Oracle 1z0-1041-23 Dumps Questions Answers

Sharing the story on Day by Day with their decision makers is the most likely reason why an analyst has created a story on the Narrate tab of the project 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. The Narrate tab is a workspace where you can create and edit your story using various tools and options. You can add multiple canvases to your story and navigate between them using the navigation bar. You can also add notifications, filters, notes, and narration to your story to enhance it and make it more interactive. Day by Day is a mobile application that allows you to access and interact with your Oracle Analytics Cloud content using voice or text commands. You can use Day by Day to view and explore your stories on your mobile device and share them with other users via email or chat. You can also receive personalized insights and recommendations from Day by Day based on your location, calendar, and preferences. Sharing the story on Day by Day with their decision makers is a convenient and effective way for an analyst to deliver their analysis and influence their decisions. The other options, such as sharing the story by exporting to MS Excel, sharing the story with consumers on the Home Page, and sharing the story by exporting to pdf, are not the most likely reasons why an analyst has created a story on the Narrate tab of the project in Oracle Analytics Cloud. These options are either not supported or not optimal for sharing a story in Oracle Analytics Cloud. References: Oracle Help Center, Oracle Help Center, Oracle Help Center

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. References: [Oracle Day By Day User’s Guide], [Oracle Day By Day User’s Guide], [Oracle Day By Day User’s Guide]

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. References: Oracle Analytics Cloud - Data Visualization User’s Guide, [Oracle Analytics Cloud - Data Visualization User’s Guide]