, and these tables are related via the fields CustomerID and CustomerKey. The goal is to ensure that the relationship between these two tables is correctly established in Qlik Sense without creating synthetic keys or data inconsistencies.
* Option A:Renaming CustomerKey to CustomerID in the OrderDetails table ensures that the fields will have the same name across both tables, which is necessary to create the relationship. However, renaming is done using AS, which might create an issue if the fields in the original data source have a different meaning.
* Option B and C:These options use AUTONUMBER to convert the CustomerKey and CustomerID to unique numeric values. However, using AUTONUMBER for both fields without ensuring they are aligned correctly might lead to incorrect associations since AUTONUMBER generates unique values based on the order of data loading, and these might not match across tables.
* Option D:This approach loads the tables with their original field names and then uses the RENAME FIELD statement to align the field names (CustomerKey to CustomerID). This ensures that the key fields are correctly aligned across both tables, maintaining their relationship without introducing synthetic keys or mismatches.
NEW QUESTION # 27
A data architect needs to retrieve data from a REST API. The data architect needs to loop over a series of items that are being read using the REST connection.
What should the data architect do?
Answer: D
Explanation:
When retrieving data from a REST API, particularly when the dataset is large or the data is segmented across multiple pages (which is common in REST APIs), the REST Connector in Qlik Sense needs to be configured to handle pagination.
Pagination is the process of dividing the data retrieved from the API into pages that can be loaded sequentially or as required. Qlik Sense's REST Connector supports pagination by allowing the dataarchitect to set parameters that will sequentially retrieve each page of data, ensuring that the complete dataset is retrieved.
Key Steps:
* REST Connector Setup: Configure the REST connector in Qlik Sense and specify the necessary API endpoint.
* Pagination Mechanism: Use the built-in pagination mechanism to define how the connector should retrieve the subsequent pages (e.g., by using query parameters like page or offset).
NEW QUESTION # 28
Exhibit
Refer to the exhibit.
The salesperson ID and the office to which the salesperson belongs is stored for each transaction. The data model also contains the current office for the salesperson. The current office of the salesperson and the office the salesperson was in when the transaction occurred must be visible. The current source table view of the model is shown. A data architect must resolve the synthetic key.
How should the data architect proceed?
Answer: C
Explanation:
In the provided data model, both the CurrentOffice and Transaction tables contain the fields SalesID and Office. This leads to the creation of a synthetic key in Qlik Sense because of the two common fields between the two tables. A synthetic key is created automatically by Qlik Sense when two or more tables have two or more fields in common. While synthetic keys can be useful in some scenarios, they often lead to unwanted and unexpected results, so it's generally advisable to resolve them.
In this case, the goal is to have both the current office of the salesperson and the office where the transaction occurred visible in the data model. Here's how each option compares:
* Option A: Comment out the Office in the Transaction table:This would remove the Office field from the Transaction table, which would prevent you from seeing which office the salesperson was in when the transaction occurred. This option does not meet the requirement.
* Option B: Inner Join the Transaction table to the CurrentOffice table:Performing an inner join would merge the two tables based on the common SalesID and Office fields. However, this might result in a loss of data if there are sales records in the Transaction table that don't have a corresponding record in the CurrentOffice table or vice versa. This approach might also lead to unexpected results in your analysis.
* Option C: Alias Office to CurrentOffice In the CurrentOffice table:By renaming the Office field in the CurrentOffice table to CurrentOffice, you prevent the synthetic key from being created. This allows you to differentiate between the salesperson's current office and the office where the transaction occurred. This approach maintains the integrity of your data and allows for clear analysis.
* Option D: Force concatenation between the tables:Forcing concatenation would combine the rows of both tables into a single table. This would not solve the issue of distinguishing between the current office and the office at the time of the transaction, and it could lead to incorrect data associations.
Given these considerations, the best approach to resolve the synthetic key while fulfilling the requirement of having both the current office and the office at the time of the transaction visible is toAlias Office to CurrentOffice in the CurrentOffice table. This ensures that the data model will accurately represent both pieces of information without causing synthetic key issues.
NEW QUESTION # 29
A startup company is about have its Initial Public Offering (IPO) on the New York Stock Exchange.
This startup company has used Qlik Sense for many years for data-based decision making for Sales and Marketing efforts, as well as for input into Financial Reporting. The startup's Qlik Sense applications use variables that have different values at different points in time.
Due to the increased rigor required in record keeping for public companies, these variables must be clearly recorded in the script reload logs of the Qlik Sense applications. These logs are refreshed daily.
The data architect wants to have the variables names, with their current values,writteninto the script reload logs. Which script statement should the data architect use?
Answer: C
Explanation:
In the scenario where the startup company is preparing for an IPO, there is an increased need for meticulous record-keeping, including the recording of variable values used in Qlik Sense applications. The TRACE statement is the most suitable option for logging variable values during script execution.
* TRACE: This statement writes custom messages, including variable values, to the script execution log.
By using TRACE, you can ensure that every reload log contains the names and current values of all relevant variables, providing the necessary transparency and traceability.
For example, the script could include:
TRACE $(VariableName);
This command will output the variable's value in the script log, ensuring it is recorded for audit purposes.
NEW QUESTION # 30
The data architect has been tasked with building a sales reporting application.
* Part way through the year, the company realigned the sales territories
* Sales reps need to track both their overall performance, and their performance in their current territory
* Regional managers need to track performance for their region based on the date of the sale transaction
* There is a data table from HR that contains the Sales Rep ID, the manager, the region, and the start and end dates for that assignment
* Sales transactions have the salesperson in them, but not the manager or region.
What is the first step the data architect should take to build this data model to accurately reflect performance?
Answer: A
Explanation:
In the provided scenario, the sales territories were realigned during the year, and it is necessary to track performance based on the date of the sale and the salesperson's assignment during that period. The IntervalMatch function is the best approach to create a time-based relationship between the sales transactions and the sales territory assignments.
* IntervalMatch: This function is used to match discrete values (e.g., transaction dates) with intervals (e.
g., start and end dates for sales territory assignments). By matching the transaction dates with the intervals in the HR table, you can accurately determine which territory and manager were in effect at the time of each sale.
Using IntervalMatch, you can generate point-in-time data that accurately reflects the dynamic nature of sales territory assignments, allowing both sales reps and regional managers to track performance over time.
NEW QUESTION # 31
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