Oracle 1z0-1041-23 Dumps

List and Expression are two types of filters that can be applied to all Dimensional data types in Oracle Analytics Cloud. A List filter allows you to select one or more values from a list of values for a dimension column. An Expression filter allows you to create a custom filter expression using SQL syntax for a dimension column. The other types of filters, such as Date and Range, are only applicable to specific data types, such as Date and Numeric. References: [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]

Semantic model created in the OA Admin tool and hierarchy created in a proper snowflake multi-table data set are two configurations that are appropriate for designing a solution to analyze retail sales with a product hierarchy in Oracle Analytics Cloud. A semantic model is a logical representation of your data that defines the relationships, calculations, hierarchies, and security rules for your data. You can create and manage semantic models using the OA Admin tool, which is a web-based interface that allows you to administer Oracle Analytics Cloud instances and services. A hierarchy is a structure that organizes your data into different levels of detail based on parent-child relationships. You can create hierarchies for your dimensions to enable drill-down analysis on your data. A snowflake multi-table data set is a type of data set that consists of multiple tables that are related to each other by foreign keys. You can create a snowflake multi-table data set using Data Preparation or Data Flow features in Oracle Analytics Cloud. You can use this type of data set to model complex dimensions that have multiple attributes stored in different tables, such as a product hierarchy with multiple levels. References: Oracle Help Center, [Oracle Help Center], [Oracle Help Center]

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. 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]

A general pattern or direction of data when viewed in relation to a time series is what a trend line highlights in Oracle Analytics Cloud. A trend line is a feature that allows you to draw a line that best fits your data and shows the overall tendency or movement of your data over time. You can add a trend line to your visualization by selecting Trend Line from the visualization gallery and choosing the data elements that you want to display in the trend line. You can also adjust the trend line settings, such as the trend line type, color, width, and label in the properties panel. You can choose from different types of trend lines, such as linear, polynomial, logarithmic, exponential, or power. A trend line highlights a general pattern or direction of data when viewed in relation to a time series, such as increasing, decreasing, or constant. You can use a trend line to analyze how your data changes over time and identify any trends or patterns that may affect your decisions or actions. The other options, such as a line representing the median values of a measure, a general pattern or direction of data when viewed in relation to other dimensions, or a line representing the average values of a measure, are not what a trend line highlights in Oracle Analytics Cloud. These options are either not related to a trend line or describe other types of lines or statistics that can be displayed in a visualization. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

The step that is required in a data flow to create a new curated data set is Add Data. Add Data is the first step in any data flow that allows you to select one or more data sources to use in your data flow. You can choose from various types of data sources, such as databases, files, applications, or existing data sets. You can also specify how to join or union multiple data sources if needed. References: Oracle Analytics Cloud - Data Visualization User’s Guide, [Oracle Analytics Cloud - Data Visualization User’s Guide]

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

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]

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. 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

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]

OBIEE 11.1.X and later is the version of OBIEE that is supported for migration to OAC. OBIEE stands for Oracle Business Intelligence Enterprise Edition, which is a comprehensive business intelligence platform that provides a range of analytics capabilities, such as interactive dashboards, ad hoc queries, enterprise reporting, and more. OAC stands for Oracle Analytics Cloud, which is a cloud-based analytics platform that provides similar features as OBIEE, as well as additional features such as data visualization, augmented analytics, machine learning, and more. You can migrate content from OBIEE to OAC using the Oracle BI Migration Tool, which is a command-line utility that allows you to export and import metadata and catalog objects between OBIEE and OAC. The Oracle BI Migration Tool supports migration from OBIEE 11.1.X and later versions to OAC, as these versions are compatible with OAC in terms of data model structure, catalog format, and security model. The other versions of OBIEE, such as OBIEE 12c, OBIEE 12g and later, and OBIEE 10g, are not supported for migration to OAC, as they are either not compatible with OAC or not available. References: Oracle Help Center, Oracle Help Center, Oracle Help Center

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]

A story can have multiple canvases and you can only export the active visual are two true statements about creating 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 also define notifications, filters, notes, and narration on each canvas to enhance your story and make it more interactive. You can only export the active visual when you create a story in Oracle Analytics Cloud. The active visual is the visualization that is currently selected or highlighted on your canvas. You can export the active visual as an image file (.png) by clicking on the Export icon on the toolbar and selecting Export Active Visual from the menu. You cannot export other elements or multiple visuals at once when you create a story in Oracle Analytics Cloud. The other statements, such as insights always take a snapshot data for a story and a project can have only one story, are not true about creating a story 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. Insights do not always take a snapshot data for a story, but rather use live data from your data set or project by default. You can change this behavior by enabling or disabling the Use Snapshot Data option for each insight in the properties panel. A project is a workspace where you can create and edit your data sets, visualizations, data flows, and stories using various tools and options. A project can have more than one story, as you can create multiple stories for different purposes or audiences within the same project. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

To create a relative time filter, you need to perform two steps:

• Select Relative Time as the filter type: A relative time filter allows you to filter your data based on a relative time period, such as last week, next month, or current year. You can select Relative Time as the filter type from the drop-down menu of the filter bar.
• Select Relative Time as the filter type and set the Relative To property: The Relative To property allows you to specify the reference point for your relative time period. For example, if you want to filter your data for the last quarter relative to today, you can set the Relative To property to Today. You can set the Relative To property from the filter dialog box after selecting Relative Time as the filter type. References: [Oracle Help Center], [Oracle Help Center]

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

Autonomous Data Warehouse is a supported source for registering and using machine learning models in Oracle Analytics Cloud. You can use the Register Model step in a data flow to register a machine learning model from Autonomous Data Warehouse and use it in your analyses or visualizations. You can also use the Apply Model step to apply a registered model to a new data set and generate predictions. 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