Data Visualization on Oracle Analytics Cloud — Lesson 3: Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration

Learning Objectives

• Assess the dependencies, controls, and expected business outcome for Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration.
• Demonstrate the workflow and leave reproducible evidence in augmented analysis and shared insight narrative.
• Recommend a preventive improvement after resolving automated insight highlighting correlation as if it were causation.

Detailed Topics

• Augmented analytics
• Explain
• Forecasting
• Machine learning
• Mobile use
• And collaboration
• Decision ownership, prerequisites, and acceptance evidence for Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration
• Relevant access, data, integration, performance, recovery, and support considerations

Instructor Demonstration

The instructor builds a representative scenario for Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration, narrating each decision and showing how it contributes to clear, performant, and secure Oracle Analytics Cloud visualizations that turn prepared data into defensible business insight. The demonstration records augmented analysis and shared insight narrative so learners can compare configuration intent with observable behaviour.

Hands-On Exercise

Complete a guided task covering Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration. After establishing a working baseline, reproduce “automated insight highlighting correlation as if it were causation,” isolate the responsible setting or data condition, apply a reversible fix, and update augmented analysis and shared insight narrative with before-and-after proof.

1. Map the current process and mark where the expected result can first be observed.
2. Run the scenario while preserving timestamps, job identifiers, and relevant output.
3. Apply a reversible correction only after evidence supports the cause.
4. Retest the original case plus an unaffected case and update the handover record.

Scenario Analysis

• Clarify the business trigger, affected roles, required records, and acceptable result for Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration.
• Compare at least two implementation or correction choices and identify which evidence would distinguish them.
• Decide how augmented analysis and shared insight narrative should be reviewed, approved, retained, and handed to the next owner.

Troubleshooting Guidance

For a failure in Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration, separate access, setup, data, integration, and timing causes. Compare the observed sequence with augmented analysis and shared insight narrative; if “automated insight highlighting correlation as if it were causation” is confirmed, make the smallest reversible correction and document why broader changes were rejected.

Validation Checklist

• Prerequisites and role permissions for Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration have been confirmed before execution.
• The result agrees with the expected values documented in augmented analysis and shared insight narrative.
• Exceptions are explained with evidence rather than hidden by manual correction.
• The final record names the approver, monitoring point, and next improvement action.

Lesson Outcome

Learners can apply Augmented analytics, explain, forecasting, machine learning, mobile use, and collaboration, explain the decisions made, and defend the result with augmented analysis and shared insight narrative.