How to Deliver Business Value from Data

Introduction: The Data Value Challenge

In today’s digital landscape, organizations are inundated with data and technology choices. Yet, many struggle to translate technical progress into tangible business value. Recognized data influencers like Chris Tab emphasize that the real challenge is not the tools themselves, but how companies bridge the gap between business objectives and technology solutions. This guide distills practical lessons, real-world examples, and proven frameworks to help you elevate your data strategy, accelerate maturity, and achieve sustainable competitive advantage.

1. Data Maturity: Assessing Where You Are

Every organization is at a unique stage in its data journey. Data maturity assessments are essential for mapping your current capabilities and identifying gaps. Key dimensions include:

• Strategy & Leadership: Is there a clear vision for data? How aligned are business and IT stakeholders?
• Technology Stack: What platforms and tools are in place? Are they integrated or siloed?
• Data Governance: Are data quality, security, and compliance practices established?
• People & Skills: Do teams have both business acumen and technical expertise?

For example, a startup may rely on spreadsheets, while a global enterprise might have advanced data platforms but struggle with agility. Tailoring your approach to your maturity level is critical.

2. Bridging Business and Technology

According to Chris Tab, the most successful data initiatives start by translating business goals into actionable technology roadmaps. This requires “thin slicing” through all the technical layers to focus on delivering business value at each step.

1. Start with Business Outcomes: Identify the key pain points or opportunities that matter to business stakeholders.
2. Map Data Capabilities to Outcomes: Determine which data assets, processes, and technologies can address those needs.
3. Iterate and Prioritize: Deliver value in cycles—start small, prove impact, and scale iteratively.

Example: A retail chain wanted to optimize its supply chain. Instead of investing in a massive data lake, it began with a focused analytics project that reduced inventory costs by 10%. The initial success built momentum for larger, more complex projects.

3. The Role of Community and Collaboration

Technology alone is not enough. Building a data-driven culture means fostering collaboration across business and technical teams. Influencers suggest:

• Embed Data Scientists and Engineers in Business Units: This enhances understanding of real-world challenges and accelerates value delivery.
• Promote Open Communication: Regular forums, brown-bag sessions, and transparent roadmaps help align priorities and share lessons.
• Create Champions: Early adopters who benefit from data initiatives can advocate for broader adoption.

“If you embed a data scientist in the business and get them to work there, that helps them understand what they’re doing. You cannot work in isolation and make a data strategy with just technology people.”

4. Lessons from the Modern Data Stack Evolution

The last decade saw explosive growth in data tools and platforms, leading to what’s often called the “modern data stack.” However, complexity can undermine value if not managed carefully.

• Era 1: Monolithic Platforms—One-size-fits-all tools (e.g., early BI suites like Cognos), accessible only to large enterprises.
• Era 2: Cloud & Best-of-Breed—A proliferation of specialized cloud tools, often leading to fragmented architectures.
• Era 3: Data Operating Systems—Emerging platforms that orchestrate and unify diverse tools, making data accessible to business users.

Chris Tab and peers advocate for simplification: “It doesn’t need to be made of 15,000 pieces. Simplify back to what’s right for your company at the right time.”

5. Data Modeling, Governance, and Observability

Data Modeling is often neglected in the rush to adopt new tools. Without clear models, data becomes hard to use, trust, and scale. Best practices include:

• Start with business concepts—model what matters most.
• Iterate models as understanding grows.
• Integrate modeling into agile delivery cycles.

Data Governance should be baked in from the start—not as a side project. This includes:

• Clear ownership and stewardship of data assets.
• Role-based access controls and security policies.
• Automated cataloging, lineage, and audit trails.

Observability—knowing what data you have, how it’s being used, and how much it costs—is critical for scaling safely. Modern platforms combine audit logging, monitoring, and cost tracking.

6. The Business Value Formula: From MVP to Scale

Delivering value from data requires a disciplined approach:

1. Build a Solid Foundation: Implement core practices—FinOps (financial operations), DataOps (collaborative development), and security from day one.
2. Deliver a Business MVP: Solve a real business pain point quickly. Use this as a reference for others.
3. Scale Through Community: As more teams see value, adoption accelerates organically. Champions help drive change.

Tip: The first team to benefit from foundational investments (like orchestration or observability) may bear more cost, but later teams benefit from shared infrastructure. Fair cost allocation and transparency help manage this.

7. Influencer Strategies: Building Credibility and Driving Change

For business leaders, building influence is about sharing knowledge, learning from others, and driving industry conversations. Tactics include:

• Consistent posting and engagement on platforms like LinkedIn.
• Reposting and crediting others to build relationships and trust.
• Being authentic—sharing both successes and lessons learned.

Chris Tab’s journey illustrates how visibility and credibility can open doors, foster collaboration, and shape industry best practices.

8. Modern Data Platforms: Snowflake as a Case Study

Modern platforms like Snowflake exemplify the convergence of usability, scalability, and governance. Key advantages include:

• Separation of Compute and Storage: Pay only for what you use, scale elastically.
• Zero-Copy Cloning & Data Sharing: Enable rapid experimentation and secure collaboration.
• Integrated Security, Observability, and Cost Controls: Reduce operational burden and risk.

Early adopters have gained significant speed, flexibility, and cost advantages, especially when foundational practices are in place.

9. From Technology to Community—The Human Factor

Technology is only as effective as the teams and culture behind it. Success depends on:

• Cross-functional Teams: Blend business, data, and technology skills.
• Transparent Communication: Share plans, progress, and pain points openly.
• Iterative Improvement: Celebrate small wins, learn from setbacks, and evolve together.

10. Next Steps: Bringing It All Together

To accelerate business value from data:

• Assess Your Maturity: Use frameworks to identify strengths and gaps—across strategy, technology, governance, and people.
• Align Business and Technology: Prioritize initiatives that deliver measurable business outcomes.
• Invest in Community: Build cross-functional teams and champion continuous learning.
• Simplify and Unify: Choose platforms and architectures that reduce complexity and support growth.
• Measure and Communicate Value: Track key metrics that align with business strategy. Regularly share progress and lessons with stakeholders.

Summary Table: Key Principles for Data-Driven Success

PrincipleDescriptionBusiness AlignmentStart with business outcomes, not technology for its own sake.Data MaturityAssess where you are and evolve iteratively.Governance & SecurityBake in controls from the start—make them easy, not burdensome.CommunityFoster collaboration and knowledge-sharing.SimplificationReduce unnecessary complexity; focus on what matters most.Continuous Value DeliveryBuild, deliver, measure, iterate.

Conclusion: Your Data Journey Starts Here

Whether you’re a startup, a growing enterprise, or a global leader, sustainable business value from data is within reach. By learning from experienced influencers, focusing on business outcomes, and building strong communities, you can turn data into a true strategic asset. Ready to accelerate your journey? Keboola and its partners are here to help.