QSDA2024 Dumps - Qlik Sense Data Architect Certification Exam - 2024

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<p>QSDA2024</p><p>Exam Name: Qlik Sense Data Architect Certification</p><p>Exam - 2024</p><p>Full version: 50 Q&As</p><p>Full version of QSDA2024 Dumps</p><p>Share some QSDA2024 exam dumps below.</p><p>1. Load the master calendar as DischargeCalendar and alias the fields to reflect they are for</p><p>Discharge</p><p>2. A company generates l GB of ticketing data daily. The data is stored in multiple tables.</p><p>Business users need to see trends of tickets processed for the past 2 years. Users very rarely</p><p>1 / 13</p><p>https://www.certqueen.com/QSDA2024.html</p><p>access the transaction-level data for a specific date. Only the past 2 years of data must be</p><p>loaded, which is 720 GB of data.</p><p>Which method should a data architect use to meet these requirements?</p><p>A. Load only 2 years of data in an aggregated app and create a separate transaction app for</p><p>occasional use</p><p>B. Load only 2 years of data and use best practices in scripting and visualization to calculate</p><p>and display aggregated data</p><p>C. Load only aggregated data for 2 years and use On-Demand App Generation (ODAG) for</p><p>transaction data</p><p>D. Load only aggregated data for 2 years and apply filters on a sheet for transaction data</p><p>Answer: C</p><p>Explanation:</p><p>In this scenario, the company generates 1 GB of ticketing data daily, accumulating up to 720</p><p>GB over two years. Business users mainly require trend analysis for the past two years and</p><p>rarely need to access the transaction-level data. The objective is to load only the necessary</p><p>data while ensuring the system remains performant.</p><p>Option C is the optimal choice for the following reasons:</p><p>Efficiency in Data Handling:</p><p>By loading only aggregated data for the two years, the app remains lean, ensuring faster load</p><p>times and better performance when users interact with the dashboard. Aggregated data is</p><p>sufficient for analyzing trends, which is the primary use case mentioned.</p><p>On-Demand App Generation (ODAG):</p><p>ODAG is a feature in Qlik Sense designed for scenarios like this one. It allows users to generate</p><p>a smaller, transaction-level dataset on demand. Since users rarely need to drill down into</p><p>transaction-level data, ODAG is a perfect fit. It lets users load detailed data for specific dates</p><p>only when needed, thus saving resources and keeping the main application lightweight.</p><p>Performance Optimization:</p><p>Loading only aggregated data ensures that the application is optimized for performance. Users</p><p>can analyze trends without the overhead of transaction-level details, and when they need more</p><p>detailed data, ODAG allows for targeted loading of that data.</p><p>Reference: Qlik Sense Best Practices: Using ODAG is recommended when dealing with large</p><p>datasets where full transaction data isn't frequently needed but should still be accessible.</p><p>Qlik Documentation on ODAG: ODAG helps in maintaining a balance between performance and</p><p>data availability by providing a method to load only the necessary details on demand.</p><p>3. Exhibit.</p><p>2 / 13</p><p>While performing a data load from the source shown, the data architect notices it is NOT</p><p>appropriate for the required analysis.</p><p>The data architect runs the following script to resolve this issue:</p><p>How many tables will this script create?</p><p>A. 1</p><p>B. 3</p><p>C. 4</p><p>D. 6</p><p>Answer: D</p><p>Explanation:</p><p>In this scenario, the data architect is using a GENERIC LOAD statement in the script to handle</p><p>the data structure provided. A GENERIC LOAD is used in Qlik Sense when you have data in a</p><p>key-value pair structure and you want to transform it into a more traditional table structure,</p><p>where each attribute becomes a column.</p><p>Given the input data table with three columns (Object, Attribute, Value), and the attributes in the</p><p>Attribute field being either color, diameter, length, or width, the GENERIC LOAD will create</p><p>separate tables based on the combinations of Object and each Attribute.</p><p>Here's how the GENERIC LOAD works:</p><p>For each unique object (circle, rectangle, square), the GENERIC LOAD creates separate tables</p><p>based on the distinct values of the Attribute field.</p><p>3 / 13</p><p>Each of these tables will contain two fields:</p><p>Object and the specific attribute (e.g., color, diameter, length, width).</p><p>Breakdown:</p><p>Table for circle:</p><p>Fields: Object, color, diameter</p><p>Table for rectangle:</p><p>Fields: Object, color, length, width</p><p>Table for square:</p><p>Fields: Object, color, length</p><p>Each distinct attribute (color, diameter, length, width) and object combination generates a</p><p>separate table.</p><p>Final Count of Tables:</p><p>The script will create 6 separate tables: one for each unique combination of Object and</p><p>Attribute.</p><p>Reference: Qlik Sense Documentation on Generic Load: Generic loads are used to pivot key-</p><p>value pair data structures into multiple tables, where each key (in this case, the Attribute field</p><p>values) forms a new column in its own table.</p><p>4. Perform a Join Load on the Encounters table to the Resident master calendar and alias the</p><p>date fields appropriately for the Discharge Date</p><p>B. 1. Load the master calendar</p><p>5. Sales managers need to see an overview of historical performance and highlight the current</p><p>year's metrics.</p><p>The app has the following requirements:</p><p>• Display the current year's total sales</p><p>• Total sales displayed must respond to the user's selections</p><p>Which variables should a data architect create to meet these requirements?</p><p>A)</p><p>B)</p><p>4 / 13</p><p>C)</p><p>D)</p><p>A. Option A</p><p>B. Option B</p><p>C. Option C</p><p>D. Option D</p><p>Answer: C</p><p>Explanation:</p><p>To meet the requirements of displaying the current year's total sales in a way that responds to</p><p>user selections, the correct approach involves using both SET and LET statements to define the</p><p>necessary variables in the data load editor.</p><p>Explanation of Option C:</p><p>SET vCurrentYear = Year(Today());</p><p>The SET statement is used here to assign the current year to the variable vCurrentYear. The</p><p>SET statement treats the variable as a text string without evaluation. This is appropriate for a</p><p>variable that will be used as part of an expression, ensuring the correct year is dynamically set</p><p>based on the current date.</p><p>LET vCurrentYTDSales = '=SUM({$} [Sales Amount])';</p><p>The LET statement is used here to assign an evaluated expression to the variable</p><p>vCurrentYTDSales. This expression calculates the Year-to-Date (YTD) sales for the current</p><p>year by filtering the Year field to match vCurrentYear. The LET statement ensures that the</p><p>expression inside the variable is evaluated, meaning that when vCurrentYTDSales is called in a</p><p>chart or KPI, it dynamically calculates the YTD sales based on the current year and any user</p><p>selections.</p><p>Key Points:</p><p>Dynamic Year Calculation: Year(Today()) dynamically calculates the current year every time the</p><p>script runs.</p><p>5 / 13</p><p>Responsive to Selections: The set analysis syntax {$} ensures that</p><p>the sales totals respond to user selections while still focusing on the current year's data.</p><p>Appropriate Use of SET and LET: The combination of SET for storing the year and LET for</p><p>storing the evaluated sum expression ensures that the variables are used effectively in the</p><p>application.</p><p>6. Delete the ProductID and OrderlD In the Shipments table</p><p>7. Delete the ShipmentID in the Shipments table</p><p>8. A data architect needs to acquire social media data for the past 10 years. The data architect</p><p>needs to track all changes made to the source data, include all relevant fields, and reload the</p><p>application four times a day.</p><p>What information does the data architect need?</p><p>A. A field with social media source, a set of key fields to sort out updated records, configure</p><p>reload task to load four times a day</p><p>B. A field with record creation time, a secondary key field to remove deleted records, configure</p><p>reload task to load four times a day</p><p>C. A field with ModificationTime, a primary key field to sort out updated records, insert and</p><p>append records, update records</p><p>D. A field with ModificationTime, a primary key field to sort</p><p>out updated records, insert and</p><p>update records, remove records</p><p>Answer: D</p><p>Explanation:</p><p>The scenario describes a need to track social media data over the past 10 years, capturing all</p><p>changes (inserts, updates, deletes) while reloading the data four times a day.</p><p>To manage this:</p><p>ModificationTime: This field is essential for tracking changes over time. It indicates when a</p><p>record was last modified, allowing the script to determine whether it needs to insert, update, or</p><p>delete records.</p><p>Primary Key Field: A primary key is crucial for uniquely identifying records. It enables the script</p><p>to match records in the source with those already loaded, facilitating updates and deletions.</p><p>Insert and Update Records: The script should handle both inserting new records and updating</p><p>existing ones based on the ModificationTime.</p><p>Remove Records: If records are deleted in the source, they should also be removed in the Qlik</p><p>Sense data model to maintain consistency.</p><p>This approach ensures that all changes in the social media data are accurately captured and</p><p>reflected in the Qlik Sense application.</p><p>6 / 13</p><p>9. Refer to the exhibit.</p><p>A company stores the employee data within a key composed of Country, UserlD, and</p><p>Department. These fields are separated by a blank space. The UserlD field is composed of two</p><p>characters that indicate the country followed by a unique code of two or three digits. A data</p><p>architect wants to retrieve only that unique code.</p><p>Which function should the data architect use?</p><p>A)</p><p>B)</p><p>C)</p><p>D)</p><p>A. Option A</p><p>B. Option B</p><p>C. Option C</p><p>D. Option D</p><p>Answer: A</p><p>Explanation:</p><p>In this scenario, the key is composed of three components: Country, UserID, and Department,</p><p>separated by spaces. The UserID itself consists of a two-character country code followed by a</p><p>7 / 13</p><p>unique code of two or three digits. The objective is to extract only this unique numeric code from</p><p>the UserID field.</p><p>Explanation of the Correct Function:</p><p>Option A: RIGHT(SUBFIELD(Key, ' ', 2), 3)</p><p>SUBFIELD(Key, ' ', 2): This function extracts the second part of the key (i.e., the UserID) by</p><p>splitting the string using spaces as delimiters.</p><p>RIGHT(..., 3): After extracting the UserID, the RIGHT() function takes the last three characters</p><p>of the string. This works because the unique code is either two or three digits, and the RIGHT()</p><p>function will retrieve these digits from the UserID.</p><p>This combination ensures that the data architect extracts the unique code from the UserID field</p><p>correctly.</p><p>10. Use a Mapping Load for the Employees table</p><p>11. Refer to the exhibit.</p><p>A data architect needs to build a dashboard that displays the aggregated sates for each sales</p><p>representative. All aggregations on the data must be performed in the script.</p><p>Which script should the data architect use to meet these requirements?</p><p>A)</p><p>8 / 13</p><p>B)</p><p>C)</p><p>9 / 13</p><p>D)</p><p>A. Option A</p><p>B. Option B</p><p>C. Option C</p><p>D. Option D</p><p>Answer: C</p><p>Explanation:</p><p>The goal is to display the aggregated sales for each sales representative, with all aggregations</p><p>being performed in the script. Option C is the correct choice because it performs the</p><p>10 / 13</p><p>aggregation correctly using a Group by clause, ensuring that the sum of sales for each</p><p>employee is calculated within the script.</p><p>Data Load:</p><p>The Data table is loaded first from the Sales table. This includes the OrderID, OrderDate,</p><p>CustomerID, EmployeeID, and Sales.</p><p>Next, the Emp table is loaded containing EmployeeID and EmployeeName.</p><p>Joining Data:</p><p>A Left Join is performed between the Data table and the Emp table on EmployeeID, enriching</p><p>the data with EmployeeName.</p><p>Aggregation:</p><p>The Summary table is created by loading the EmployeeName and calculating the total sales</p><p>using the sum([Sales]) function.</p><p>The Resident keyword indicates that the data is pulled from the existing tables in memory,</p><p>specifically the Data table.</p><p>The Group by clause ensures that the aggregation is performed correctly for each</p><p>EmployeeName, summarizing the total sales for each employee.</p><p>Key Qlik Sense Data Architect</p><p>Reference: Resident Load: This is a method to reuse data that is already loaded into the app’s</p><p>memory. By using a Resident load, you can create new tables or perform calculations like</p><p>aggregation on the existing data.</p><p>Group by Clause: The Group by clause is essential when performing aggregations in the script.</p><p>It groups the data by specified fields and performs the desired aggregation function (e.g., sum,</p><p>count).</p><p>Left Join: Used to combine data from two tables. In this case, Left Join is used to enrich the</p><p>sales data with employee names, ensuring that the sales data is associated correctly with the</p><p>respective employee.</p><p>Conclusion: Option C is the most appropriate script for this task because it correctly performs</p><p>the necessary joins and aggregations in the script. This ensures that the dashboard will display</p><p>the correct aggregated sales per employee, meeting the data architect’s requirements.</p><p>12. Load the Sales table and alias the SalesPersonID and RegionalAcctMgrlD fields as</p><p>EmployeelD</p><p>Answer: C</p><p>Explanation:</p><p>In the provided scenario, the data architect needs to create a data model that supports various</p><p>analyses, including total sales for each customer, total sales by state, identifying customers with</p><p>11 / 13</p><p>no sales, and displaying the names of salespersons and regional account managers.</p><p>Here’s why Option C is the correct choice:</p><p>Loading the Sales Table: The Sales table contains key information related to sales transactions,</p><p>including SaleID, CustomerID, Amount, SaleDate, SalesPersonID, and RegionalAcctMgrID.</p><p>This table must be loaded first as it will be central to the analysis.</p><p>Loading the Customers Table: The Customers table includes customer details such as CustID,</p><p>CustName, Address, City, State, and Zip. Loading this table and linking it to the Sales table via</p><p>the CustomerID field allows you to perform analyses such as total sales per customer and total</p><p>sales by state. Importantly, loading the customers separately will also allow the identification of</p><p>customers without any sales.</p><p>Loading the Employees Table Twice: The Employees table must be loaded twice because it is</p><p>used to look up two different roles in the sales process: the SalesPersonID and the</p><p>RegionalAcctMgrID.</p><p>When loading the table twice:</p><p>The first instance of the Employees table will be used to map the SalesPersonID to</p><p>EmployeeName.</p><p>The second instance will be used to map the RegionalAcctMgrID to EmployeeName.</p><p>Aliasing the EmployeeID field appropriately in each instance is crucial to prevent creating</p><p>synthetic keys and to ensure the correct association with the roles in the sales process.</p><p>This approach ensures that the data model will correctly support all the required analyses,</p><p>including identifying customers without sales, which is crucial for meeting the business</p><p>requirements.</p><p>Option A and Option B propose using a mapping load and ApplyMap, which can complicate the</p><p>model and does not directly address all the business requirements.</p><p>Option D involves aliasing fields in a way that could create unnecessary complexity and might</p><p>not accurately reflect the relationships in the data.</p><p>Thus, Option C is the correct answer as it best meets the requirements while maintaining a clear</p><p>and functional data model.</p><p>13. Load the Encounters table</p><p>D. 1. Load the Encounters table</p><p>14. Load the existing data from the QVD without the updated rows that have just been loaded</p><p>from the database and concatenate with the new and updated records.</p><p>12 / 13</p><p>More Hot Exams are available.</p><p>350-401 ENCOR Exam Dumps</p><p>350-801 CLCOR Exam Dumps</p><p>200-301 CCNA Exam Dumps</p><p>Powered by TCPDF (www.tcpdf.org)</p><p>13 / 13</p><p>https://www.certqueen.com/promotion.asp</p><p>https://www.certqueen.com/350-401.html</p><p>https://www.certqueen.com/350-801.html</p><p>https://www.certqueen.com/200-301.html</p><p>http://www.tcpdf.org</p>