Smarter GTM Execution Powered by Draup + Oracle Autonomous Data Warehouse
Self-driving, self-securing, and self-repairing. Draup integrates directly with Oracle to deliver workforce insights securely and at scale.
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Why Draup + Oracle ADW?
Draup delivers structured external sales signals directly into Oracle ADW, enabling teams to mash up internal CRM data with buyer intent and market context. With high performance and governance built in, teams can run forecasts, segmentation, and predictive analytics without worrying about infrastructure.
About Oracle Autonomous Data Warehouse
Oracle Autonomous Data Warehouse is a self-driving, self-securing, and self-repairing platform. It ensures high performance, automated management, and strong security for enterprise analytics.
How the Integration Works
- 1Stream Draup’s enriched account, buyer, and market intelligence flows directly into your data platform, aligning with existing GTM, revenue, and analytics pipelines.
- 2Enrich Datasets surface high-value signals, buyer intent, account readiness, competitive activity, hiring momentum, firmographics, and market shifts.
- 3Analyze Revenue, sales, and RevOps teams run real-time analytics, forecasting, and segmentation by blending Draup intelligence with internal CRM and pipeline data.
- 4Activate Insights power targeting, territory planning, forecasting, AI copilots, and GTM execution, helping teams prioritize the right accounts and close faster.
GTM Teams with Oracle ADW + Draup see
- Faster, more accurate revenue insights.
- Stronger governing of data assets and signals.
- Predictive analytics made easier with unified data.
- Scalable BI for sales, marketing, and finance.
What You Can Do
- Build predictive revenue models with buyer signals.
- Segment markets and accounts with real external context.
- Run executive dashboards with combined data.
- Forecast pipeline risk, churn, and opportunity growth.
Draup Works Wherever Your Teams Work
Draup connects with 30+ CRMs and sales platforms, so your sellers, marketers, and RevOps leaders get intelligence in the tools they already use.
By filling up this form, you agree to allow Draup to share this data with our affiliates, subsidiaries and third parties
Frequently Asked Questions
What makes Draup a good fit for Oracle ADW?
Draup delivers structured, analytics-ready data that complements Oracle’s high-performance warehouse.
How is Draup data typically used in Oracle environments?
Teams often blend Draup intelligence with internal data to support forecasting, segmentation, and executive reporting.
Can this support enterprise governance requirements?
Yes, Draup data aligns well with Oracle’s built-in governance and security frameworks.
Is this suitable for predictive analytics?
Absolutely, Draup datasets are commonly used for revenue, churn, and pipeline modeling.
How frequently are datasets refreshed?
Draup updates data regularly to reflect evolving buyer and market dynamics.
Impactful insights, delivered real-time
Access insights via API, custom data feeds, the Draup platform or using MCP
APIs & Integrations
Best for
Embedding live insights in workflows without storing data
- Native integrations with 33+ CRMs, like Salesforce, Hubspot, Microsoft Dynamics CRM, etc.
- Real-time access to critical data
- Enhanced security and data Integrity
- Efficient API performance with flexible limits
Custom Data Feed
Best for
Analytics at scale & joining Draup with internal data
- Highly customizable feeds for workflow needs
- Scheduled pushes to data lakes/warehouses (S3, ADLS, BigQuery, SFTP)
- Scalable use cases with the data
- Integrates with internal data assets for co-pilots/agents
Draup Platform
Best for
Fastest time-to-value,
no build required
- Ready-to-use UI with 200+ productized use cases & workflows
- Leverage visualizations & workflows to drive seller action with no overhead
- Enterprise controls: SSO, RBAC, governance
- Integrates UI & functionality into CRM apps
Model Context Protocol
Best for
Real-time Al workflows & LLM applications
- Native integration with Claude, OpenAl, and MCP-compatible Al tools
- Zero ETL, models query live data without pipelines or reindexing
- Governed access with token-based scopes, Pll masking, and audit trails
- Grounded, real-time data prevents LLMs from generating outdated or inaccurate insight
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