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質問 # 39
Which technique does Data Preparation in OAC use for as SSN, credit card number, and customer number?
- A. Obfuscation to protect sensitive information
- B. Sentiment Analysis algorithms
- C. Cryptographic algorithms to encrypt sensitive information
- D. Advanced Analytics functions
正解：A
解説：
Data Preparation in OAC uses obfuscation to protect sensitive information such as SSN, credit card number, and customer number. Obfuscation is a technique that replaces the original values with random or masked values that preserve the format and length of the original values. This way, you can hide or anonymize sensitive information while maintaining its usability for analysis or visualization. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide
質問 # 40
Which two can be defined on a canvas in a story in Oracle Analytics Cloud?
- A. Narration
- B. Filters
- C. Notes
- D. Notifications
正解：B、D
解説：
Notifications and Filters are two elements that can be defined on a canvas in a story in Oracle Analytics Cloud. A canvas is a page or a slide where you can add and arrange various elements to create your story. You can add multiple canvases to your story and navigate between them using the navigation bar. You can define Notifications and Filters on a canvas to enhance your story and make it more interactive. Notifications are messages that appear on your canvas to inform or alert your audience about something important or relevant to your story, such as a key insight, a recommendation, or a call to action. You can create notifications using the Notification icon on the toolbar and customize them by changing the text, color, position, and duration of the message. Filters are criteria that limit the data that is displayed on your canvas based on certain values or ranges. You can create filters using the Filter icon on the toolbar and apply them to one or more elements on your canvas. You can also enable your audience to change the filter values interactively using the filter bar or the filter dialog box. The other elements, such as Notes and Narration, are not available on a canvas in a story in Oracle Analytics Cloud. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 41
You want to create a Sales Amount by Month report for a product. The report should display sales amount from all cities in the South region with sales amount more than 1 million USD.
Which two Alters can be applied for Region and Sales Amount
- A. Range filter 'or Region and Date filter for sales Amount
- B. List filter for Region and Expression filter for Sales Amount
- C. List filter for Region and Range filter for Sales Amount
- D. List filter for Region and List filter for Sales Amount
正解：A、D
解説：
Two filters that can be applied for Region and Sales Amount are:
Range filter for Region and Date filter for sales Amount. A range filter allows you to specify a range of values for a column using operators such as greater than, less than, between, or not between. A date filter allows you to specify a date or a date range for a column using operators such as before, after, on, or between. For example, you can use a range filter to select only the South region and a date filter to select only the months with sales amount more than 1 million USD.
List filter for Region and List filter for Sales Amount. A list filter allows you to select one or more values from a list of values for a column using operators such as equals, not equals, in, or not in. For example, you can use a list filter to select only the South region and another list filter to select only the sales amounts that are more than 1 million USD. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 42
You are designing an analytics solution for a company that distributes packaged foods for independent retailers. The solution requires self-service analytics capabilities for product management and In addition, highly formatted reports must be delivered by scheduled email to external resellers Which edition of Oracle Analytics must you use
- A. OAC Business Intelligence Edition
- B. OAC Enterprise Edition
- C. OAC Professional Edition
- D. OA Fusion Analytics Warehouse Edition
- E. OA Data Visualization Cloud
正解：B
解説：
To design an analytics solution that requires self-service analytics capabilities for product management and sales teams, as well as highly formatted reports delivered by scheduled email to external resellers, you must use OAC Enterprise Edition. OAC Enterprise Edition is the most comprehensive edition of Oracle Analytics Cloud that offers both self-service and governed analytics capabilities, as well as BI Publisher for creating pixel-perfect reports and delivering them by email or other channels. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 43
Identify the correct use of BI Ask.
- A. is used to enter column names into the search hold, select them, and quickly see them added to a project
- B. is used to power the type ahead functionality.
- C. is used to enable user input in Natural Language. It extracts column names from the User Input and quickly build visuals for the columns extracted
- D. is used to search for visualizations
- E. is used to search for projects
正解：C
解説：
The correct use of BI Ask is that it is used to enable user input in natural language. It extracts column names from the user input and quickly builds visuals for the columns extracted. BI Ask is a feature that allows you to create analyses using natural language queries instead of dragging and dropping columns from the subject area pane. You can type or speak your query in BI Ask and it will automatically generate the best visualization for your query based on the columns extracted from your input. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 44
You are creating an analytics solution for a financial institution using Oracle Analytics Cloud.
One of the requirements is a workbook with a model that identifies customers with multiple potential infraudulent transactions.
Which algorithm would be the best fit for this purpose?
- A. Decision Tree
- B. Logistic Regression
- C. Support Vector Machine
- D. Anomaly Detection
正解：D
解説：
Anomaly Detection is the algorithm that would be the best fit for creating a model that identifies customers with multiple potential fraudulent transactions in Oracle Analytics Cloud. Anomaly Detection is a machine learning technique that allows you to detect outliers or anomalies in your data that deviate from the normal or expected behavior. You can use Anomaly Detection to create a model that scores each customer based on their transaction history and flags those who have unusually high or low values as potential fraudsters. The other algorithms, such as Support Vector Machine, Decision Tree, and Logistic Regression, are not the best fit for this purpose. Support Vector Machine is a machine learning technique that allows you to classify data into two or more categories based on a linear or nonlinear boundary. Decision Tree is a machine learning technique that allows you to create rules or conditions for splitting data into branches or nodes based on certain criteria. Logistic Regression is a machine learning technique that allows you to predict the probability of an event occurring based on one or more variables. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 45
A column in your data has a wide range of numerical values. You want to create a column that labels these values as Large, Medium, or Small.
Which data preparation action helps you to accomplish this?
- A. Bin
- B. Bundle
- C. Convert
- D. Extrapolate
正解：A
解説：
Bin is the data preparation action that helps you to create a column that labels numerical values as Large, Medium, or Small in Oracle Analytics Cloud. Bin is a feature that allows you to group numerical values into discrete categories or bins based on a specified range or interval. You can use Bin to create a new column that assigns labels to each bin, such as Large, Medium, or Small. The other data preparation actions, such as Convert, Extrapolate, and Bundle, do not help you to accomplish this task. Convert is a feature that allows you to change the data type or format of a column. Extrapolate is a feature that allows you to fill in missing values in a column based on a linear or exponential trend. Bundle is a feature that allows you to combine multiple columns into one column. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 46
You have created a Machine Learning model and investigated how accurate it \s. How should you use it in Oracle Analytics Cloud (OAC)?
- A. Connect to the model as a new project.
- B. Use a data flow with a Commit Model step and save as a new data set.
- C. Create Data Flow with a cumulative value prediction.
- D. Create a custom calculation based on a related formula.
- E. Use Data Flow with an Apply Model step and save as a new data set.
正解：E
解説：
After creating and testing a machine learning model, you can use it to make predictions on new data sets using a data flow. A data flow is a sequence of steps that transform and enrich data from one or more sources. An Apply Model step allows you to apply a previously trained model to a new data set and generate predictions as a new column. You can then save the output of the data flow as a new data set for further analysis or visualization. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 47
Your client wants to implement a custom plug in from Oracle Analytics Library. Vou just finished uploading the extension to Oracle Analytics Cloud (OAC).
What action do you need to take before the extension is available for use in projects?
- A. Enable the plug-in from the Plug-in menu.
- B. No additional action is needed.
- C. Restart the OAC instance.
- D. Refresh the page.
正解：D
解説：
Refreshing the page is the action that you need to take before the extension is available for use in projects after uploading it to Oracle Analytics Cloud. An extension is a custom plug-in that adds new functionality or enhances existing functionality in Oracle Analytics Cloud. You can download extensions from Oracle Analytics Library, which is a repository of extensions created by Oracle and the community. You can also create your own extensions using the Extension SDK, which is a software development kit that provides tools and resources for developing extensions. To upload an extension to Oracle Analytics Cloud, you need to go to the Console page and select Plug-ins from the menu. Then you need to click on Upload and browse for the extension file (.zip) that you want to upload. After uploading the extension, you need to refresh the page to see the extension in the list of available plug-ins. You can then enable or disable the extension as needed. The other actions, such as enabling the plug-in from the Plug-in menu, restarting the OAC instance, or taking no additional action, are not required or correct before the extension is available for use in projects. Reference: Oracle Help Center, Oracle Help Center, Oracle Help Center
質問 # 48
As part of an analysis, you have the following set of data:
Assuming, you have entered the Aggregate function SUM (Revenue) in the second column.
- A. Row 1: 1000 Row 2: 3000
- B. Row 1: 2000 Row 2: 3000
- C. Row 1: 1000 Row 2: 2000
- D. Row 1; 3000 Row 2: 3000
正解：C
解説：
Based on the image of the chart, the aggregate function SUM (Revenue) will calculate the sum of revenue for each product category. The chart shows that Product A has two rows with revenue values of 500 and 500, so the sum is 1000. Product B has two rows with revenue values of 1000 and 1000, so the sum is 2000. Reference: Oracle Analytics Cloud - Data Visualization User's Guide
質問 # 49
Which application role must you grant to the user?
- A. Bl Content Author
- B. DV Content Author
- C. Bl Data Model Author
- D. Bl Dataload Author
正解：B
解説：
DV Content Author is the application role that you must grant to the user who wants to create and edit data visualizations in Oracle Analytics Cloud. Data Visualization is a feature that allows you to explore, analyze, and visualize your data using various types of charts, graphs, maps, and more. You can also apply filters, calculations, aggregations, and other functions to your data. To access Data Visualization, you need to have the DV Content Author role, which gives you the permission to create and edit data sets, projects, and data flows. The other roles, such as BI Content Author, BI Data Model Author, and BI Dataload Author, are not required for Data Visualization, but rather for other features such as Business Intelligence, Data Modeler, and Data Loader. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 50
Your Oracle Analytics client asks you to shape a story and story and share it as a file.
Which are three valid file types for sharing a story?
- A. Acrobat (.pdf)
- B. Word (.docx)
- C. image (.png)
- D. AutoCad (.dxf)
- E. Package (.dva)
正解：A、C、E
解説：
Image (.png), Acrobat (.pdf), and Package (.dva) are three valid file types for sharing a story in Oracle Analytics Cloud. A story is a feature that allows you to create and present a narrative based on your data using various elements, such as visualizations, text boxes, images, videos, and more. You can use a story to communicate your findings and recommendations to your audience in an engaging and interactive way. You can share a story as a file by exporting it to one of the supported file formats, such as image (.png), Acrobat (.pdf), or Package (.dva). An image file (.png) allows you to save a snapshot of your story as an image that you can view or print using any image viewer application. An Acrobat file (.pdf) allows you to save your story as a document that you can view or print using any PDF reader application. A Package file (.dva) allows you to save your story along with its associated data sets and projects as a compressed file that you can import into another Oracle Analytics Cloud instance or application. The other file types, such as AutoCad (.dxf) and Word (.docx), are not valid file types for sharing a story in Oracle Analytics Cloud. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 51
Which two are supported on the home page of a BI Ask visualization?
- A. View data from multiple data sets \n a single query.
- B. Drilling down on the visualizations.
- C. opening visualizations in the Oracle Analytics Cloud home page to customize and add to a project
- D. saving visualizations displayed on the Oracle Analytics Cloud home page
正解：A、B
解説：
Drilling down and viewing data from multiple data sets in a single query are two features that are supported on the home page of a BI Ask visualization in Oracle Analytics Cloud. BI Ask is a natural language interface that allows you to ask questions and get answers in the form of visualizations. You can drill down on the visualizations to explore the data at different levels of detail. You can also view data from multiple data sets in a single query by using keywords such as "and", "or", and "with". The other features, such as opening and saving visualizations, are not supported on the home page of a BI Ask visualization, but rather require you to open the visualization in a project or data visualization. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 52
Which role is required to edit and create a new semantic model in Oracle Analytics Cloud Enterprise Edition?
- A. BI Content Author
- B. DV Consumer Role
- C. BI Data Model Author
- D. BI RPD Model Author
- E. BI Data Load Author
正解：C
解説：
To edit and create a new semantic model in Oracle Analytics Cloud Enterprise Edition, you need to have the BI Data Model Author role. This role allows you to access and use the Data Modeler tool, where you can create and modify semantic models that define the logical structure and relationships of your data sources. You can also use the Data Modeler to create calculations, hierarchies, variables, security filters, and other features for your semantic models. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 53
Which two statements are true about Presentation Catalog?
- A. My Folders can be shared with other users.
- B. Catalog items can be set to read-only.
- C. To prevent corrupter, of the catalog, storage of objects of different types must be segregated into their own folders.
- D. You can grant ownership of items you create to other users.
正解：B、D
解説：
You can grant ownership of items you create to other users and catalog items can be set to read-only are two true statements about Presentation Catalog in Oracle Analytics Cloud. Presentation Catalog is a feature that allows you to store, organize, and manage your analytics content and resources, such as data sets, projects, data flows, data models, and more. You can grant ownership of items you create to other users by changing the owner property of the items in the catalog. This allows you to transfer the full control and responsibility of the items to another user. You can also set catalog items to read-only by changing the permissions of the items in the catalog. This prevents other users from modifying or deleting the items, but allows them to view or copy them. The other statements, such as My Folders can be shared with other users and storage of objects of different types must be segregated into their own folders, are not true about Presentation Catalog in Oracle Analytics Cloud. My Folders is a personal folder that is visible only to you and cannot be shared with other users. You can store objects of different types in the same folder in the catalog, as long as they have unique names. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 54
Which are two use-cases for Data Flow?
- A. Train and test the Machine Learning model.
- B. Create a custom Python Machine Learning model.
- C. To curate data sets that can be used for visualizations.
- D. Perform some lightweight transformation within the Project.
正解：C
解説：
Data Flow is a feature of Oracle Analytics Cloud that enables you to create and run data flows to transform and enrich your data. You can use Data Flow for various use-cases, such as:
To curate data sets that can be used for visualizations. You can join, filter, aggregate, pivot, and perform other operations on your data sets to prepare them for analysis.
To train and test the Machine Learning model. You can use Data Flow to apply machine learning algorithms to your data and create predictive models. You can also evaluate the performance of your models and compare them with different parameters. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 55
What does a fact table use to reference dimension tables?
- A. Primary key
- B. Master key
- C. Foreign key
- D. Aggregate type
- E. Dimension attribute
正解：C
解説：
A fact table uses a foreign key to reference dimension tables in a relational database schema. A fact table is a table that contains numerical measures or facts that are related to a business process or event, such as sales, orders, or transactions. A dimension table is a table that contains descriptive attributes or dimensions that provide context to the facts, such as product, customer, time, or location. A foreign key is a column or a set of columns in a table that refers to the primary key of another table. A primary key is a column or a set of columns in a table that uniquely identifies each row in the table. A foreign key establishes a relationship between the fact table and the dimension tables, and allows you to join them for analysis. The other options, such as dimension attribute, aggregate type, and master key, are not used by a fact table to reference dimension tables. A dimension attribute is a column in a dimension table that contains a specific level or detail of the dimension, such as product name, customer name, or month. An aggregate type is a property of a measure column that specifies how the measure should be aggregated or calculated, such as sum, average, count, or minimum. A master key is not a valid term in relational database schema. Reference: Oracle Help Center, Oracle Help Center
質問 # 56
Oracle Applications Connector supports Oracle Fusion Applications Cloud.
Which is valid about Oracle Applications Connector?
- A. It can be used with the Thin Client Modeler.
- B. It cannot connect to on-premises Oracle BI Enterprise Edition.
- C. When abating a connection, enter the URL for Oracle Fusion Applications.
- D. The Active User's Credentials option in the Create Oracle Application Connection dialog box.
- E. It cannot be used with Oracle Applications Connector.
- F. When creating a connection, enter the Business Intelligence URL for Oracle Fusion Applications
正解：C
解説：
Oracle Applications Connector supports Oracle Fusion Applications Cloud, which is a suite of cloud applications that provide enterprise resource planning, human capital management, customer relationship management, and other functionalities. To create a connection to Oracle Fusion Applications Cloud using Oracle Applications Connector, you need to enter the URL for Oracle Fusion Applications in the Create Oracle Application Connection dialog box. The other options are not valid about Oracle Applications Connector. You do not need to enter the Business Intelligence URL for Oracle Fusion Applications, as this is not required for the connection. The Active User's Credentials option is not available in the Create Oracle Application Connection dialog box, as this is only applicable for some other types of connections. Oracle Applications Connector can be used with Oracle Applications Connector, as this is its purpose. It can also connect to on-premises Oracle BI Enterprise Edition, as this is one of the supported sources. It cannot be used with the Thin Client Modeler, as this is a separate tool that does not require a connection. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 57
An analyst is creating a story on the Narrate tab of the project. What is the most likely reason they have done this?
- A. To share the story by exporting to MS Excel.
- B. To share the story with consumers on the Home Page.
- C. To share the story on Day by Day with their decision makers.
- D. To share the story by exporting to pdf.
正解：C
解説：
Sharing the story on Day by Day with their decision makers is the most likely reason why an analyst has created a story on the Narrate tab of the project in Oracle Analytics Cloud. A story is a feature that allows you to create and present a narrative based on your data using various elements, such as visualizations, text boxes, images, videos, and more. You can use a story to communicate your findings and recommendations to your audience in an engaging and interactive way. The Narrate tab is a workspace where you can create and edit your story using various tools and options. You can add multiple canvases to your story and navigate between them using the navigation bar. You can also add notifications, filters, notes, and narration to your story to enhance it and make it more interactive. Day by Day is a mobile application that allows you to access and interact with your Oracle Analytics Cloud content using voice or text commands. You can use Day by Day to view and explore your stories on your mobile device and share them with other users via email or chat. You can also receive personalized insights and recommendations from Day by Day based on your location, calendar, and preferences. Sharing the story on Day by Day with their decision makers is a convenient and effective way for an analyst to deliver their analysis and influence their decisions. The other options, such as sharing the story by exporting to MS Excel, sharing the story with consumers on the Home Page, and sharing the story by exporting to pdf, are not the most likely reasons why an analyst has created a story on the Narrate tab of the project in Oracle Analytics Cloud. These options are either not supported or not optimal for sharing a story in Oracle Analytics Cloud. Reference: Oracle Help Center, Oracle Help Center, Oracle Help Center
質問 # 58
Which relational database schema consists than in single-dimension tables?
- A. Leaf
- B. Network
- C. Sun Snowflake schema
- D. Star schema
正解：A
解説：
Leaf is the relational database schema that consists of single-dimension tables in Oracle Analytics Cloud. A leaf schema is a type of schema that consists of one fact table and one dimension table for each dimension in the data model. A leaf schema simplifies the data model by eliminating the need for multiple tables or joins for each dimension. However, a leaf schema may result in data redundancy and inconsistency, as the same dimension values may be repeated across different tables. The other types of schemas, such as network, star, and snowflake, consist of more than one dimension table per dimension. A network schema consists of multiple fact tables and multiple dimension tables that are interconnected by foreign keys. A star schema consists of one fact table and multiple dimension tables that are directly related to the fact table by foreign keys. A snowflake schema consists of one fact table and multiple dimension tables that are related to each other by foreign keys. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 59
In Oracle Analyt.es Cloud (OAC), an Enterprise BI application database has many dimensions. Which option helps you to visualize on a subset of the original data?
- A. Filtering
- B. Sorting
- C. Indexing
- D. Selecting
正解：A
解説：
Filtering is the option that helps you to visualize on a subset of the original data in Oracle Analytics Cloud. You can use filters to limit the data that is displayed in your visualizations based on certain criteria. You can apply filters to dimensions, measures, or attributes in your data set. The other options, such as Sorting, Indexing, and Selecting, do not help you to visualize on a subset of the original data, but rather change the order, structure, or appearance of the data. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 60
Your client wants you to build visualizations that will help them understand their data better. Which two methods will help them achieve this?
- A. Create Data Flow to highlight interesting data.
- B. Add the relevant visualizations to a canvas.
- C. Create a sequence and schedule it to run on a nightly basis.
- D. Add trend lines, clustering, and outliers to visualizations to offer new perspectives
- E. Use the explain feature to quickly identify Basic Facts, Key Drivers, Segments, and Anomalies.
正解：B、E
解説：
Using the explain feature and adding the relevant visualizations to a canvas are two methods that will help you build visualizations that will help your client understand their data better in Oracle Analytics Cloud. The explain feature is a feature that allows you to automatically generate insights and recommendations for your data based on various factors, such as Basic Facts, Key Drivers, Segments, and Anomalies. Basic Facts are summary statistics that describe your data, such as count, sum, average, minimum, and maximum. Key Drivers are variables that have a strong influence or correlation with your data, such as product category, customer segment, or region. Segments are groups of data points that have similar characteristics or patterns, such as high-value customers, low-performing products, or seasonal trends. Anomalies are data points that deviate significantly from the normal or expected behavior of your data, such as outliers, spikes, or drops. You can use the explain feature to quickly identify these factors and create visualizations that highlight them. You can also add the relevant visualizations to a canvas, which is a workspace where you can arrange and display your visualizations in a meaningful way. You can choose from various types of visualizations, such as charts, graphs, maps, tables, and more. You can also customize your visualizations by applying filters, calculations, aggregations, and other functions to your data. You can use these methods to create visualizations that will help your client understand their data better and discover new insights. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 61
You are building a model that will be used for a sales report.
Which two statements are the about hierarchy and levels?
- A. A hierarchy must have one to many relationships between attributes.
- B. Hierarchies enable drilling in reports.
- C. Each level is based on one or multiple columns.
- D. Skipped levels and unbalanced hierarchies can be enabled for all the dimension tables.
- E. When defining a level. Key Columns must be the same as Display Columns.
- F. A dimension table must have only one hierarchy.
- G. A hierarchy shows relationships among a group of columns in a fact table.
正解：B、C
解説：
Two statements that are true about hierarchy and levels are:
Each level is based on one or multiple columns. A level is a logical grouping of one or more columns that represent a certain granularity or detail of data. For example, a level can be based on a single column, such as Year, or multiple columns, such as Year and Quarter.
Hierarchies enable drilling in reports. A hierarchy is a logical structure that defines the relationships among levels and shows how data can be aggregated or disaggregated from one level to another. For example, a hierarchy can show how Year, Quarter, Month, and Day are related in a time dimension. Hierarchies allow users to drill down or drill up in reports to see different levels of detail or summary of data. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 62
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