Data Gurus Podcast | Insights on Business Strategy, Mergers and Acquisitions, Market Research & Data Collection

Data Quality in the Financial Markets | Ep. 129


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In today’s episode, Sima is excited to welcome Gangesh Ganesan, the Founder and CEO of PeerNova, as her guest on the show. This podcast is typically about data and the data ecosystem. Today, however, Gangesh takes us into the area of the financial market. In this episode, he explains the importance of ensuring that data has good quality and is accurate.
PeerNova
PeerNova is a Silicon Valley-based data company founded by Gangesh Ganesan about five years ago. They have offices in Silicon Valley, San Jose, London, and New York. Although their themes mostly get distributed worldwide, the core is in Silicon Valley. Some of their development happens in Eastern Europe and they also have a theme in Brazil.
A global company
PeerNova is a global company. They are venture-funded and raised a substantial amount of capital to develop their software platform.
Software platform
The PeerNova software platform is called Cuneiform and offers data quality for financial institutions.
Data quality
Data quality means ensuring the correctness, completeness, consistency, and timeliness of data that might get distributed across different applications, databases, data stores, and data warehouses in a global financial institution.
Making the correct decisions
Currently, data quality is vital for making the correct decisions in the financial industry. It has been a big problem in that industry for the last two or three decades.
Financial Institutions
Financial institutions typically solved their data quality problem by employing many people to ensure that data was correct, complete, and consistent. In some cases, it could take tens of thousands of people to solve the problem for large financial institutions.
The Cuneiform platform saves time and money
The Cuneiform platform is about applying technology to automate as many of the workflows as possible. It can do that at a substantially lower cost, and more importantly, it does it near real-time.
Inspiration
Early on, Gangesh was inspired by some ideas that came about in blockchains. A crucial notion in blockchains is that of lineage, with which you can find the origin of any transaction. And you can track it either forward or backward to find the seed or genesis event. That idea inspired Gangesh to build a generic software platform with which every piece of data could get tracked in that way.
Data quality
They soon realized that maintaining the lineage and ‘audit trails’ of the data quality of financial institutions at scale and solving for correctness, completeness, and consistency problems was a vital challenge. It took them four or five years to build their Cuneiform platform. Financial institutions have been undergoing many changes
Financial institutions have been undergoing many changes over the last twenty years. And their pain points have become very acute.
The current focus
The entire focus of Gangesh’s business is currently in capital markets and financial institutions.
The Zero Code
Using what is known as Zero Code, Gangesh has ensured business users, who are often tech-savvy but are not developers, can have the four attributes of data quality-correctness, consistency, completeness, and timeliness for all their data.
Accuracy
In the financial industry, they cannot afford to make any mistakes, so their data quality needs to be accurate one hundred percent of the time.
Enterprise selling
Enterprise selling of software at very high levels can be a problem, so Gangesh offers his clients the chance to do a free pilot to see if their model works for that specific use case. Reference-able clients are a big deal at PeerNova, so they also try to identify easy-to-replicate use cases to have a step-and-repeat concept that is easy to demonstrate.
The problem of data quality
The problem of data quality is something fundamental. The financial industry has always lacked a comprehensive end-to-end solution for that problem. Gangesh believes that data quality is a category-making idea for which ...
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Data Gurus Podcast | Insights on Business Strategy, Mergers and Acquisitions, Market Research & Data CollectionBy Sima Vasa

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