Making the business case for data observability with Rohit Choudhary - CEO of Acceldata

Listen to this episode on Anchor FM

How do you make the business case for data observability? In this episode of DATAcated on Air, host Kate Strachnyi speaks with Rohit Choudhary, CEO of Acceldata, about data observability, what it means, and why it’s important. Listen in to learn more about how data observability is helping businesses reach their goals.

You will want to hear this episode if you are interested in...

  • What is data observability? [02:49]
  • Types of companies Acceldata serves [07:24]
  • Starting the conversation [08:24]
  • What does Acceldata do? [10:21]
  • Pitching data observability [16:19]
  • The importance of data observability [21:55]
  • Success with PhonePe [30:55]
  • How does the system handle data drifts? [32:37]
  • The future of data observability [37:03]

Getting more from data

Companies have been investing in data science and technology to manage their data. When Acceldata started, customers were going through on-premise infrastructure and were finding it difficult to operate. In the last three and half years, the world has completely changed. Now there are systems like Snowflake and various CSPs. Today, companies and CEOs are responsible for dealing with multiple ecosystems where data resides, depending on their quality requirement and the kind of business they serve.

From an overall perspective, everyone is trying to get more out of their data. The challenge with data operations is that there are three points of pain. Operational pain is from dealing with complex systems. Innovation pain is from using the best engineers to solve day-to-day issues rather than creating innovative solutions on the business model. A big topic is also the budget. For the next few years, as this trillion-dollar opportunity of migration to the cloud begins, there will be a lot of talk of financial controls.

Making the pitch

A great way to start the conversation about data observability is to ask if the data your company uses is reliable. Then, ask if the processed data is the correct data to base decisions. A great example of this is what happened to Zillow. One of Zillow’s models started processing data incorrectly. As a result, houses were being priced out of the market. The company was buying at higher prices and selling at lower prices. This sort of business outage has critical effects on companies and their productivity. Acceldata’s mission is to eliminate complexity, scale data utilization, and generate better results.

Why is data observability important?

Data is going to drive businesses for all enterprises, large and small. This direction means a company must have a reliable grid. Without good, high-quality, reliable data, obtaining desired outcomes will be difficult. Acceldata’s mission is to eliminate complexities, scale data utilization, and generate better results from a business point of view. The most significant challenge people have today is processing more data and use cases. Business has an unending appetite to consume more business use cases and all that is related to data.

Acceldata figured out early in its journey the necessity of monitoring the data pipelines, the quality of data, and the underlying computer systems. When all those things are put together, it’s clear that what’s needed is a multi-dimensional system. This system would provide visibility into these complex, opaque data systems and would have the capability of synthesizing signals across these layers. The company can simulate performance of different workloads to figure out how much capacity is needed on an ongoing basis.

Resources & People Mentioned

Connect with Rohit Choudhary

Connect with DATAcated

Subscribe to the DATACATED On Air podcast