1z0-1041-23 Practice Exam Questions with Answers Oracle Cloud Infrastructure 2023 Enterprise Analytics Professional Certification

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

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]

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]

Creating a cluster with a suitable number of groups for the specific analysis is a method that you can use to categorize a large number of data points on a particular canvas in Oracle Analytics Cloud. A cluster is a group of data points that have similar characteristics or patterns based on certain criteria or variables. Clustering is a machine learning technique that allows you to automatically segment your data into clusters based on various algorithms and techniques, such as k-means, hierarchical, or density-based clustering. You can create a cluster with a suitable number of groups for your specific analysis by selecting Cluster from the visualization gallery and choosing the data elements that you want to use for clustering. You can also adjust the number of groups and the clustering method in the properties panel. You can use this method to categorize a large number of data points on your canvas and discover hidden patterns or relationships in your data. The other methods, such as creating a trend line, visualizing the data by using a network chart, or using a combination of a tree diagram and a trellis visualization, are not suitable for categorizing a large number of data points on a particular canvas in Oracle Analytics Cloud. These methods are either not supported or not optimal for clustering or categorizing data in Oracle Analytics Cloud. References: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]

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 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]

The Time Dimension wizard is a feature of Oracle Analytics Cloud that allows you to create a time dimension table in your database without having to write any SQL code. The time dimension table is a table that contains information about time periods, such as year, quarter, month, week, day, hour, and so on. You can use the time dimension table to perform time-based analysis on your data, such as comparing sales across different quarters or calculating year-to-date revenue. The Time Dimension wizard performs three tasks when you execute it:

• It creates the time dimension table in your database based on the parameters that you specify, such as the name of the table, the start date and end date of the time range, the level of granularity (such as day or hour), and the format of the date values.
• It loads time data into the time dimension table based on the parameters that you specify, such as the number of rows to insert per batch, the commit interval, and the connection details of your database.
• It creates the time dimension and hierarchy in your data model based on the parameters that you specify, such as the name of the dimension, the name of the hierarchy, and the levels and attributes of the hierarchy. References: [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 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]

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]

Data wrangling is a process of transforming and enriching data to make it more suitable for analysis or visualization. Some statements that are true about data wrangling are:

• In data wrangling, transformations available are dependent on the data type. For example, you can apply different transformations to numeric, text, date, or location data types.
• It is used to curate data sets that can be used for complex visualizations. For example, you can use data wrangling to create calculated columns, merge or split columns, group or aggregate values, filter or sort rows, or join or union data sets. References: [Oracle Analytics Cloud - Data Visualization User’s Guide], [Oracle Analytics Cloud - Data Visualization User’s Guide]

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]

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]

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

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]