Invented by Mohan; Ram, Boni; Prasanna, Mishra; Anushka, Ranjan; Khushika

Today, businesses depend on both spreadsheets and databases to manage and analyze their data. But there’s a gap between these two worlds. This gap leads to slowdowns, mistakes, and limits on what users can do. A new patent application proposes a way to fill this gap, letting people use familiar spreadsheet formulas to tap into the power of big databases, all without learning complex code. Let’s unravel how this invention works, why it matters, and what makes it unique.

Background and Market Context

Spreadsheets are everywhere. In offices big and small, people use tools like Microsoft Excel and Google Sheets for tasks from budgets to forecasts. Spreadsheets are easy for anyone to use—just type in numbers, write a formula, and get results. You see your work in neat tables and charts, and you don’t need special training. This is why accountants, analysts, and managers rely on them every day.

But spreadsheets have limits. As data grows, spreadsheets can get slow and even crash. Most tools cap the number of rows and columns you can use. Try working with millions of records, and you’ll hit a wall. Also, spreadsheets can’t handle very complex analysis, like advanced modeling or data mining. Security is another worry: sharing files can lead to leaks or accidental changes.

To solve these problems, businesses invest in databases. Databases can store huge amounts of information, keep it secure, and let many people work together at once. With a database, you can run powerful searches, combine different sources, and get answers fast. But using databases isn’t easy. You need to know special languages like SQL, and most spreadsheet users don’t have that training. Moving data from spreadsheets to databases (and back) often means hiring experts or learning new tools. This process is slow, costly, and full of chances for errors.

So, companies face a tough choice. They can stick with spreadsheets and accept their limits, or move to databases and lose the simple interface their teams love. The market is full of add-ons and plugins that try to bridge this gap, but most are clunky or require too much technical know-how.

This is where the patent application we’re exploring comes in. It offers a way for users to keep their familiar spreadsheet interface, but under the hood, it turns their formulas into fast, efficient database queries. Users don’t have to know SQL or any programming—they just keep using their spreadsheets, and the system does the hard work for them.

Scientific Rationale and Prior Art

The science behind this patent comes from the fields of computer language processing and database theory. In simple terms, computers need a way to understand what people mean when they enter a formula. Programmers have long used things called “syntax trees” to break down commands into pieces the computer can follow. At the same time, databases use their own logic—called “relational algebra”—to figure out how to fetch and mix data quickly.

Before this invention, there were already some tools that connected spreadsheets and databases. Some plugins let you pull data from a database into a spreadsheet, or push spreadsheet tables into a database. Some advanced tools let you write SQL right inside a spreadsheet, but for most users, SQL is too hard. Others try to “record” spreadsheet actions and turn them into scripts, but these are often limited and can’t handle all the ways people use formulas.

Another challenge is keeping things up to date. If your spreadsheet pulls data from a database, what happens if the data changes? Many solutions require you to refresh the data manually or don’t support real-time updates. Some systems also struggle with keeping calculations fast when the data is huge or when many people are working at once.

On the technical side, past inventions have tried to “parse” spreadsheet formulas—breaking them into parts so a computer can understand them. This parsing process usually involves building an “abstract syntax tree” (AST), which maps out the steps in a formula. For example, in =SUM(A1:A10), the AST would show that you’re asking to sum a range of cells. But just parsing isn’t enough—you need to turn that structure into something a database can run. That’s where “expression trees” and “relational algebra” come in. These steps turn the formula’s logic into a set of instructions the database can understand and execute quickly.

While the building blocks existed, no prior system fully combined them in a way that allowed non-technical users to write regular spreadsheet formulas and have them automatically converted—on the fly—into optimized database queries, with results displayed live in the spreadsheet. Especially missing were features like real-time data updates, handling multiple data sources, and optimizing queries for speed and efficiency, all in an easy-to-use package.

Invention Description and Key Innovations

This patent application presents a complete solution for letting spreadsheet users harness the power of databases, without leaving their comfort zone. Here’s how it works, step by step, in plain language:

1. Receiving the Formula: The system starts with a spreadsheet interface—just like Excel or Google Sheets. The user enters a formula, for example, =SUMIF(customers[CITY],"Delhi",customers[AGE]). The user doesn’t need to know where the data lives or how to write queries.

2. Building the Abstract Syntax Tree (AST): When the formula is entered, the system breaks it down into its parts. It uses grammar rules (like those in language textbooks) to figure out what each piece means: which part is a function, which part is a reference, which part is a value. This creates a tree-shaped map that lays out the structure of the formula. Each “node” in the tree represents something—like a function, a cell reference, or a number.

3. Creating the Expression Tree: Next, the system turns the AST into an “expression tree.” This step simplifies things by focusing on the actual calculations and business logic. It strips away extra details and organizes the steps in the order they need to happen. It can also remove any repeated or useless parts, making the calculation as efficient as possible. For example, if the same table is referenced twice, it only needs to be fetched once.

4. Translating to Relational Algebra: The expression tree is then turned into a set of logical instructions that databases understand—called relational algebra. This step is like converting a recipe written in one language into another, making sure the meaning stays the same but using the terms the database speaks.

5. Generating Database Queries: Now, the system takes the relational algebra and writes an actual database query—usually in SQL. It chooses the best way to fetch the needed data, apply filters, and do the calculations. It uses smart algorithms to optimize the query, so it runs fast and doesn’t waste resources.

6. Running the Query and Fetching Results: The system connects to the right database or data source, runs the query, and gets back the results. This could be a single number, a table, or any other output the user expects.

7. Showing Results in the Spreadsheet: The output is displayed right in the spreadsheet, just as if the formula had been calculated directly. The results can be shown in tables, charts, or other formats. Users can sort, filter, or drill down into the data without ever seeing the underlying query.

8. Keeping Everything Up to Date: One of the clever parts of this invention is that if the data in the database changes, the system can automatically rerun the query and update the results in real time. The user doesn’t have to refresh or re-enter anything—the spreadsheet always shows the latest data.

9. Handling Multiple Queries and Data Sources: The system can handle many formulas at once, even if they use different data sources. It prioritizes and schedules queries so everything runs smoothly, even with big data or lots of users. It can also run queries in parallel, making things even faster.

10. Security and Efficiency: Because the heavy lifting happens in the database, the system benefits from all the security, speed, and reliability features databases offer. There’s no risk of overloading a simple spreadsheet tool, and sensitive data stays protected.

What truly sets this invention apart is how seamless the experience is for the user. They don’t see any of the behind-the-scenes work. They just write formulas as always, but now they can work with much bigger data, get results faster, and trust that everything is accurate and secure. The system adapts to different spreadsheet programs and database types, so it works in many environments. It can even be updated to support new functions or data types as needed.

From a technical point of view, the invention covers both methods (the steps and processes) and devices (computers and software systems) that implement this solution. It uses a modular structure, with different components handling input, parsing, optimization, query generation, execution, and output. This design makes it flexible, scalable, and easy to maintain or extend.

For businesses, this means less need for training or hiring database experts. Teams can work faster and smarter, using the tools they already know. For IT departments, it means better security, less risk of errors, and easier management of data. For software vendors, it opens the door to new features and integrations that bring more value to users.

Conclusion

This patent application describes a big step forward in how we use data at work. By turning everyday spreadsheet formulas into powerful, optimized database queries—automatically and invisibly—it gives users the best of both worlds: the simplicity of spreadsheets and the muscle of databases. In a world where data keeps growing, and businesses need to move faster, this is an innovation with real impact. Whether you’re an analyst, a manager, a developer, or an IT leader, this technology promises to make your work easier, faster, and more reliable—without asking you to learn anything new.

Click here https://ppubs.uspto.gov/pubwebapp/ and search 20250217364.