Pass 1z0-1041-23 Exam Latest Practice Questions Updated on Jan 06, 2024
Oracle 1z0-1041-23 Study Guide Archives
NEW QUESTION # 27
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. Package (.dva)
- E. AutoCad (.dxf)
Answer: A,C,D
Explanation:
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]
NEW QUESTION # 28
Which two statements are true about data wrangling?
- A. It is used to perform some lightweight transformation within the data visualization UI.
- B. In data wrangling, transformations available are dependent on the data type.
- C. It is used to tram and test the Machine Learning model.
- D. It is used to curate data sets that can be used for complex visualizations.
Answer: B,D
Explanation:
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. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
NEW QUESTION # 29
You are creating a data model for a healthcare provider Patient information is contained in related tables for contact information, primary physician, insurance information, and billing details.
For management and personal information reasons, the project owner requires that these table not be merged.
What is the correct relational topology to model the patient dimension?
- A. Distributed tree
- B. Start
- C. Balance tree
- D. Universe
Answer: C
Explanation:
Balance tree is the correct relational topology to model the patient dimension for a healthcare provider in Oracle Analytics Cloud. A balance tree is a type of schema that consists of one or more dimension tables that are related to each other by foreign keys. A balance tree schema allows you to model a dimension that has multiple attributes that are organized into different levels of detail. For example, you can model a patient dimension that has attributes such as contact information, primary physician, insurance information, and billing details. Each attribute can be stored in a separate table that is linked to a parent table by a foreign key. A balance tree schema enables you to perform drill-down analysis on your dimension without having to merge all the tables into one. The other types of schemas, such as distributed tree, universe, and star, are not suitable for modeling a patient dimension with multiple related tables. A distributed tree schema consists of one or more dimension tables that are not related to each other by foreign keys. A universe schema consists of one or more fact tables that are related to each other by foreign keys. A star schema consists of one fact table that is related to multiple dimension tables by foreign keys. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 30
Which two are true about dashboard prompts?
- A. Prompt values can be limited based on values selected in other prompts.
- B. Repository variables and session variables can be used in prompt default values.
- C. All prompts must be displayed on a single page.
- D. Prompts can be developed using only a single column.
Answer: A,B
Explanation:
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. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide
NEW QUESTION # 31
You are creating a Data Model for a sales order and do not have the Time dimension table created in the database.
You decide to use the Time Dimension create feature of Oracle Analytics Cloud (OAC) What are the tasks performed by the Time Dimension wizard execution?
- A. The Time Dimension wizard creates the Time dimension table in the database and loads time data.
- B. The Time Dimension wizard creates the time dimension table in the database, loads time data, and creates the time dimension in the Data Model.
- C. The Time Dimension wizard generated the DDL query for the Time dimension table and inserts SQL for data load, which you need to run on your respective database schema.
- D. The Time Dimension wizard creates the Time dimension table in the database, load time data, and create the time dimension and hierarchy in the Data Model.
Answer: D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 32
Which two are supported on the home page of a BI Ask visualization?
- A. Drilling down on the visualizations.
- B. opening visualizations in the Oracle Analytics Cloud home page to customize and add to a project
- C. View data from multiple data sets \n a single query.
- D. saving visualizations displayed on the Oracle Analytics Cloud home page
Answer: A,C
Explanation:
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]
NEW QUESTION # 33
Which technique does Data Preparation in OAC use for as SSN, credit card number, and customer number?
- A. Sentiment Analysis algorithms
- B. Cryptographic algorithms to encrypt sensitive information
- C. Obfuscation to protect sensitive information
- D. Advanced Analytics functions
Answer: C
Explanation:
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
NEW QUESTION # 34
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. Bundle
- B. Extrapolate
- C. Bin
- D. Convert
Answer: C
Explanation:
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]
NEW QUESTION # 35
Which relational database schema consists than in single-dimension tables?
- A. Network
- B. Sun Snowflake schema
- C. Star schema
- D. Leaf
Answer: D
Explanation:
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]
NEW QUESTION # 36
Which two can be defined on a canvas in a story in Oracle Analytics Cloud?
- A. Narration
- B. Filters
- C. Notes
- D. Notifications
Answer: B,D
Explanation:
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]
NEW QUESTION # 37
You are building a model that will be used for a sales report.
Which two statements are the about hierarchy and levels?
- A. Each level is based on one or multiple columns.
- B. A hierarchy must have one to many relationships between attributes.
- C. Hierarchies enable drilling in reports.
- D. Skipped levels and unbalanced hierarchies can be enabled for all the dimension tables.
- E. A hierarchy shows relationships among a group of columns in a fact table.
- F. A dimension table must have only one hierarchy.
- G. When defining a level. Key Columns must be the same as Display Columns.
Answer: A,C
Explanation:
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]
NEW QUESTION # 38
The Administrator has navigated to the console page and clicked on search index. Which three items can be included in the index?
- A. Templates
- B. Data Models
- C. Shared Folders
- D. User Folders
- E. Content Folder
Answer: B,C,D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 39
What does a trend line highlight in Oracle Analytics Cloud?
- A. A line representing the average values of a measure
- B. A line representing the median values of a measure
- C. A general pattern or direction of data when viewed in relation to other dimensions
- D. A general pattern or direction of data when viewed in relation to a time series
Answer: D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 40
Using Narrate insight, you can take a snapshot of any moments of any information that you see in a visualization and keep track of any moments of sudden realization while you work with the data.
You can then share these with other users. Which statement is true about sharing with Insights?
- A. It is not possible to share Insights with other users.
- B. Insights is shared as a story and everybody will see their information based on permissions
- C. By default all users cannot share Insights.
- D. Insights is a/ways shared in form of story so everybody will see the same information.
Answer: B,D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 41
Which three could improve the results from Natural Language Query (NLQ) with Oracle Day By Day?
- A. Snonyms
- B. Curating the exposed data sets by removing duplicate or unnecessary attributes
- C. Exposing a limited number of data sets for Day By Day NLQ
- D. Pre-caching NLQ metadata search elements
- E. Acronyms
Answer: A,B,E
Explanation:
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. Reference: [Oracle Day By Day User's Guide], [Oracle Day By Day User's Guide], [Oracle Day By Day User's Guide]
NEW QUESTION # 42
Which two can be defined on a canvas in a story in Oracle Analytics Cloud?
- A. Narration
- B. Filters
- C. Notes
- D. Notifications
Answer: B,D
Explanation:
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]
NEW QUESTION # 43
How can Oracle Analytics Cloud (OAC) be used to categorize a large number of data points on a particular canvas?
- A. Use a combination of a tree diagram and a trellis visualization.
- B. Create a trend line and apply OAC Advanced Analytics.
- C. Create a cluster with a suitable number of groups for the specific analysis.
- D. Visualize the data by using a network chart.
Answer: C
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 44
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 List filter for Sales Amount
- C. List filter for Region and Expression filter for Sales Amount
- D. List filter for Region and Range filter for Sales Amount
Answer: A,B
Explanation:
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]
NEW QUESTION # 45
You are a developer designing a solution to analyze retail sales. A key requirement for the solution is a product hierarchy with multiple levels that supports drill-down in an Oracle Analytics Cloud (OAC) workbook.
Which two configurations are appropriate for your solution?
- A. Data set created with data preparation
- B. Semantic model created in the Thin Client Modeler
- C. Data set merging a semantic model with the hierarchy and additional data
- D. Hierarchy created in a proper snowflake multi-table data set
- E. Data set with a hierarchy created in OAC Data Flow
- F. Semantic model created in the OA Admin tool
Answer: D,F
Explanation:
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. Reference: Oracle Help Center, [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 46
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