Ad-Hoc-Big-Data-Analysis

As a former CRO, I can say firsthand—nothing beats a spreadsheet for quick ad-hoc data analysis. In my past role, I had access to a full tech stack: forecasting platforms, Salesforce reports, ERP systems, FP&A tools, product dashboards, BI software, and a highly capable revenue ops team. Yet, despite all of that, I still found myself relying on spreadsheets for analyzing performance, forecasting results, and future planning. The ease of use, combined with their flexibility, makes spreadsheets perfect for on-the-fly exploration—and, let’s be honest, everyone speaks spreadsheet.

However, spreadsheets have their limits. They struggle when you're dealing with large-scale datasets, integrating data from multiple sources, or managing complex hierarchies. Here's a real example: we wanted to know how many Fortune 500 companies were subscribed to our newsletter and how many were customers. With a mailing list of over 40,000 subscribers and thousands of accounts in Salesforce, it took our RevOps team more than a week to deliver an answer—and the process was anything but smooth.

To analyze data efficiently at scale and across diverse sources, you need more powerful tools than a spreadsheet can offer—tools like SQL, Python Pandas, and Jupyter notebooks. But let’s be real, I haven’t written much code since the early 2000s. Many business users are in the same boat—these tools are out of reach. Even when data and engineering teams step in, ad-hoc analysis isn’t their favorite task. The back-and-forth to translate business requirements into SQL queries eats up time and often leads to miscommunication.

That’s where Gigasheet comes into play. Gigasheet brings the familiarity and ease of a spreadsheet while scaling to handle massive datasets and integrate multiple data sources—all without needing coding skills. It's designed for business users, but it also includes the governance and API controls that data teams need. Gigasheet helps users explore your data quickly without predefined processes getting in the way.

Historically, ad-hoc analysis at scale required SQL or Python Pandas. Gigasheet allows everyday users to get answers without requiring those skills. We make it easy to combine data from a variety of sources like databases, warehouses, or big CSVs and JSON files, all within a few clicks. With this power in your hands, users are less dependent on high value resources for dynamic analysis.

The real strength of Gigasheet lies in its simplicity. Start with a broad question, and as you dig deeper, evolve your analysis in real time. Need to filter or create calculated fields on the fly? Easy. Want to spot anomalies or visualize trends? Gigasheet’s built-in tools have you covered. If you’re dealing with large data, tools like Pandas are traditionally the go-to, but Gigasheet empowers non-coders to work at scale without that technical overhead.

At the end of the day, the ability to perform flexible, on-demand analysis is crucial. With Gigasheet, both analysts and executives can dive deep into their data, uncover insights, and get the answers they need—no code required. The future of ad-hoc data analysis is here, and it’s called Gigasheet.