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NEW QUESTION # 18
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 two separate data flows for the Country and Sales data sets. Then call one data flow from another.
- 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 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.
- 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.
Answer: A,B
Explanation:
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]
NEW QUESTION # 19
Which are two use-cases for Data Flow?
- A. Perform some lightweight transformation within the Project.
- B. To curate data sets that can be used for visualizations.
- C. Create a custom Python Machine Learning model.
- D. Train and test the Machine Learning model.
Answer: B
Explanation:
Data Flow is a feature of Oracle Analytics Cloud that enables you to create and run data flows to transform and enrich your data. You can use Data Flow for various use-cases, such as:
To curate data sets that can be used for visualizations. You can join, filter, aggregate, pivot, and perform other operations on your data sets to prepare them for analysis.
To train and test the Machine Learning model. You can use Data Flow to apply machine learning algorithms to your data and create predictive models. You can also evaluate the performance of your models and compare them with different parameters. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 20
In which two layers can you use Oracle Analytics Cloud (OAC) to determine which values of a given data set may provide the greatest opportunity due to their outlier qualities?
- A. Modify the color palette to highlight unique values.
- B. Use a combination of Max/Min value reference lines.
- C. Add an outlier visualization to your canvas. This will highlight data points that stand out and may justify further investigation.
- D. Create a box plot visualization of your data set.
Answer: C,D
Explanation:
Oracle Analytics Cloud (OAC) provides various ways to identify and analyze outliers in your data set. Outliers are data points that deviate significantly from the rest of the data and may indicate errors, anomalies, or opportunities. Two layers that you can use to determine which values of a given data set may provide the greatest opportunity due to their outlier qualities are:
Add an outlier visualization to your canvas. This will highlight data points that stand out and may justify further investigation. An outlier visualization is a type of scatter plot that automatically detects and labels outliers in your data using machine learning algorithms. You can use the outlier visualization to explore the characteristics and causes of the outliers and compare them with the normal data points.
Create a box plot visualization of your data set. A box plot is a type of graph that shows the distribution of a numerical variable using quartiles and whiskers. A box plot can also identify outliers as data points that lie beyond the whiskers or outside a certain range. You can use the box plot to see how the outliers affect the overall distribution and variation of your data.
NEW QUESTION # 21
Oracle Applications Connector supports Oracle Fusion Applications Cloud.
Which is valid about Oracle Applications Connector?
- A. It cannot connect to on-premises Oracle BI Enterprise Edition.
- B. When creating a connection, enter the Business Intelligence URL for Oracle Fusion Applications
- C. It can be used with the Thin Client Modeler.
- D. The Active User's Credentials option in the Create Oracle Application Connection dialog box.
- E. It cannot be used with Oracle Applications Connector.
- F. When abating a connection, enter the URL for Oracle Fusion Applications.
Answer: F
Explanation:
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]
NEW QUESTION # 22
Which two steps do you perform to create a Relative Time filter?
- A. Add a date column to the Filter bar.
- B. Select Relative Time as the filter type.
- C. Select Relative Time as the filter type and set the Relative To property.
- D. Select Date Range as the filter type.
Answer: B,C
Explanation:
To create a relative time filter, you need to perform two steps:
Select Relative Time as the filter type: A relative time filter allows you to filter your data based on a relative time period, such as last week, next month, or current year. You can select Relative Time as the filter type from the drop-down menu of the filter bar.
Select Relative Time as the filter type and set the Relative To property: The Relative To property allows you to specify the reference point for your relative time period. For example, if you want to filter your data for the last quarter relative to today, you can set the Relative To property to Today. You can set the Relative To property from the filter dialog box after selecting Relative Time as the filter type. Reference: [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 23
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. AGO
- B. PERIODROLLING
- C. TODATE
- D. FORECAST
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 # 24
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. MaxStackPrince
- C. Date
- D. All columns are required
Answer: C
Explanation:
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]
NEW QUESTION # 25
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. 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. Inspect the data set and check the access control.
Answer: B,C,E
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 # 26
You have been tasked with building an analysis that requires data from two subject areas. How do you accomplish this?
- A. Create an analysis and add a second subject area for a union.
- B. Create two separate analyses and use the merge feature.
- C. Create two separate analyses and use the union feature.
- D. A subject area must be modified to include all the columns required.
Answer: A
Explanation:
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]
NEW QUESTION # 27
What does a fact table use to reference dimension tables?
- A. Foreign key
- B. Aggregate type
- C. Master key
- D. Primary key
- E. Dimension attribute
Answer: A
Explanation:
A fact table uses a foreign key to reference dimension tables in a relational database schema. A fact table is a table that contains numerical measures or facts that are related to a business process or event, such as sales, orders, or transactions. A dimension table is a table that contains descriptive attributes or dimensions that provide context to the facts, such as product, customer, time, or location. A foreign key is a column or a set of columns in a table that refers to the primary key of another table. A primary key is a column or a set of columns in a table that uniquely identifies each row in the table. A foreign key establishes a relationship between the fact table and the dimension tables, and allows you to join them for analysis. The other options, such as dimension attribute, aggregate type, and master key, are not used by a fact table to reference dimension tables. A dimension attribute is a column in a dimension table that contains a specific level or detail of the dimension, such as product name, customer name, or month. An aggregate type is a property of a measure column that specifies how the measure should be aggregated or calculated, such as sum, average, count, or minimum. A master key is not a valid term in relational database schema. Reference: Oracle Help Center, Oracle Help Center
NEW QUESTION # 28
Which three could improve the results from Natural Language Query (NLQ) with Oracle Day By Day?
- A. Curating the exposed data sets by removing duplicate or unnecessary attributes
- B. Exposing a limited number of data sets for Day By Day NLQ
- C. Snonyms
- D. Pre-caching NLQ metadata search elements
- E. Acronyms
Answer: A,C,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 # 29
Which two filters can be applied to all Dimensional data types?
- A. Date
- B. Range
- C. List
- D. Expression
Answer: C,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 # 30
Which two are true about creating a story in Oracle Analytics Cloud?
- A. A story can have multiple multiple canvases.
- B. Insight always take a snapshot data for a story.
- C. A project can have only one story.
- D. You can only export the active visual.
Answer: A,D
Explanation:
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. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
NEW QUESTION # 31
You have created a Machine Learning model and investigated how accurate it \s. How should you use it in Oracle Analytics Cloud (OAC)?
- A. Create Data Flow with a cumulative value prediction.
- B. Create a custom calculation based on a related formula.
- C. Connect to the model as a new project.
- D. Use Data Flow with an Apply Model step and save as a new data set.
- E. Use a data flow with a Commit Model step and save as a new data set.
Answer: D
Explanation:
After creating and testing a machine learning model, you can use it to make predictions on new data sets using a data flow. A data flow is a sequence of steps that transform and enrich data from one or more sources. An Apply Model step allows you to apply a previously trained model to a new data set and generate predictions as a new column. You can then save the output of the data flow as a new data set for further analysis or visualization. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, [Oracle Analytics Cloud - Data Visualization User's Guide]
NEW QUESTION # 32
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. Open the inspect dialog for a given Machine Learning model and review the p score.
- C. Run the Machine earning model with various filter values applied.
- D. Use the Debug option in the Data Flow where the model was created. Create Data Flow that includes a histogram.
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 # 33
You have a Historical Sales data set, which you use to train a model in Oracle Anatytics Cloud (OAC) Your products have an attribute named Profitability, which has one of the three values: high, medium, c This is the property you set as the target.
Which train data step is required to train a model in
- A. Train Multi-Classifier
- B. Train Clustering
- C. Train Numeric Prediction
- D. Train Binary-Classifier
- E. Train Multi-Value
- F. Train Text Prediction
Answer: A
Explanation:
A multi-classifier is a machine learning model that can predict one of several possible classes for a given input. In this case, the target attribute Profitability has three possible values: high, medium, or low. Therefore, a multi-classifier is the appropriate model to train on this data set. Reference: Oracle Analytics Cloud - Data Visualization User's Guide, Oracle Analytics Cloud - Data Visualization User's Guide
NEW QUESTION # 34
Your client has created new custom map layer. How can this map layer be exposed in a project?
- A. Navigate to the Console. Click Maps. On the Map Layers tab, upload the xml file.
- B. Create a new project. Add a map visualization. Change the layer property to new. Click upload. Select the Json file to upload.
- C. Create a new project. Add a map visualization, change the layer property to new. click upload. Select the geojson file to upload.
- D. Navigate to the Console. Click Maps. From the Map Layers tab, upload the geojson file.
Answer: A
Explanation:
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]
NEW QUESTION # 35
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