[Startup Bharat] This Nagpur couple built a data migration engine which serves customers in the US

Smita and Sandesh Gawande run Torana Inc. has built an agile rules engine named, ‘iCEDQ’ to automate ETL testing, data migration testing, and big data testing.

Sandesh Gawande, the Chief Technology Officer (CTO) of Torana Inc., came across one of the most common problems in technology – unsuccessful data migrations. He found out that there was not a single way to ensure the success rate, nor existed a platform that automated testing to extract, transform, and load (ETL), and data migration.

Typically, ETL testing refers to the testing of the data that is extracted from one database and transferred to another. With no solution to the problem, Sandesh says, ETL testing could potentially influence several million-dollar technology companies that deal with huge amounts of data daily. Further, the problem needed a platform that would automate the phenomenon and also assure quality.

Sandesh and Smita.

"Born out of this problem was iCEDQ, an enterprise-suite DataOps automation software and a data quality governance platform for ETL testing, big data testing, and data migration testing," says Sandesh.

This agile rules engine was built by Torana Inc., a software product company started by Smita Gawande (CEO) and her husband, Sandesh Gawande.

Based out of Nagpur, Torana was founded in February 2007. At present, the startup has offices in Nagpur, which is 63-member strong, and Stamford, Connecticut, the United States, with 18 employees.

The startup derives its name from the Torana Fort, built by Chhatrapati Shivaji. It signifies a symbol of purpose, initiative, bravery, and strength.

Product roadmap

Smita and Sandesh are both engineers. Smita is a computer science engineer and has experience working as a business intelligence architect at companies like GE Capital, Verizon, and Praxair in the US. Sandesh is a mechanical engineer and has experience working and consulting as data and ETL architect for companies like Qualcomm, GE, Deutsch Bank, JPMorgan Chase, and Morgan Stanley.

Sandesh was heading the back-office migration process for one of the financial firms when the Chief Information Officer (CIO) commented on the data compromise during the migration process. He researched and found out that no such product was available in the market to prevent the same. So, he decided to work on the problem.

Sandesh says, "We revised our product thrice. We redesigned it and finally built a JAVA-based in-memory engine, and now we have Apache spark-based in-memory engine. The ever-changing technology space is a challenge but, we take it as an opportunity to keep our products updated for the customers."

Considering iCEDQ was a technical and not a business product, Sandesh says, the tech teams ought to get approvals from the business teams to buy a product like this. Since iCEDQ is a niche technical product, Sandesh says content strategy and educating people is a challenge. Several companies still work with the manual form of ETL testing; they don’t know that such a product exists and can solve their problem.

Business model

iCEDQ was built as an agile rules engine to improve productivity and shorten the project timelines of testing data warehouse and ETL projects, with powerful features. Torana follows the licensing business model for iCEDQ, where users buy the licenses in three editions – standard, high throughput, and big data.

The first customer of Torana was Nomura Securities, and the next few customers were acquired through digital marketing. The startup’s clientele list reportedly includes the likes of the New York Stock Exchange, IBM, Lockheed Martin, Nomura, Great American Insurance Group, etc.

Sandesh says the feedback loops from the startup's customers have helped the company evolve the product continuously into a complete test data management solution.

He also claims that the platform has matured into full-agile, delivering 100x scalability, and 40 percent cost reduction, over the manual and cumbersome ETL testing processes.

Bootstrapped since day one, the company is now estimated to be making an annual recurring revenue of $5 million. Sandesh says the startup has been constantly innovating in the data testing space, by using customer feedback and the latest technological developments to grow the product. The startup also has two other products in development, he adds.

"We aim to grow both vertically, as well as horizontally in the data testing space," Sandesh concludes.

(Edited by Suman Singh)


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