[Mar 26, 2024] Free Oracle 1z0-1041-23 Exam Questions and Answer
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NEW QUESTION # 33
What does a trend line highlight in Oracle Analytics Cloud?
- A. A general pattern or direction of data when viewed in relation to a time series
- B. A general pattern or direction of data when viewed in relation to other dimensions
- C. A line representing the average values of a measure
- D. A line representing the median values of a measure
Answer: A
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 # 34
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. Insights is a/ways shared in form of story so everybody will see the same information.
- 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. It is not possible to share Insights with other users.
Answer: A,B
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 # 35
Which three could improve the results from Natural Language Query (NLQ) with Oracle Day By Day?
- A. Acronyms
- B. Curating the exposed data sets by removing duplicate or unnecessary attributes
- C. Pre-caching NLQ metadata search elements
- D. Exposing a limited number of data sets for Day By Day NLQ
- E. Snonyms
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 # 36
You have a global data set for oil princes for a period of time for each country.
However, you need to perform analyses on Asian countries for a period of one month Which two combinations of filters could you use to achieve this?
- A. Expression and Date Range
- B. Range and Expression
- C. Date Range and Top Bottom N
- D. List and Range
- E. List and Date Range
Answer: A,E
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 37
You have the Bl Service Administrator application role and you are notified that a user cannot get answers when using Day by Day with Oracle Analytics Cloud Professional Edition.
They asked a question related to an existing data set and the language was English.
Which three statements are valid about investigating this issue?
- A. Inspect the data set and make sure that it is certified, indexed for searching, and English language is selected.
- B. Inspect the data set and check the access control.
- C. Verify that the user has been assigned the BI Content Author and Bl Data Load Author roles.
- D. Verify that the user is assigned the BI Content Author and DV Consumer roles.
- E. Day by Day does not work with Oracle Analytics Cloud Professional Edition.
Answer: A,B,C
Explanation:
To investigate why a user cannot get answers when using Day by Day with Oracle Analytics Cloud Professional Edition, you can do the following steps:
Verify that the user has been assigned the BI Content Author and Bl Data Load Author roles. These roles are required to access and use Day by Day features, such as asking questions using natural language or voice, or getting personalized insights based on usage patterns.
Inspect the data set and check the access control. You need to make sure that the user has sufficient permissions to view and query the data set that they asked a question about.
Inspect the data set and make sure that it is certified, indexed for searching, and English language is selected. These are some of the criteria that make a data set eligible for Day by Day queries. You can use the Manage menu in Data Sets to check and modify these settings. Reference: [Oracle Day By Day User's Guide], [Oracle Day By Day User's Guide], [Oracle Day By Day User's Guide]
NEW QUESTION # 38
You are building a model that will be used for a sales report.
Which two statements are the about hierarchy and levels?
- A. A hierarchy must have one to many relationships between attributes.
- B. Skipped levels and unbalanced hierarchies can be enabled for all the dimension tables.
- C. A dimension table must have only one hierarchy.
- D. Hierarchies enable drilling in reports.
- E. A hierarchy shows relationships among a group of columns in a fact table.
- F. Each level is based on one or multiple columns.
- G. When defining a level. Key Columns must be the same as Display Columns.
Answer: D,F
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 # 39
Which three statements are true about usage tracking in Oracle Analytics Cloud?
- A. You create a new connection pool in the Oracle Analytics Developer Client tool.
- B. It is available for both Professional and Enterprise Edition.
- C. After a change has been made to the Usage Tracking Connection Pool setting in the console, a restart is required.
- D. It is available only for Enterprise Edition.
- E. You create a new connection pool in Data Modeler.
Answer: A,C,D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 40
How should you determine the accuracy of a Machine Learning Model created in Oracle Analytics Cloud (OAC)?
- A. Open the inspect dialog for given Machine i earning model and review the F1 score.
- B. Use the Debug option in the Data Flow where the model was created. Create Data Flow that includes a histogram.
- C. Open the inspect dialog for a given Machine Learning model and review the p score.
- D. Run the Machine earning model with various filter values applied.
Answer: A
Explanation:
To determine the accuracy of a machine learning model created in Oracle Analytics Cloud, you can open the inspect dialog for the given machine learning model and review the F1 score. The F1 score is a metric that measures the balance between precision and recall of a machine learning model, especially for binary classification problems. The F1 score ranges from 0 to 1, where 1 means perfect accuracy and 0 means no accuracy. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
NEW QUESTION # 41
You need to compute sales for a period that starts at a quarter before and ends at a quarter after the current quarter.
Which Time Series function will you use?
- A. TODATE
- B. PERIODROLLING
- C. FORECAST
- D. AGO
Answer: B
Explanation:
To compute sales for a period that starts at a quarter before and ends at a quarter after the current quarter, you need to use the PERIODROLLING function. This function allows you to calculate the aggregated value of a measure over a rolling time period relative to the current time level. For example, PERIODROLLING("Sales", -1, 1, "Quarter") will return the sum of sales for the current quarter, the previous quarter, and the next quarter. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide
NEW QUESTION # 42
Your client wants to implement a custom plug in from Oracle Analytics Library. Vou just finished uploading the extension to Oracle Analytics Cloud (OAC).
What action do you need to take before the extension is available for use in projects?
- A. Enable the plug-in from the Plug-in menu.
- B. No additional action is needed.
- C. Restart the OAC instance.
- D. Refresh the page.
Answer: D
Explanation:
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. Reference: Oracle Help Center, Oracle Help Center, Oracle Help Center
NEW QUESTION # 43
Which two can be used to display as prompts in your Publisher report?
- A. Expression filters
- B. Number filters
- C. List filters
- D. Lists of values
- E. Date Filters
Answer: A,B
Explanation:
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. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
NEW QUESTION # 44
You have created the product type dashboard prompt and applied it to the Sales dashboard. In the Sales dashboard, you have three pages: Sales, Order, and Revenue.
The dashboard prompt is applied to all pages, but you want it only for the Sales page.
What configuration changes are required to change the dashboard prompt range?
- A. In the Dashboard editor, go to dashboard properties and charge the scope from Dashboard to Page.
- B. In the Prompt Configuration option, change the Choose input Type.
- C. In the Dashboard editor, edit the section and add a condition to change the scope.
- D. In the Dashboard editor, edit the dashboard prompt properties and change the scope from Dashboard to Page.
Answer: D
Explanation:
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. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide
NEW QUESTION # 45
You are creating an analytics solution for a financial institution using Oracle Analytics Cloud.
One of the requirements is a workbook with a model that identifies customers with multiple potential infraudulent transactions.
Which algorithm would be the best fit for this purpose?
- A. Logistic Regression
- B. Decision Tree
- C. Anomaly Detection
- D. Support Vector Machine
Answer: C
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 46
Which two filters can be applied to all Dimensional data types?
- A. List
- B. Date
- C. Range
- D. Expression
Answer: A,D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 47
Which data action must you use to connect to Oracle Analytics Publisher reports?
- A. Publish Event
- B. HTTP API
- C. Webhooks
- D. Analytics Link
- E. URL Navigation
Answer: D
Explanation:
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. Reference: [Oracle Help Center]
NEW QUESTION # 48
In Oracle Analytics Cloud (OAC), you can quickly search for saved objects.
However, if your input or search criteria is not formed correctly, it will not return any results. What could be the problem with your input?
- A. The input contains an asterisk (*) in the search text (for example, 'revenue).
- B. The input contains a comma (,) in the search text.
- C. The input contains the date attribute in the year-month-day format
- D. The input contains the object name only as search text.
Answer: B
Explanation:
The input containing a comma (,) in the search text is a possible problem that could prevent you from getting any results when searching for saved objects in Oracle Analytics Cloud. The comma is a special character that is used to separate multiple search terms or phrases. If you use a comma in your search text, you need to enclose the text in double quotation marks ("") to indicate that it is a single term or phrase. For example, if you want to search for an object named "Sales, Revenue, and Profit", you need to enter it as ""Sales, Revenue, and Profit"" in the search box. The other options are not problems with the input, as they are valid ways to search for saved objects. You can use an asterisk () as a wildcard character to match any number of characters in your search text (for example, "revenue"). You can use the object name only as search text, as this will return all objects that match or contain the name. You can use the date attribute in the year-month-day format, as this will return all objects that were created or modified on that date. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 49
Which service do you need to subscribe for creating an Oracle Analytics Cloud (OAC) instance?
- A. Oracle Autonomous Database
- B. Oracle Big Data Cloud Storage
- C. Oracle Back Storage
- D. Oracle Analytics Cloud
Answer: D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 50
You are designing an analytics solution for a company that distributes packaged foods for independent retailers. The solution requires self-service analytics capabilities for product management and In addition, highly formatted reports must be delivered by scheduled email to external resellers Which edition of Oracle Analytics must you use
- A. OAC Business Intelligence Edition
- B. OA Data Visualization Cloud
- C. OAC Professional Edition
- D. OAC Enterprise Edition
- E. OA Fusion Analytics Warehouse Edition
Answer: D
Explanation:
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. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
NEW QUESTION # 51
Which two statements are true about data wrangling?
- A. In data wrangling, transformations available are dependent on the data type.
- B. It is used to perform some lightweight transformation within the data visualization UI.
- C. It is used to curate data sets that can be used for complex visualizations.
- D. It is used to tram and test the Machine Learning model.
Answer: A,C
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 # 52
You have added a forecast to your visualization. Which three models are available for calculating the forecast7
- A. ARIMA
- B. ARENA
- C. Seasonal ARENA
- D. Seasonal ARIMA
- E. Seasonal ETS
- F. ETS
Answer: C,E,F
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 53
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