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

Two types of filters that can be used to display as prompts in your Publisher report are:

• Number filters. A number filter allows you to specify a numeric value or a range of numeric values for a column using operators such as equals, not equals, greater than, less than, or between. For example, you can use a number filter to prompt users to enter a minimum or maximum sales amount for your report.
• Expression filters. An expression filter allows you to specify a logical expression for a column using operators such as AND, OR, NOT, or parentheses. For example, you can use an expression filter to prompt users to enter a combination of conditions for your report, such as region equals South AND sales amount greater than 1 million USD. References: [Oracle Analytics Cloud - Data Visualization User’s Guide], [Oracle Analytics Cloud - Data Visualization User’s Guide]

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

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

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]

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

Selecting the desired data elements from the Data Elements pane and then right-clicking and selecting Create Best Visualization from the drop-down menu and selecting the desired data elements from the Data Elements pane and dragging them to the Best visualization zone in the Explore pane are two methods that you can use to invoke the best visualization in Oracle Analytics Cloud. The best visualization is a feature that automatically selects the most suitable type of visualization for your data based on various factors, such as the number and type of data elements, the distribution and range of values, and the analytical purpose. You can use these two methods to create the best visualization for your data without having to manually choose the visualization type from the gallery. The other methods, such as changing the project’s properties, selecting the Best Visualization option from the project’s Canvas Settings drop-down menu, and dragging the data elements to a blank area of the canvas, are not valid ways to invoke the best visualization in Oracle Analytics Cloud. References: [Oracle Help Center], [Oracle Help Center]

Natural Language Query (NLQ) is a feature of Oracle Day By Day that allows you to ask questions using natural language and get answers in the form of charts, tables, or maps. To improve the results from NLQ, you can do the following:

• Define acronyms for commonly used terms or phrases in your data sets, such as KPI, ROI, or CRM. This will help NLQ understand your queries better and match them to the relevant data elements.
• Define synonyms for different words that have the same meaning in your data sets, such as sales, revenue, or income. This will help NLQ handle variations in your queries and return consistent results.
• Curate the exposed data sets by removing duplicate or unnecessary attributes that may confuse NLQ or reduce its performance. You can also rename or reorder attributes to make them more intuitive or user-friendly. References: [Oracle Day By Day User’s Guide], [Oracle Day By Day User’s Guide], [Oracle Day By Day User’s Guide]

To build an analysis that requires data from two subject areas, you can create an analysis and add a second subject area for a union. A union is an operation that combines two or more data sets with similar columns into one data set. You can use the Add Subject Area option in the Criteria tab of an analysis to add another subject area and select Union as the operation type. References: [Oracle Analytics Cloud - Data Visualization User’s Guide], [Oracle Analytics Cloud - Data Visualization User’s Guide]

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]

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

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]

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

A column’s navigation option can be enabled conditionally and presentation variables can be used while navigating from one analysis to another are two true statements about Action Links in Oracle Analytics Cloud. Action Links are a feature that allows you to create interactive links in your analyses that perform actions when clicked, such as navigating to another analysis, opening a web page, sending an email, or running a script. You can create Action Links for columns or measures in your analyses and configure them to suit your needs. You can enable a column’s navigation option conditionally by using a conditional expression that determines whether the Action Link is active or not based on the value of the column or another column in the same row. You can also use presentation variables while navigating from one analysis to another by passing the value of the presentation variable as a parameter to the target analysis. Presentation variables are variables that capture user input and store it in a session variable that can be referenced by other analyses or filters. The other statements, such as navigation from one analysis to another is not possible if they reside in different folders and navigation from one analysis to another works only when both analyses are created from a single subject area, are not true about Action Links in Oracle Analytics Cloud. You can navigate from one analysis to another regardless of where they reside in the catalog, as long as you have access to them. You can also navigate from one analysis to another even if they are created from different subject areas, as long as they have compatible columns or measures that can be used for filtering or drilling. 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]

Dashboard prompts are filters that allow users to dynamically change the data displayed in a dashboard. Some statements that are true about dashboard prompts are:

• Prompt values can be limited based on values selected in other prompts. This is called cascading prompts, where the values of one prompt depend on the selection of another prompt.
• Repository variables and session variables can be used in prompt default values. This allows users to set dynamic default values for prompts based on variables defined in the repository or the session. References: Oracle Analytics Cloud - Data Visualization User’s Guide, Oracle Analytics Cloud - Data Visualization User’s Guide

ETS, Seasonal ARIMA, and Seasonal ETS are three models that are available for calculating the forecast in Oracle Analytics Cloud. A forecast is a feature that allows you to predict future values of your data based on historical data and various statistical methods. You can add a forecast to your visualization by selecting Forecast from the visualization gallery and choosing the data elements that you want to forecast. You can also adjust the forecast settings, such as the forecast length, confidence interval, and forecast method in the properties panel. You can choose from different models for calculating the forecast, such as ETS, Seasonal ARIMA, and Seasonal ETS. ETS stands for Exponential Smoothing, which is a model that uses weighted averages of past observations to smooth out the fluctuations and trends in the data. Seasonal ARIMA stands for Seasonal AutoRegressive Integrated Moving Average, which is a model that uses a combination of autoregressive and moving average terms to capture the patterns and seasonality in the data. Seasonal ETS stands for Seasonal Exponential Smoothing, which is a model that extends the ETS model by adding a seasonal component to account for the periodic variations in the data. The other models, such as ARENA and Seasonal ARENA, are not available for calculating the forecast in Oracle Analytics Cloud. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]