The HR management team wants to aggregate data to show the number of employees across regions and to be able to drill down into the data.Which three user story requirements should be collected to assist the development team?
Answer(s): A,B,D
Data Source (A): The first step in building any report is identifying the source of the data. Understanding where the data comes from is crucial because it affects how the data will be queried, filtered, and displayed. It also impacts performance, security, and accuracy of the data. Appian reports can pull data from various sources such as Appian databases, external databases, or even from integrations with other systems. Documenting this information allows the development team to connect the report to the correct data source, ensuring that the report reflects accurate and up-to- date information.
Appian Documentation - Data SourcesReport Type (B): It is essential to define the type of report required. In this scenario, the HR management team wants an aggregate view with drill-down capabilities. The report type will determine how the data is visualized, whether it is a pie chart, bar graph, or tabular format. This user story requirement ensures that the developers design a report that meets the HR team's needs and expectations for viewing and interacting with the data.Appian Documentation - Creating ReportsRole-Based Permissions (D): Role-based permissions are critical for ensuring that users see only the data they are authorized to access. For instance, while an HR executive might have access to all regions' data, a regional manager might only see data for their specific region. Defining these permissions upfront is vital for security and compliance. The development team will use this information to implement the correct access controls in the report, which is crucial for protecting sensitive employee information.Appian Documentation - Managing User Permissions
An organization wants to automate identification of its dissatisfied customers based on the ticket description and assign the appropriate team to provide a quick resolution.What is the best way to auto-classify the dissatisfied customers as part of processing?
Answer(s): A
The organization aims to automate the identification of dissatisfied customers based on the ticket description. To achieve this, leveraging natural language processing (NLP) capabilities is the most efficient method. Appian provides connected systems that allow integration with external NLP services. These services can analyze text data (such as ticket descriptions) to determine the sentiment or classify the text into predefined categories (like "dissatisfied customer").Natural Language Connected System:Appian can integrate with third-party NLP platforms such as Google Cloud Natural Language, AWS Comprehend, or Azure Text Analytics via connected systems.These services analyze the text provided in the ticket description to detect sentiment, keywords, or specific categories indicating dissatisfaction.Based on the analysis, the system can automatically assign the appropriate team to handle the case.Why Not Other Options?:B . Decision Table: While decision tables are useful for rule-based decisions, they are not suitable for interpreting unstructured text like ticket descriptions.C . Image Analysis Connected System: This option is irrelevant as the task involves text processing, not image analysis.D . SAIL Form: SAIL forms are primarily used for user interface creation and are not intended for text analysis or classification.Implementation in Appian:Create a connected system to integrate with the chosen NLP service.Configure the NLP service to analyze the text data and return the sentiment or classification results.Based on the results, use process models to route the ticket to the appropriate team for resolution.
Appian Documentation on Connected Systems: Appian Connected SystemsAppian Community Success Guide: Appian Delivery MethodologyThird-Party NLP Services Integration: Google Cloud NLP Documentation
According to best practices, which two types of tests should be considered during user acceptance testing (UAT)?
Answer(s): C,D
Regulation Acceptance Testing (C): During User Acceptance Testing (UAT), it is essential to ensure that the application complies with industry regulations and standards. Regulation acceptance testing focuses on verifying that the system adheres to legal and compliance requirements specific to the industry or region where the application will be used. This ensures that the application meets all necessary regulatory guidelines before going live.
Appian Documentation - Testing and ValidationFunctional Testing (D): Functional testing is a critical component of UAT as it verifies that the application's functionality works as expected from the end-user's perspective. This includes validating that all features, workflows, and business processes perform correctly according to the specified requirements. UAT is the final phase where end-users interact with the application to confirm that it meets their needs and performs as intended.Appian Documentation - Functional TestingNote: Load testing (A) and platform security testing (B) are important types of tests but are usually conducted during performance and security testing phases rather than UAT. UAT focuses more on ensuring the application meets business requirements and end-user expectations.
You are designing a user interface that requires a confirmation message when the user attempts to delete a row.Review the image with the confirmation message:"Are you sure you want to delete the item?"According to best practices, which button labels should you choose?
According to UI/UX best practices, the button labels in a confirmation dialog should be clear and directly related to the action the user is about to take. "Cancel" allows the user to abort the action, while "Delete" confirms the action to delete the item. This approach ensures that the user understands exactly what will happen when they click either button, reducing the risk of accidental deletion or confusion.
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