Organizations often assume pushing workforce data directly into a general-purpose warehouse like Snowflake before connecting to an analytics platform is an optimal strategy. While this could be appealing for enterprise consistency, this warehouse-first approach overlooks critical workforce-specific requirements.
Starting with One Model's comprehensive data extraction and modeling capabilities before moving to an enterprise warehouse ensures greater success, efficiency, and analytical accuracy.
Workforce data is dynamic, constantly evolving, and deeply intertwined with organizational operations. Generic data warehouse systems are effective for storage but lack specialized capabilities for extracting and modeling HR-specific complexities such as transaction-based employee data, hierarchical structures, and frequent retroactive updates.
Organizations considering a warehouse-first strategy should recognize several limitations:
1. Delayed Implementation and Compromised Data Integrity
HR data extraction requires specialized and time-sensitive transaction log-based incremental updates, not repetitive snapshots, to avoid redundancy, inflated costs, and reduced query performance. Without dedicated subject matter expertise or experience extracting HR data into a warehouse, this complexity can delay HR time-to-value significantly and introduces unintended engineering decisions that compromise data quality.
2. Complex Workforce Data Modeling
Generic data warehouse solutions lack pre-built schemas necessary to handle nuances of sensitive workforce data like performance, terminations, rehires, and salary adjustments accurately. Starting from scratch on these builds can lead to downstream analytical inaccuracies and inefficiencies when making use of data that isn't modeled properly.
3. Manual Maintenance and Increased Security Risk
Warehouse-first strategies require continuous manual oversight and updates of both pipelines and stored data, increasing the risk of errors, compliance issues, and security vulnerabilities. Managing and maintaining these challenges manually in-house can lead to time delays which in turn diminishes organizational trust in analytics.
4. Unprepared for Advanced Analytics and AI
Data warehouses typically optimize data storage and architecture for basic querying and lite reporting rather than deeper analytical processes like predictive modeling or preparing data for use in AI initiatives. Without specialized modeling, organizations face severe limitations in extracting strategic value from their workforce data.
One Model is a comprehensive, full-stack solution designed explicitly for People Analytics, emphasizing openness, flexibility, and transparency. One Model provides expertise and support while also allowing your team full visibility and control over data transformations through accessible SQL code, facilitating seamless integration and customization.
One Model's managed connectors efficiently handle complex data extraction at scale from industry leading HRIS systems like Workday, Oracle, and SAP, as well as hundreds of systems across the HR tech and Work Tech stack. Unlike brute-force methods taking monthly snapshots, One Model intelligently captures meaningful data changes nightly, significantly enhancing scalability, accuracy, and speed.
One Model utilizes self-healing data models powered by advanced algorithms and AI-driven error correction. One Model tools continuously monitor and automatically correct data anomalies, ensuring ongoing accuracy, especially critical for managing common HR challenges like retroactive updates.
Sensitive employee information demands stringent security. One Model strictly adheres to industry-leading compliance standards such as SOC 2 and ISO 27001. The platform incorporates robust role-based access controls, ensuring secure, compliant data management, and protection.
One Model supports flexible data flows, whether directly from source systems like Oracle or Workday into One Model, or subsequently pushing refined data to warehouses like Snowflake. One Model can also ingest directly from warehouses like Snowflake for ad hoc data loads or full system loads of historical data. Organizations retain complete control, choosing precisely how and when data moves, ensuring no compromise to data integrity, governance, or analytical capability.
Even with the challenges outlined above, there is clear strategic value in centralizing workforce data within enterprise warehouses like Snowflake, Redshift, or BigQuery. The issue isn't the warehouse itself but rather how the data arrives there. A warehouse-first approach mistakenly treats workforce data like just another standard dataset, missing the complexity and specialized structure needed for effective analytics.
To bridge this gap, One Model created the Data Destinations toolkit. Rather than forcing a choice between HR-specific modeling and an enterprise-wide warehouse strategy, Data Destinations ensures that once the data is modeled in our platform, organizations can easily push carefully structured, analytics-ready, and secure workforce data directly from One Model into their warehouse of choice. This maintains the integrity, accuracy, and privacy of the workforce data, making your warehouse strategy not only scalable but strategically valuable.
Starting your People Analytics journey directly with One Model addresses the foundational concerns raised at the outset: managing complexity, ensuring data accuracy, and maintaining compliance and security. Unlike the generic warehouse-first approach, One Model prioritizes capturing and modeling workforce data in its raw, uncompromised form, specifically tailored for the intricate demands of HR analytics. By opting for direct integration, your organization gains not only superior analytical capabilities and efficiency but also robust security and compliance that are built directly into the data pipeline.
Rather than forcing HR data into a one-size-fits-all solution, One Model’s specialized approach empowers your analytics team to produce precise, actionable insights. Ultimately, investing first in One Model ensures your HR analytics infrastructure is both strategically aligned with business objectives and resilient enough to adapt and evolve with organizational needs, transforming your workforce data into a reliable driver of informed, strategic decision-making.