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Oracle 1Z0-1041-22 Exam
- Topic 1: Describe 'sequence' in the context of OAC data preparation/ Describe and Create Oracle Analytic Cloud Solutions
- Topic 2: Create a flexible layout of multiple visualizations to present data as a story/ Using Oracle Applications Connector and EPM Connector
- Topic 3: Create and train a machine learning model, analyze its effectiveness and use it in a project/ Explain Migration Options to OAC and OAS
- Topic 4: Register and apply Oracle Database Machine Learning Models/ Oracle Analytics Cloud Provisioning and Lifecycle
- Topic 5: Explain OAC 'best visualization' for a data set/ Describe using Function Shipping with ADW
- Topic 6: Explain Advanced Calculations inside Expression Editor/ Describe the Advanced Analytics capabilities in OAC
- Topic 7: Navigate from a Data Visualization into a Publisher Report using Data Actions/ Describe self service data preparation
- Topic 8: Administer Analysis, Dashboards and Reports/ Use OAC to present your data as a story
- Topic 9: se Data Flows to curate a Data Set/ Provision Users and Application Roles
- Topic 10: Oracle Analytics Cloud Answers, Dashboards and BI Publisher/ Bursting Pixel Perfect Reports and using Data Sets
- Topic 11: Create Advanced Analytics Functions/ Describe brushing and its benefits
- Topic 12: Explain Transactional System, Analytical Systems, Data Warehousing, Dimension, Facts and Hierarchies/ Import a custom visualization plugin
Free Oracle 1Z0-1041-22 Exam Actual Questions
The questions for 1Z0-1041-22 were last updated On Feb. 05, 2023
Describe what is the aim or the main functionality for the BI Ask?
You have created a visualization of revenue data over time. It displays some seasonality (e.g. high revenue around typical holiday periods) but there is no obvious pattern to the data overall. In which two ways can you start to get insight from this data?
Which three options are correct about application workbooks?
How should you determine the accuracy of a machine learning model created in Oracle Analytics Cloud?
Your company is using an Essbase cube, which is enabled for Scenario Management. Planners model data in individual scenarios and submit them for approval.
While modeling data in the "SB1" sandbox, you changed a few values based on some assumption. Later, you realized that your assumptions were incorrect. You want to start again with the original values, the same as base.
Which step should you perform?
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