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Jahnavi-Oracle · 2026-03-02T07:45:16+00:00

* Which dataset did you use? Sales Pipeline * How did you analyze or prepare the data? I analyzed the data by reading the structure and sample rows via Dataset insights and Calculated metrics like coverage ratio (Open Pipeline ÷ Target/Remaining Target), weighted pipeline (Value × Probability), progressed deals (% with…

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Pipeline Pulse

Jahnavi-Oracle

Which dataset did you use?
Sales Pipeline
How did you analyze or prepare the data?
I analyzed the data by reading the structure and sample rows via Dataset insights and Calculated metrics like coverage ratio (Open Pipeline ÷ Target/Remaining Target), weighted pipeline (Value × Probability), progressed deals (% with recent stage start date), and gap analysis to understand the patterns and warnings in it.
Who is the intended audience for your visualization?
The intended audience is sales leadership (VP Sales, Sales Directors, Regional Managers) who need to answer these questions in under 2 minutes:
Are we on track to hit revenue?
Where is money stuck in the pipeline?
What actions should I take now?
What is your visualization about, and what question or problem does it address?
pipeline dashboard helps in tracking health, bottlenecks, and actions across regions, reps, and stages.
Business impact: Identifies $X pipeline at immediate risk and surfaces specific interventions (rep reallocation, executive escalations, pricing refresh) to accelerate revenue.
Did you use any Oracle Analytics AI features when building your visualization (ex. AI Assistant)? If so, please describe how they were used.
Yes I used AI Assistant on top of the data after indexing the dataset to query it with natural language.

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Comments

Bhaskar Konar

This is a fantastic dashboard. It connects pipeline health, bottlenecks, and rep-level actions seamlessly - making the insights both clear and actionable.

Excellent work! 👏

Jahnavi-Oracle

Thank you @Bhaskar Konar

Tatenda Mukaro

This is awesome