Oracle 1z0-1041-23 Oracle Cloud Infrastructure 2023 Enterprise Analytics Professional Exam Practice Test

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. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

To display the report in the click event drilled down in the same window, you can set the drill in place option in section properties. This option allows you to replace the original report with the drilled report in the same section of the dashboard page. You can also use breadcrumbs to navigate back to the original report. References: Oracle Analytics Cloud - Data Visualization User’s Guide, Oracle Analytics Cloud - Data Visualization User’s Guide

To create an Oracle Analytics Cloud (OAC) instance, you need to subscribe to the Oracle Analytics Cloud service on Oracle Cloud Infrastructure (OCI). Oracle Analytics Cloud is a comprehensive analytics platform that provides a range of analytics capabilities, such as data visualization, augmented analytics, machine learning, enterprise reporting, and more. You do not need to subscribe to other services such as Oracle Back Storage, Oracle Autonomous Database, or Oracle Big Data Cloud Storage to create an OAC instance, although you can use them as data sources for your analytics projects. References: [Oracle Help Center], [Oracle Help Center]

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. References: Oracle Help Center, Oracle Help Center, Oracle Help Center

To expose a new custom map layer in a project, you need to do the following steps:

• Navigate to the Console by clicking the Home icon on the top left corner of the screen and then clicking Console.
• Click Maps on the left navigation pane to open the Maps page.
• On the Map Layers tab, click Upload to upload your custom map layer file. The file must be in XML format and follow the Oracle Analytics Cloud map layer specification.
• After uploading your custom map layer file, you can see it in the list of available map layers and use it in your projects. References: Oracle Analytics Cloud - Data Visualization User’s Guide, [Oracle Analytics Cloud - Data Visualization User’s Guide]

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. References: [Oracle Help Center], [Oracle Help Center]

Oracle Analytics Cloud (OAC) provides various ways to identify and analyze outliers in your data set. Outliers are data points that deviate significantly from the rest of the data and may indicate errors, anomalies, or opportunities. Two layers that you can use to determine which values of a given data set may provide the greatest opportunity due to their outlier qualities are:

• Add an outlier visualization to your canvas. This will highlight data points that stand out and may justify further investigation. An outlier visualization is a type of scatter plot that automatically detects and labels outliers in your data using machine learning algorithms. You can use the outlier visualization to explore the characteristics and causes of the outliers and compare them with the normal data points.
• Create a box plot visualization of your data set. A box plot is a type of graph that shows the distribution of a numerical variable using quartiles and whiskers. A box plot can also identify outliers as data points that lie beyond the whiskers or outside a certain range. You can use the box plot to see how the outliers affect the overall distribution and variation of your data.

References: Oracle Analytics Cloud - Data Visualization User’s Guide, Oracle Analytics Cloud - Data Visualization User’s Guide

A single transaction means that all the data flows in a sequence are executed as a unit of work. If any data flow fails, the entire sequence is aborted and the changes made by the previous data flows are rolled back to ensure data consistency and integrity. References: Oracle Analytics Cloud - Data Visualization User’s Guide

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. References: [Oracle Help Center], [Oracle Help Center]

Analytics Link is a data action that allows you to connect to Oracle Analytics Publisher reports and view them in Oracle Analytics Cloud. You can use Analytics Link to embed reports in your dashboards, projects, or data visualizations. You can also pass parameters to the reports and filter them dynamically. References: [Oracle Help Center]

To create a line chart visualization of revenue data at the day level that displays the last 365 days of data and the next 90 days of forecast, you need to add a forecast and change the Period value to 90. A forecast is a feature that allows you to predict future values of a measure based on historical data using various methods, such as linear, exponential, or seasonal. The Period value specifies how many future values you want to forecast. For example, you can add a forecast to your line chart and set the Period value to 90 to see the projected revenue for the next 90 days. References: [Oracle Analytics Cloud - Data Visualization User’s Guide], [Oracle Analytics Cloud - Data Visualization User’s Guide]

 A multi-classifier is a machine learning model that can predict one of several possible classes for a given input. In this case, the target attribute Profitability has three possible values: high, medium, or low. Therefore, a multi-classifier is the appropriate model to train on this data set. References: Oracle Analytics Cloud - Data Visualization User’s Guide, Oracle Analytics Cloud - Data Visualization User’s Guide

User Folders, Shared Folders, and Data Models are three items that can be included in the search index in Oracle Analytics Cloud. The search index is a feature that enables you to quickly find and access the analytics content and resources that you need. You can configure the search index to include or exclude certain types of items from the index, such as folders, data sets, projects, data models, and more. You can include User Folders and Shared Folders in the search index to make them searchable by name, description, or owner. You can also include Data Models in the search index to make them searchable by name, description, owner, or subject area. The other item, Templates, cannot be included in the search index, as this is not a supported type of item for indexing. References: [Oracle Help Center], [Oracle Help Center]

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. References: Oracle Analytics Cloud - Data Visualization User’s Guide, Oracle Analytics Cloud - Data Visualization User’s Guide

Insights is always shared in form of story so everybody will see the same information and insights is shared as a story and everybody will see their information based on permissions are two true statements about sharing with insights in Oracle Analytics Cloud. Insights 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 insights using the Insight icon on the toolbar and customize them by changing the text, color, position, and duration of the message. You can also enable or disable the Use Snapshot Data option for each insight in the properties panel. When you share your insights with other users, you share them as part of your story, which 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 share your story with other users by exporting it as a file (.png, .pdf, or .dva) or by sending it via email or chat. When you share your insights as part of your story, everybody will see the same information that you see in your insights, regardless of whether you use live data or snapshot data for your insights. However, everybody will also see their information based on their permissions for accessing the data sets or projects that are associated with your story. The other statements, such as it is not possible to share insights with other users and by default all users cannot share insights, are not true about sharing with insights in Oracle Analytics Cloud. You can share insights with other users as part of your story using various methods, such as exporting, emailing, or chatting. You can also control who can share insights by changing the permissions of your story in the catalog. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

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. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

To change the dashboard prompt range from all pages to only the Sales page, you need to do the following steps:

• In the Dashboard editor, edit the dashboard prompt properties by clicking the Edit View button on the top right corner of the prompt.
• In the Scope tab, select Page as the scope option and choose Sales as the page name from the drop-down list.
• Click OK to save your changes and apply the dashboard prompt only to the Sales page. References: Oracle Analytics Cloud - Data Visualization User’s Guide, Oracle Analytics Cloud - Data Visualization User’s Guide

Usage tracking is a feature of Oracle Analytics Cloud that enables you to collect and analyze information about how users interact with your analytics content and resources. Usage tracking is available only for Enterprise Edition, as this is a more advanced and scalable edition than Professional Edition. To enable usage tracking, you need to create a new connection pool in the Oracle Analytics Developer Client tool, which is a desktop application that allows you to create and manage data models for Oracle Analytics Cloud. You also need to configure the Usage Tracking Connection Pool setting in the console, which is a web-based interface that allows you to administer Oracle Analytics Cloud instances and services. After making any change to this setting, you need to restart your Oracle Analytics Cloud instance for the change to take effect. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

To perform a trend analysis on a data set of stocks, you need to have at least one date column that represents the time dimension of your data. A trend analysis is a method of analyzing how a variable changes over time and identifying patterns or trends that may exist. Without a date column, you cannot perform a trend analysis on your data set. The other columns, such as MaxStockPrice and MinStockPrice, are optional and depend on what variable you want to analyze. References: [Oracle Help Center]

To filter a global data set for oil prices for a period of time for each country based on Asian countries and one month period, you can use two combinations of filters:

• Expression and Date Range: An expression filter allows you to create a custom filter expression using SQL syntax. You can use an expression filter to specify the condition for Asian countries based on the country column of your data set. A date range filter allows you to filter your data based on a start date and an end date. You can use a date range filter to specify the one month period based on the date column of your data set.
• List and Date Range: A list filter allows you to filter your data based on one or more values from a list of values. You can use a list filter to select the Asian countries from the list of values in the country column of your data set. A date range filter allows you to filter your data based on a start date and an end date. You can use a date range filter to specify the one month period based on the date column of your data set. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]