A data architect executes the following script:
Which values does the OrderDate field contain after executing the script?
In the script provided, the alt() function is used to handle various date formats. The alt() function in Qlik Sense evaluates a list of expressions and returns the first valid expression. If none of the expressions are valid, it returns the last argument provided (in this case, '31/12/2022').
Step-by-step breakdown:
The alt() function checks the Date field for three different formats:
YYYYMMDD
YYYY/MM/DD
DD/MM/YYYY
If none of these formats match the value in the Date field, the default date '31/12/2022' is assigned.
Values in the Date field:
20210131: Matches the first format YYYYMMDD.
2020/01/31: Matches the second format YYYY/MM/DD.
31/01/2019: Matches the third format DD/MM/YYYY.
9999: Does not match any of the formats, so the alt() function returns the default value '31/12/2022'.
A company needs to analyze daily sales data from different countries. They also need to measure customer satisfaction of products as reported on a social media website. Thirty (30) reports must be produced with an average of 20,000 rows each. This process is estimated to take about 3 hours.
Which option should the data architect use to build this solution?
In this scenario, the company needs to analyze daily sales data from different countries and also measure customer satisfaction of products as reported on a social media website. This suggests that the data is likely coming from different sources, including possibly an API or a web service (social media website).
The Qlik REST Connector is the appropriate tool for this job. It allows you to connect to RESTful web services and retrieve data directly into Qlik Sense. This is especially useful for integrating data from various online sources, such as social media platforms, which typically expose data via REST APIs. The REST Connector enables the extraction of large datasets from these sources, which is necessary given the requirement to produce 30 reports with an average of 20,000 rows each.
Microsoft SQL Server is not suitable for fetching data from web services or social media platforms.
Qlik GeoAnalytics is used for mapping and geographical data visualization, not for connecting to RESTful services.
Mailbox IMAP is for connecting to email servers and is not applicable to the data extraction needs described here.
Thus, Qlik REST Connector is the correct answer for this scenario.
A company's analytics team is migrating from QlikView to Qlik Sense. During the transition there is an opportunity to improve overall reporting.
Which set of criteria must the data architect consider while planning for the migration?
During the transition from QlikView to Qlik Sense, the analytics team has the opportunity to improve the overall reporting. To ensure a smooth migration while optimizing the new environment, the data architect needs to consider several key factors.
Option C is the best choice because it encompasses the essential aspects of a migration project:
QlikView Archival:
Archiving QlikView applications is crucial to ensure that historical data and applications are preserved and can be referenced if needed in the future. This step is important to maintain continuity and provide a fallback option if required during the transition.
Source Data Architecture:
Understanding the existing source data architecture is critical to ensure that the new Qlik Sense applications can seamlessly connect to the data sources. This also helps in identifying opportunities to optimize or re-architect the data pipelines for better performance in Qlik Sense.
Load Script:
The load script from QlikView might need to be revised or optimized for Qlik Sense. It's important to ensure that the script is compatible and takes advantage of Qlik Sense's capabilities, such as improved data handling, better inline transformations, and enhanced scripting functions.
Data Model:
Reviewing and possibly redesigning the data model is essential during the migration. Qlik Sense's associative engine allows for more flexibility, and this is an opportunity to improve the data model for better performance, scalability, and user experience.
Business Use Case:
Understanding the business use case is vital to ensure that the new Qlik Sense applications meet the business requirements effectively. This includes making sure that the new reports and dashboards are aligned with the business goals and provide the necessary insights.
Qlik Migration Guide: When migrating from QlikView to Qlik Sense, it's important to consider not just the technical aspects but also the business implications and opportunities for improvement.
Qlik Documentation on Data Modeling and Load Script Optimization: These resources provide best practices on how to optimize load scripts and data models during migration to ensure smooth operation and better performance in Qlik Sense.
A data architect needs to develop three separate apps (Sales, Finance, and Operations). The three apps share numerous identical calculation expressions.
The goals include:
* Reducing duplicate script
* Saving time on expression modifications
* Increasing reusable Qlik developer assets.
The data architect creates a common script and stores it on a file server that Qlik Sense can access. How should the data architect complete the requirements?
When developing multiple Qlik Sense applications (Sales, Finance, Operations) that share numerous identical calculation expressions, it is crucial to have a centralized, reusable script to avoid redundancy, save time on modifications, and increase the reusability of the assets.
The best approach in Qlik Sense to achieve these goals is to use the Include script function. This function allows the data architect to reference a script file that is stored on a file server. The Include function will inject the contents of the external script file into the Qlik Sense script at the point where the Include statement is called. This means that all three apps (Sales, Finance, Operations) can include this common script, and any updates made to the script will automatically apply to all apps that include it.
This method provides a highly maintainable solution because:
No Duplicate Script: The shared logic is maintained in a single file, eliminating redundancy.
Ease of Modifications: Any changes made to the script are propagated to all applications that include it.
Reusable Assets: The script can be reused across different applications, enhancing efficiency and consistency.
Exhibit.
One of the data sources a data architect must add for a newly developed app is an Excel spreadsheet. The Region field only has values for the first record for the region. The data architect must perform a transformation so that each row contains the correct Region.
Which function should the data architect implement to resolve this issue?
The given Excel spreadsheet has a Region field where the region value is only specified for the first record within each region. The data architect needs to fill in the missing region values for subsequent rows.
Previous() Function: The Previous() function in Qlik Sense returns the value of the expression from the previous row. In this case, it can be used to fill down the Region values so that each row contains the correct region information.
Implementation: The script can be designed to check if the current row's Region value is missing (null). If it is missing, the script can assign the value from the previous row using the Previous() function.
LOAD
If(IsNull(Region), Previous(Region), Region) AS Region,
...
This logic fills in the missing Region values with the value from the preceding row, which effectively resolves the issue shown in the spreadsheet.
