How Fortune 500 Companies Tackle Their Toughest Data Challenges

There’s an old parable about five blind people examining an elephant. Each touches a different part—the trunk, the tail, the legs—and believes they are describing a completely different animal. But when you step back, it’s clearly an elephant.

Why am I telling this story in an article about data for Fortune 500 companies? Because this is exactly what happens with data in large organizations. Every decision from entering a new market, to optimizing supply chains, and predicting customer behavior, relies on vast amounts of data. But as organizations grow, they build layers of complex tech stacks, siloed data, and access controls that make it difficult to get clear, real-time insights. Business users struggle to access the data they need, IT teams are buried under requests, and leaders can’t make informed decisions because no one is seeing the full picture.

I’ve been working with a lot of Fortune 500 companies at Sigma, like Blackstone and DoorDash, and I keep coming across the same challenges. Here’s why.‍

Yes, Fortune 500 companies are still using spreadsheets

Even though there’s a spectrum of data and tech maturity in these enterprises, they’re often slow to adopt the best technologies because of all the approval processes, security checks, and compliance reviews that go with having so much data.

They eventually transition to the modern data stack with enterprise cloud data warehouses like Snowflake, Databricks, or BigQuery. They’ll have data integration tools like dbt, Fivetran, or Airbyte to bring data from other systems, then layer business intelligence platforms like Sigma on top. Even with these tools, though, most people still rely on homegrown spreadsheet solutions. Users default to what they know because they lack access to better tools.

This is a big challenge in finance, where the institution might ask you to integrate with a tool that was built 20 years ago. So, departments build workarounds in Excel to circumvent these systems. This leads to random silos and one-off solutions that serve a small group of users but don’t scale across the organization. Add to that the fact that Excel lacks the governance capabilities enterprises actually need, and that spreadsheets are never really live. That makes collaboration difficult, especially when working with billions of rows, and they’re always prone to security breaches. 

What these companies really want is a system where they can mix and match compute engines and provide a seamless interface—or a “storefront”—to business users. The challenge? Not many products work across all these compute engines.

Data security vs. self-service: A constant tug-of-war

Another major challenge is RBAC, or role-based access controls. With teams of over 100,000 people, ensuring the right users and departments have access to the right data is critical. At the same time, data breaches are a serious risk, so everything exposed to end users must be backed by stringent security standards.

This is especially critical in healthcare. You can’t have patient data being accidentally shared between two individuals, for obvious reasons. So, you need to implement access control at the provider level, and embed security measures in how the data is consumed. Manufacturing companies face similar challenges—they rely on real-time data to optimize supply chains and monitor production efficiency, but must ensure only authorized personnel can access sensitive operational data.

This tug-of-war between security and accessibility is what companies are trying to fix.

This tug-of-war between security and accessibility is what companies are trying to fix. They need to provide data to end users in a way they can actually consume it. So self-service—or rather, the lack of it—has become a problem. Each department conducts its own security and compliance reviews, repeating processes across teams instead of operating under a unified framework. As silos increase, maintaining these disconnected systems becomes incredibly expensive and inefficient.

Rapid fire: How Sigma helps Fortune 500 companies

For business and data leaders, their number one job is to provide a vision, but they can’t do that if every department is working from disconnected data. Without alignment, different teams interpret the same message in completely different ways (just like the elephant story). Leaders also need to allocate resources effectively—but how can they if they don’t have a clear view of what’s happening across the organization? With hundreds of tools, technologies, and data sources scattered across different teams, making informed decisions becomes nearly impossible.

Beyond vision and resource allocation, data leaders must also set goals and strategy, foster collaboration across departments, ensure technology investments align with business objectives, and maintain strict compliance with data governance and security regulations. That's why they need a system that balances accessibility with governance, enabling real-time decision-making at scale. The key is interoperability—a unified approach that aligns data and security standards across the organization, eliminating inconsistencies and unnecessary overhead while ensuring secure, seamless information sharing. But scaling with vast amounts of data, different regulations, and complex organizational structures can be tricky.

This is where Sigma comes in. Because Sigma sits directly on top of enterprise cloud data warehouses, data never leaves the cloud, which means no data extracts and no silos. Multiple security layers ensure information is protected before reaching end users, allowing teams to collaborate without compromising governance. With SOC 2 Type II, GDPR, and HIPAA compliance, along with audit logging and customer-managed encryption, companies can confidently safeguard their data and ensure top-tier security. By centralizing governance within Sigma, data leaders ensure compliance without creating bottlenecks, while enabling cross-functional teams to align around trusted, real-time data.

Data leaders need a system that balances accessibility with governance, enabling real-time decision-making at scale. The key is interoperability.

But access to data means nothing if users don’t know how to work with it. Sigma’s self-service analytics allows business users to explore and analyze live data independently, reducing reliance on IT teams while keeping data secure. With embedded analytics, companies can curate the user experience and deploy it across regions. Nearly two billion people use spreadsheets—so Sigma makes data analysis as familiar as Excel, just without the limitations. Users can drill down, segment, and interact with data in ways that make insights immediately actionable.

Centralized collaboration and real-time decision-making is also made possible in Sigma. With writeback capabilities, teams can push insights directly into operational workflows—updating forecasts, adjusting models, and feeding real-time insights back into business processes. This ensures that data isn't just consumed but actively used to drive business outcomes.

Seeing the Whole Elephant: Why Complete Data Matters

When data is trapped in silos, even the sharpest teams are left making decisions in the dark. They see one piece of the puzzle, but not the full picture. 

The Fortune 500 companies that get ahead are the ones that tear down silos, unify their teams around live, trusted data, and make decisions with confidence. Sigma makes this possible by eliminating extracts, enabling governed self-service, and delivering real-time insights at scale—so every department, every leader, every decision-maker is finally seeing the whole elephant.

Because in the end, that’s the difference between companies that move forward—and companies that get left behind.