Services
Data Team as a Service
An embedded team of data professionals who learn your business — not just your tech stack — and deliver the strategic guidance and hands-on execution mid-market organizations need to move faster with data, automation, and AI.
Key Takeaways
Data Strategy as a Service (DTaaS) provides ongoing, fractional data leadership and execution without hiring a full-time data team. It's the most cost-effective way for mid-market companies to maintain a living data strategy, continuous engineering support, and analytics capacity.
- Fractional data team at 30-50% the cost of full-time hires
- Continuous strategy refinement — not a one-time engagement
- Scales up or down with your business needs month to month
- Combines strategy, engineering, and analytics in one retainer
- Ideal for companies with $50M-$500M revenue that aren't ready for a full data team
How it works: roadmap, backlog, execution.
DTaaS isn't staff augmentation and it isn't project-based consulting. It's a dedicated team that operates as an extension of your organization — one that understands your business goals, not just your data stack.
Here's the operating model:
- ✓We build a strategic roadmap together. Before any implementation work begins, we align on where your business is headed and where data, automation, and AI can accelerate that. The roadmap becomes the foundation for everything the team does.
- ✓We maintain a prioritized backlog. Day-to-day, the team works through a backlog of projects — data engineering, automation workflows, predictive models, analytics — prioritized by business impact. You always know what's being done and why.
- ✓Specialized skills flex up and down. If the backlog shifts toward machine learning for a quarter, we flex in data science resources. If it's a heavy integration period, data engineering scales up. The strategic core stays constant. The implementation layer adapts to the work.
- ✓Cadence keeps it accountable. Weekly standups, monthly reviews, quarterly roadmap adjustments. Clear deliverables, transparent progress, and a team that operates on your schedule.
Business first, technology second.
Most outsourced data teams are purely technical — they build what you ask them to build. That's useful, but it's not the full picture.
Because our team is embedded in your organization over months and years, we learn more than your systems. We learn your business — how you make money, where you lose efficiency, what keeps leadership up at night. That business knowledge changes the nature of what we recommend.
- ✓We save you from rework by making architectural decisions today that hold up when the next initiative comes along.
- ✓We solve multiple problems at once because we know what's coming — a pipeline built for one need can extend to feed an automation workflow, a predictive model, and a reporting layer.
- ✓We protect you from vendor lock-in with vendor-neutral guidance and architectures that keep your options open.
- ✓We anticipate what's next instead of waiting for you to identify the next project. A business-aware team comes to you with recommendations, not just status updates.
A team that flexes with your needs.
The core of every engagement is continuity: a project lead and strategist who knows your business, your roadmap, and your systems. Around that core, specialized skills scale based on what the backlog demands.
- ✓Data Engineering — Pipelines, integrations, warehousing, and infrastructure. The foundation everything else depends on.
- ✓Data Science & ML — Predictive models, forecasting systems, and machine learning applications built on your data.
- ✓Automation — Workflow automation that eliminates manual processes across departments.
- ✓BI & Analytics — Dashboards, reports, and self-service analytics for business teams who need answers without waiting on IT.
- ✓Data Governance — Quality controls, documentation, and access management. The piece most organizations neglect — and the one that causes the most pain when it's missing.
Not every engagement needs every discipline at once. The team composition matches the work and evolves as your data maturity grows.
How DTaaS compares.
Data Team as a Service gets confused with staff augmentation and project consulting. They solve different problems.
Staff Augmentation
Individual contractors backfill specific roles. You manage them directly. They rotate out when the contract ends. It works for filling a gap, but knowledge leaves when the contractor does — and there's no strategic layer guiding the work.
Project Consulting
A firm delivers a fixed-scope initiative: deploy a data platform, build an ML model, implement an automation workflow. It has a start date and an end date. It works for one-time deliverables, but it doesn't build ongoing capability or strategic continuity.
Data Team as a Service
A dedicated team operates as part of your organization on an ongoing basis. They build a strategic roadmap, manage a backlog across multiple disciplines, and flex specialized resources as priorities shift — all while developing the deep business knowledge that makes every subsequent project more valuable.
DTaaS is designed for organizations that need sustained data capability and business-aware strategic guidance — not a one-time project or a single contractor.
Disciplines we bring to the table.
Strategy & Project Lead
Sets priorities, manages the roadmap, and translates business objectives into data initiatives. Your consistent strategic partner.
Data Engineering
Builds and maintains pipelines, warehouses, and integrations — the infrastructure layer that everything else depends on.
Data Science & AI
Machine learning models, predictive analytics, forecasting systems, and AI applications built on your data foundation.
Automation
Workflow automation, process orchestration, and integration logic that eliminates manual work across your organization.
BI & Analytics
Dashboards, reporting, and self-service analytics using Power BI, Tableau, Looker, or whatever your stack requires.
Data Governance
Data quality, documentation, access controls, and compliance — the foundation of trustworthy analytics.
Data Integration
Connecting disparate systems, unifying data sources, and ensuring clean, reliable data flows between platforms.
Solution Architecture
Technology selection, system design, and vendor-neutral guidance that keeps your infrastructure flexible and future-proof.
Common questions about DTaaS.
How long do DTaaS engagements typically last?
Most engagements run 6-12 months minimum, with many extending well beyond that. The model is designed for sustained partnership — the longer the team is embedded, the more strategic value they deliver because they understand your business more deeply over time.
How is DTaaS priced?
DTaaS is typically structured as a predictable monthly investment based on the scope of work and team composition. This gives you budget certainty while allowing the mix of specialized skills to flex with your priorities.
Can you work with our existing tools and platforms?
Yes. We're vendor-neutral and work across the modern data stack — cloud platforms (AWS, Azure, GCP), BI tools (Power BI, Tableau, Looker), data warehouses (Snowflake, Databricks, Redshift), and automation platforms. We also advise on tool selection when you're evaluating options.
How do you handle strategic planning vs. day-to-day execution?
Both happen in parallel. The team maintains a strategic roadmap (revisited quarterly) and a prioritized backlog of projects (managed weekly). Day-to-day execution is always guided by the strategic plan, so every pipeline, model, and automation serves a larger business objective.
What happens when the engagement ends?
Everything we build is yours — the infrastructure, the dashboards, the models, the documentation, and the strategic playbooks. A good DTaaS partner builds your organization's capability, not dependency. We also offer knowledge transfer sessions to ensure your internal team can maintain and extend what we've built.
How is this different from hiring a full-time data team?
Hiring a full data team internally requires recruiting 4-5 specialized roles (data engineer, analyst, scientist, strategist, governance), which can take 6-12 months and cost $500K+ annually in salary alone. DTaaS gives you the same range of expertise immediately, with the flexibility to scale disciplines up and down without the fixed overhead of full-time headcount.
Want a deeper look at the DTaaS model, when it makes sense, and how to evaluate providers? Read our guide: What Is Data Team as a Service?
See This Service in Action
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Consolidating 15+ Systems into a Modern BI Platform for a $7B Real Estate Firm
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