Get Oracle 1Z0-1041-23 Exam Dumps

Answer : A, B, E

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]

Answer : A, C, E

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]

Answer : B

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]

Answer : A, D

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.

Answer : C, D

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]