[2024年04月13日]1z0-1041-23問題集PDFとテストエンジン 試験問題
検証済みの1z0-1041-23テスト問題集と解答で正確な72問題解答あります
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質問 # 38
You have been tasked with building an analysis that requires data from two subject areas. How do you accomplish this?
- A. Create two separate analyses and use the merge feature.
- B. Create an analysis and add a second subject area for a union.
- C. A subject area must be modified to include all the columns required.
- D. Create two separate analyses and use the union feature.
正解：B
解説：
To build an analysis that requires data from two subject areas, you can create an analysis and add a second subject area for a union. A union is an operation that combines two or more data sets with similar columns into one data set. You can use the Add Subject Area option in the Criteria tab of an analysis to add another subject area and select Union as the operation type. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 39
Data How can take one or more data sets and integrate them to produce curated sets of dat a. After applying all the joins, transformations, and filters, you need to save the data. What are the two options to save data in Data Flow?
- A. Spreadsheet
- B. All Rows
- C. Data Set Storage
- D. Database Connection
正解：C、D
解説：
After creating a data flow, you need to save the output data to a destination. You have two options to save data in Data Flow:
Data Set Storage: This option allows you to save the output data as a data set in Oracle Analytics Cloud. You can choose the name, description, and format of the data set. You can also specify whether to overwrite or append the existing data set.
Database Connection: This option allows you to save the output data to an external database that you have connected to Oracle Analytics Cloud. You can choose the connection, schema, table name, and mode of the database destination. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 40
Which type of report is an example of the bursting feature in Pixel Perfect Reporting?
- A. Bar codes
- B. Customized regional marketing reports
- C. Ad hoc reporting
- D. Interactive data exploration
- E. Government PDF forms
正解：E
解説：
Government PDF forms is an example of the bursting feature in Pixel Perfect Reporting in Oracle Analytics Cloud. Pixel Perfect Reporting is a feature that allows you to create and publish highly formatted reports that meet specific layout and design requirements, such as invoices, statements, receipts, labels, and more. You can use Pixel Perfect Reporting to create reports using various tools and options, such as templates, layouts, components, expressions, parameters, and more. You can also use Pixel Perfect Reporting to publish reports using various methods and formats, such as email, printer, file system, FTP server, PDF, HTML, RTF, Excel, PowerPoint, and more. The bursting feature is a feature that allows you to distribute reports to multiple recipients based on certain criteria or conditions. You can use the bursting feature to create personalized reports for each recipient that contain only relevant information for them. You can also use the bursting feature to deliver reports to each recipient using their preferred method and format. Government PDF forms is an example of the bursting feature in Pixel Perfect Reporting in Oracle Analytics Cloud. You can use this feature to create and distribute government PDF forms that comply with specific standards and regulations for each recipient based on their location or status. The other options, such as ad hoc reporting, customized regional marketing reports, interactive data exploration, and bar codes are not examples of the bursting feature in Pixel Perfect Reporting in Oracle Analytics Cloud. These options are either not related to Pixel Perfect Reporting or describe other types of reports or features that can be created or used in Oracle Analytics Cloud. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 41
Which technique does Data Preparation in OAC use for as SSN, credit card number, and customer number?
- A. Obfuscation to protect sensitive information
- B. Advanced Analytics functions
- C. Sentiment Analysis algorithms
- D. Cryptographic algorithms to encrypt sensitive information
正解：A
解説：
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
質問 # 42
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. Support Vector Machine
- D. Anomaly Detection
正解：D
解説：
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]
質問 # 43
You need to curate data for Country Dimension and dependent Sales Facts that store country sales data.
How do you design the data flow and load data for these two separate data sets in data storage?
- A. Create a single data flow that loads data to the Country data storage in the first step and then loaders data storage in the seconds the flows for the Country and Sales data sets.
- B. Create data flows for the Country and Sales data sets. Then create a sequence where the data flow for Sales is called first followed by the data flow for Country.
- C. Create two separate data flows for the Country and Sales data sets. Then call one data flow from another.
- D. Create two separate data flows for the Country and Sales data sets. Then create a sequence "low for Country is called first followed by the data flow for Sales.
正解：B、C
解説：
There are two possible ways to design the data flow and load data for these two separate data sets in data storage:
Create two separate data flows for the Country and Sales data sets. Then call one data flow from another using a Call Data Flow step. This will allow you to execute one data flow after another in a single run.
Create data flows for the Country and Sales data sets. Then create a sequence that defines the order of execution of these data flows using a Sequence step. This will allow you to run multiple data flows sequentially or in parallel. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 44
Oracle Applications Connector supports Oracle Fusion Applications Cloud.
Which is valid about Oracle Applications Connector?
- A. When creating a connection, enter the Business Intelligence URL for Oracle Fusion Applications
- B. It cannot be used with Oracle Applications Connector.
- C. When abating a connection, enter the URL for Oracle Fusion Applications.
- D. The Active User's Credentials option in the Create Oracle Application Connection dialog box.
- E. It cannot connect to on-premises Oracle BI Enterprise Edition.
- F. It can be used with the Thin Client Modeler.
正解：C
解説：
Oracle Applications Connector supports Oracle Fusion Applications Cloud, which is a suite of cloud applications that provide enterprise resource planning, human capital management, customer relationship management, and other functionalities. To create a connection to Oracle Fusion Applications Cloud using Oracle Applications Connector, you need to enter the URL for Oracle Fusion Applications in the Create Oracle Application Connection dialog box. The other options are not valid about Oracle Applications Connector. You do not need to enter the Business Intelligence URL for Oracle Fusion Applications, as this is not required for the connection. The Active User's Credentials option is not available in the Create Oracle Application Connection dialog box, as this is only applicable for some other types of connections. Oracle Applications Connector can be used with Oracle Applications Connector, as this is its purpose. It can also connect to on-premises Oracle BI Enterprise Edition, as this is one of the supported sources. It cannot be used with the Thin Client Modeler, as this is a separate tool that does not require a connection. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 45
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. Extrapolate
- B. Bin
- C. Convert
- D. Bundle
正解：B
解説：
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]
質問 # 46
Your client wants you to build visualizations that will help them understand their data better. Which two methods will help them achieve this?
- A. Add trend lines, clustering, and outliers to visualizations to offer new perspectives
- B. Use the explain feature to quickly identify Basic Facts, Key Drivers, Segments, and Anomalies.
- C. Create Data Flow to highlight interesting data.
- D. Create a sequence and schedule it to run on a nightly basis.
- E. Add the relevant visualizations to a canvas.
正解：B、E
解説：
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 47
Which two statements are true about Action Links?
- A. A column's navigation option can be enabled conditionally.
- B. Presentation variables can be used while navigating from one analysis to another.
- C. Navigation from one analysis to another is not possible if they reside in different folders.
- D. Navigation from one analysis to another works only when both analyses are created from a single subject area.
正解：A、B
解説：
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
質問 # 48
You have a data set of stocks with the columns Date, MaxStockPrice and MinStockPrince.
Which column cannot be removed when performing a trend analysis?
- A. MintStockPrince
- B. All columns are required
- C. Date
- D. MaxStackPrince
正解：C
解説：
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. Reference: [Oracle Help Center]
質問 # 49
You have added a forecast to your visualization. Which three models are available for calculating the forecast7
- A. Seasonal ETS
- B. Seasonal ARIMA
- C. ETS
- D. ARIMA
- E. Seasonal ARENA
- F. ARENA
正解：A、C、E
解説：
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]
質問 # 50
Oracle Analytics Cloud (OAC) offers several visualization options for presenting query results Which two methods do you use to invoke the best visualization in OAC?
- A. Select the desired data elements from the Data Elements pane and drag them to the Best visualization zone in the Explore pane.
- B. Select the Best Visualization option from the project's Canvas Settings drop-down menu.
- C. Select the desired data elements from the Data Elements pane, and then right-click and select Create Best Visualization from the drop-down menu.
- D. Change the project's properties to "Always use Best Visualization
- E. Select the desired data elements from the Data Elements pane and drag them to a blank area of the canvas.
正解：A、C
解説：
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. Reference: [Oracle Help Center], [Oracle Help Center]
質問 # 51
What does a trend line highlight in Oracle Analytics Cloud?
- A. A general pattern or direction of data when viewed in relation to other dimensions
- B. A line representing the median values of a measure
- C. A general pattern or direction of data when viewed in relation to a time series
- D. A line representing the average values of a measure
正解：C
解説：
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]
質問 # 52
What does a single transaction mean in a sequence of data flows?
- A. A data flow can load to a single data set at one point.
- B. Multiple data flows in a sequence run one after the other. However, if any now falls, all the changes made in the sequence are rolled back.
- C. If any flow within a sequence fails, all the changes made in the sequence remain as is.
- D. A sequence can have only one data flow to save data to multiple data storage.
正解：B
解説：
A single transaction means that all the data flows in a sequence are executed as a unit of work. If any data flow fails, the entire sequence is aborted and the changes made by the previous data flows are rolled back to ensure data consistency and integrity. Reference: Oracle Analytics Cloud - Data Visualization User's Guide
質問 # 53
Which two filters can be applied to all Dimensional data types?
- A. List
- B. Expression
- C. Range
- D. Date
正解：A、B
解説：
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]
質問 # 54
Your client has created new custom map layer. How can this map layer be exposed in a project?
- A. Create a new project. Add a map visualization. Change the layer property to new. Click upload. Select the Json file to upload.
- B. Create a new project. Add a map visualization, change the layer property to new. click upload. Select the geojson file to upload.
- C. Navigate to the Console. Click Maps. From the Map Layers tab, upload the geojson file.
- D. Navigate to the Console. Click Maps. On the Map Layers tab, upload the xml file.
正解：D
解説：
To expose a new custom map layer in a project, you need to do the following steps:
Navigate to the Console by clicking the Home icon on the top left corner of the screen and then clicking Console.
Click Maps on the left navigation pane to open the Maps page.
On the Map Layers tab, click Upload to upload your custom map layer file. The file must be in XML format and follow the Oracle Analytics Cloud map layer specification.
After uploading your custom map layer file, you can see it in the list of available map layers and use it in your projects. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 55
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. Date Range and Top Bottom N
- B. List and Range
- C. List and Date Range
- D. Expression and Date Range
- E. Range and Expression
正解：C、D
解説：
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]
質問 # 56
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. Day by Day does not work with Oracle Analytics Cloud Professional Edition.
- B. Inspect the data set and make sure that it is certified, indexed for searching, and English language is selected.
- C. Inspect the data set and check the access control.
- D. Verify that the user is assigned the BI Content Author and DV Consumer roles.
- E. Verify that the user has been assigned the BI Content Author and Bl Data Load Author roles.
正解：B、C、E
解説：
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]
質問 # 57
Which role is required to edit and create a new semantic model in Oracle Analytics Cloud Enterprise Edition?
- A. BI Data Load Author
- B. DV Consumer Role
- C. BI RPD Model Author
- D. BI Content Author
- E. BI Data Model Author
正解：E
解説：
To edit and create a new semantic model in Oracle Analytics Cloud Enterprise Edition, you need to have the BI Data Model Author role. This role allows you to access and use the Data Modeler tool, where you can create and modify semantic models that define the logical structure and relationships of your data sources. You can also use the Data Modeler to create calculations, hierarchies, variables, security filters, and other features for your semantic models. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 58
Identify the correct use of BI Ask.
- A. is used to power the type ahead functionality.
- B. is used to search for projects
- C. is used to enable user input in Natural Language. It extracts column names from the User Input and quickly build visuals for the columns extracted
- D. is used to search for visualizations
- E. is used to enter column names into the search hold, select them, and quickly see them added to a project
正解：C
解説：
The correct use of BI Ask is that it is used to enable user input in natural language. It extracts column names from the user input and quickly builds visuals for the columns extracted. BI Ask is a feature that allows you to create analyses using natural language queries instead of dragging and dropping columns from the subject area pane. You can type or speak your query in BI Ask and it will automatically generate the best visualization for your query based on the columns extracted from your input. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 59
Which two can be used to display as prompts in your Publisher report?
- A. Date Filters
- B. Lists of values
- C. Expression filters
- D. Number filters
- E. List filters
正解：C、D
解説：
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]
質問 # 60
Which two statements are true about Oracle Analytics Cloud (OAC) self-service data preparation
- A. The Oracle Data Integrator (ODI) tool, which is used for extract, load, and transformation, foundational component of Oracle Analytics Cloud and is essential for data preparation.
- B. Database data can be extended with spreadsheet data.
- C. Data flows have many built-in steps that can be used to prepare the data.
- D. Joins can be created only in Oracle Analytics Cloud Data Modeler.
正解：B、C
解説：
Oracle Analytics Cloud (OAC) self-service data preparation is a feature that allows you to transform and enrich data from various sources and create data sets for analysis or visualization. Some statements that are true about OAC self-service data preparation are:
Database data can be extended with spreadsheet data. This means that you can join or union data from a database source with data from a spreadsheet file and create a new data set that combines both sources.
Data flows have many built-in steps that can be used to prepare the data. This means that you can use data flows to perform various operations on your data, such as creating calculated columns, filtering or sorting rows, grouping or aggregating values, applying machine learning models, or saving data to different formats. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide
質問 # 61
You have been given a spreadsheet that contribute to employee attrition data to determine the most important factors that contribute to employee attrition.
What is the quickest way to start this analysis after uploading data to Oracle Analytics Cloud (OAC)?
- A. Perform a cluster analysis of employees.
- B. Use Outlier identification.
- C. Use the Explain option on the Attrition attribute.
- D. Calculate a forecast of the probability of attrition.
正解：C
解説：
The quickest way to start the analysis of employee attrition data after uploading it to Oracle Analytics Cloud is to use the Explain option on the Attrition attribute. The Explain option is a feature that allows you to automatically generate insights and visualizations about an attribute or a measure in your data set. In this case, the Explain option will show you the most important factors that contribute to employee attrition, such as salary, job satisfaction, or performance rating. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, [Oracle Analytics Cloud - Data Visualization User's Guide]
質問 # 62
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