No More Spreadsheets: How We Built A Powerful Planning System That Actually Scales

I’m Anupam Gupta, Co-Founder at Celebal Technologies. Over the past eight years, we’ve helped global enterprises solve complex problems using cloud, data, and AI. But no matter the industry or scale, one thing shows up time and again: business planning still leans too heavily on disconnected tools and outdated spreadsheets.

That’s why Sigma immediately stood out to us.

No matter the industry or scale, one thing shows up time and again: business planning still leans too heavily on disconnected tools and outdated spreadsheets.

What began as a way to streamline our own revenue planning, quickly evolved. With Sigma layered on top of our Databricks Lakehouse, we started building data apps that not only eliminated spreadsheets, but brought together forecasting, collaboration, and planning into one unified experience. Today, those apps span cost modeling, profitability analysis, headcount forecasting—even energy planning. And the results have been transformational for us and for our customers.

Why the old tools had to go

There were two recurring challenges we set out to solve with Sigma.

First, the spreadsheet problem. Businesses still rely heavily on spreadsheets—they’re everywhere. But spreadsheets pose challenges around data silos, security, and the lack of modern collaboration or AI capabilities. Plus, there’s always a clunky back-and-forth between spreadsheets and cloud data warehouses, which adds significant tech debt.

Second, traditional planning tools. There are plenty of options on the market, but they often come with their own data platforms and AI engines, which aren’t as scalable or powerful as a central cloud platform like Databricks. That means more interfaces to build and more complexity for engineering teams.

We wanted to get rid of these challenges. So, we turned to Sigma.

Sigma opened the door for us to build data apps natively on the cloud data warehouse. It all started with our own revenue planning app. We pulled sales data from our CRM, invoicing from ERP, and project data from internal systems—all into our Databricks Lakehouse. Then we layered Sigma on top. Now, different sales pods can do their own revenue planning, securely access the right data, and collaborate directly in the app. It’s no longer a spreadsheet mess—it’s streamlined, secure, and scalable.

Sigma opened the door for us to build data apps natively on the cloud data warehouse.

And we didn’t stop there. We’re also building cost planning, profitability analysis, and headcount forecasting apps. What we built for ourselves, we’re now delivering to enterprise customers. 

How we use Sigma to build smarter apps

Our development journey begins by understanding user personas. In planning, that often includes both top-down and bottom-up workflows—CFOs and financial controllers, for example, each have distinct ways of working. We ask them to show us the layouts they’re using. From there, we model it in our Lakehouse and recreate the layout in Sigma.

Security comes next. We define data-level permissions to ensure the right people access the right data. Then we turn to collaboration. One of the first things we solve is the write-back problem—which Sigma handles out of the box. From there, we integrate workflows. That’s pretty much it. It’s that easy. 

A great example of a data app we built is in energy forecasting. We originally built renewable energy models in Databricks notebooks—but now, we’ve wrapped those models in a Sigma interface. That makes it instantly more usable and palatable to business users. Ultimately, our goal is to combine technical depth with business-friendly design.

Sigma’s data apps are like spreadsheets on steroids

User adoption has been incredibly strong—and I think a big reason is what I often say: Sigma is like a spreadsheet on steroids.

In the past, users had to make trade-offs. You could have volume, or performance, or complex logic—but rarely all three. With Sigma on top of Databricks, we get all of it. We’re running forecasts on terabytes of data, building advanced business logic in the Lakehouse, and delivering results instantly in a familiar interface.

Planning layouts and reports sit side by side. Users can adjust assumptions and see the impact in real time—without needing to write SQL or Python. It feels like a spreadsheet, but everything is happening live and at scale.

User adoption has been incredibly strong—and I think a big reason is what I often say: Sigma is like a spreadsheet on steroids.

We’ve also pushed heavy lifting—macros, calculations, data prep—into the warehouse, where it belongs. That’s made life easier for business users and reduced our reliance on IT or shadow teams.

From a governance perspective, everything is secure. We manage access through Databricks Unity Catalog, and those controls flow straight through to Sigma.

It’s fast, intuitive, and solves problems legacy tools never could.

Wisdom for builders: What I’d do again

If you’re building your first data app on Sigma, my advice is simple: start with the user. What do they do today? What would make that experience better? Replicate the spreadsheet feel if needed—but then go further. Add something new.

Tightly integrate with your cloud data warehouse. You want one platform, not a stack of disconnected tools. And always give users something extra. 

One of the coolest things we’ve built is real-time scenario planning. You can simulate thousands of SKUs or model capex investments and instantly see the cascading impact on financials, operations, or workforce metrics. That kind of insight used to take days. Now it happens in seconds.

Sigma gives business users the flexibility of a spreadsheet with the power and control of the cloud. It bridges the gap between planners and decision-makers. Whether it’s a CFO, supply chain lead, or HR manager, they can see changes and impacts instantly—all in one interface.

That’s what it means to be truly data-driven.

Go further: Explore Sigma’s Planning Data Apps

See how Sigma powers real-time planning, forecasting, and analysis—without the spreadsheet chaos. Dive into the data app demos and experience what’s possible.

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