Continuous Data Quality Monitoring with Gangesh Ganesan

Data Transformers Podcast
Continuous Data Quality Monitoring with Gangesh Ganesan
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Episode: Continuous Data Quality Monitoring with Gangesh Ganesan

Episode Summary: Is continuous data quality monitoring a myth? Not so fast. That is according to Gangesh Ganesan, Founder & CEO of PeerNova. Traditional data quality monitoring requires data to be in a repository and data quality platforms apply certain business rules to measure the data quality. And the exceptions are referred back to the data sources/owners to fix the exceptions. PeerNova’s Cuneiform solution, with its origins in data security & networking, applies a no-code approach to solving the measurement and monitoring problem. Additionally, Gangesh talked to us about measuring the business impact of the exceptions that are identified. With a technologist background, Gangesh got an opportunity to switch to the business side when the company he was working for decided to spinoff a division. After a couple of iterations, Gangesh sold his previous company to Qualcomm. And the he embarked on the data quality journey with special focus on financial institutions.

1:30: PeerNova is a SaaS company focused on data quality monitoring. Focused on quantitative measurement of quality of data. Data does not have to be in a central repository for PeerNova solution to do its job.

4:00: One of the earliest use cases is monitoring the data quality in stock settlements on the wall street. Settlement use cases. Data quality plays a big factor in settling trades and financial instruments.. This involves multiple parties and data quality is important to accurately settle the trades..

7:30: Monitoring data quality across the network i.e. within the enterprise as well as across the 3rd parties is very important. .

9:20: No-code approach is the best way to including business users in monitoring data quality. Otherwise it becomes an IT function’s problem.

13:00: Peernova journey has been going on for 7 years. With the observation that data quality problem is actually a data lineage problem across the network, a blockchain approach seemed relevant. Actually, financial institutions helped Peernova connect with other parties for much bigger impact.

18:20 (Headliner) Gangesh’s entrepreneurial journey. Started with Bosch. Had an opportunity to buy a division being sold off and sell it. Another similar opportunity and sold the next company to Qualcomm.

21:00: Where is the drive coming from? From the original goal of having an ‘exit’ and transitioning to ‘enjoy the journey’ liberated.  Flow state concept drives people to be 3x to 5x when they are in a flow.

24:00: Inflection point of transitioning from a technologist to an entrepreneur. Be curious. Trying to learn and grow constantly. When you are learning, you’ll know where the opportunities are and how to take advantage of.

26:00: Worked at Cypress semi. Went to a training session on first day. Learned to be a ‘precision questioning’. Answer just the question.

Resources mentioned in this episode:

Podcast website: https://DataTransformersPodcast.Com

Data Transformers Podcast

Join Peggy and Ramesh as they explore the exciting world of Data Management, Data Analytics, Data Governance, Data Privacy, Data Security, Artificial Intelligence, Cloud Computing, Internet Of Things.

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