Run Advanced Talent Analytics at Scale in Microsoft Azure Blob Storage

Microsoft Azure Blob Storage meets Draup’s workforce intelligence. Stream talent, skills, and market datasets into Microsoft Azure Blob Storage to power HR analytics, workforce planning, and AI-driven workforce models, with no integration friction.

Why Draup + Azure Blob Storage

Draup delivers structured workforce datasets into Azure Blob Storage, giving HR teams a secure, scalable foundation for talent analytics and AI-driven workforce planning. Blob acts as a flexible staging layer for enriching HR systems, dashboards, and forecasting models with global labor intelligence.

About Microsoft Azure Blob Storage

Azure Blob Storage is a cost-effective, massively scalable storage for unstructured data. It integrates deeply with the Azure ecosystem, supporting enterprise analytics and ML workloads.

How the Integration Works

  • 1Stream Draup delivers structured talent intelligence directly into your data platform with secure, scalable access.
  • 2Contextualize Datasets surface critical workforce signals, skills gaps, mobility flows, market competitiveness, and emerging role trends.
  • 3Model Teams build forecasts, scenarios, and AI-driven workforce models using combined internal and external data.
  • 4Operationalize Insights flow into planning, reporting, and decision-making systems to support faster, smarter talent strategies.

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Talent Teams with Azure Blob Storage + Draup see

  • Easier access to external workforce insight across analytics tools
  • Stronger alignment of HR planning with real labor supply
  • Scalable storage for talent datasets and ML inputs
  • Consistent, governed data feeding both operational and strategic use cases

What You Can Do

  • Feed Draup datasets into HR dashboards and analytics platforms
  • Compare talent availability across markets and roles
  • Support forecasting models for skills and location strategy
  • Benchmark internal workforce data against global trends

Draup Works Wherever Your Teams Work 

Draup connects with 30+ ATS, HRIS, and HCM platforms, so your recruiters, workforce planners, and HR leaders get market intelligence in the tools they already rely on.

Frequently Asked Questions

What type of Draup talent data is delivered to Blob?

Skills data, labor supply-demand, mobility insights, and competitive benchmarks.

How is the data typically used?

For analytics, dashboards, ML models, and HR system enrichment.

Is this secure for workforce data?

Azure Blob’s encryption and access controls provide strong governance.

Who benefits most?

Workforce planning, HR analytics, TA leadership, and strategy teams.

Does this support AI-driven HR use cases?

Yes, Blob is frequently used as a staging layer for HR AI models.

Impactful insights, delivered real-time

Access insights via API, custom data feeds, the Draup platform or using MCP

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APIs & Integrations

Best for

Embedding live insights in workflows without storing data

  • Native integrations with 33+ HCM, HRIS, ATS and more, like Workday, SAP Successfactors, etc.
  • Real-time access to critical data
  • Enhanced security and data Integrity
  • Efficient API performance with flexible limits
Learn more
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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
Learn more
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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
Book a demo

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
Learn more

Data Trust & Methodology at Draup

Draup uses a structured methodology to reduce inaccuracies and prevent misleading information, with a focus on transparency and responsible data practices.

1

Data Transparency and Coverage

Draup sources data from diverse, vetted global inputs including public datasets, labor information, professional ecosystems, and industry research. Coverage varies by region and role, and we supplement limited areas with alternative sources and analyst-led modeling.

2

Profiles Behind the Numbers

All aggregate insights related to buyers, roles, skills, and locations are grounded in structured, anonymized human and organizational profiles rather than pure extrapolation. This ensures context, reliability, and protection of personal identities.

3

Data Hygiene and Integrity

We maintain a clean, accurate data environment by removing duplicates, outdated entities, and invalid records. Automated checks powered by ML models and analyst reviews work together to ensure clarity and accuracy for every entity, such as buyer, role, skill, technology, or company. Learn more

4

AI Governance and Bias Mitigation

Our governance framework combines automated evaluations with Human-in-the-Loop reviews. We use statistical checks, audits, and cross-source comparisons to reduce demographic and structural bias before insights reach the platform.

5

Compensation Guardrails

Compensation insights use blended, directional inputs such as aggregated ranges, benchmarks, modeled distributions, and market signals. We distinguish clearly between modeled and reported data and apply guardrails to prevent over-interpretation.

6

Hourly and Frontline Workforce Coverage

For hourly, frontline, and blue-collar roles where digital visibility is limited, we incorporate government datasets, localized labor information, and specialized partners to build a more complete and balanced view of workforce supply and demand.

SOC 2
GDPR
ISO
EAIGG

Ethical AI, Backed by Global Standards

Draup, an AI-first company, upholds global standards like SOC 2, GDPR, and ISO 27001. As an EAIGG member, we audit for bias and build trustworthy AI.

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Drive better decisions with unmatched, real-time data & agentic intelligence

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