Confluent's Rubal Sahni Shares How Data Streaming is Transforming the Market

Rubal Sahni of Confluent discusses how data streaming transforms Indian businesses, enhancing real-time decision-making, efficiency, and personalized customer experiences.

Punam Singh
New Update
Rubal Sahni, Confluent

Data streaming technologies offer a dynamic market for Indian companies. By enabling real-time analysis and decision-making, these technologies help businesses adapt swiftly to changing market conditions, personalize customer experiences, and improve operational efficiency.


This exclusive interview with Rubal Sahni, Area VP and Country Manager, India, Confluent explores the benefits and applications of data streaming for Indian companies, the role of governance and compliance, and how notable partnerships and collaborations are bolstering the data streaming ecosystem in India.


DQ: How do data streaming technologies provide a competitive advantage to Indian companies in a dynamic market environment?


Rubal Sahni: In today's fast-paced market, data streaming technologies provide Indian companies with a distinct competitive edge. Unlike traditional batch processing, data streaming enables real-time analysis of information as it's generated, allowing for quicker and more informed decision-making. This is crucial in India's rapidly changing market, where customer preferences and industry trends can shift swiftly.

By leveraging data streaming, companies can personalize offerings and interactions instantly, leading to increased customer satisfaction and loyalty. The real-time insights enable businesses to swiftly adjust strategies, pricing, and product offerings, maintaining competitiveness in a fast-evolving landscape.

Data streaming equips organizations with a unified, real-time view of their data, unlocking advantages such as streamlined workflows, increased automation, and more efficient operations. It's crucial for cutting-edge applications like real-time fraud detection and predictive maintenance, especially valuable in sectors where Indian companies compete globally.

Moreover, data streaming facilitates AI and ML adoption, with 98% of India’s IT leaders with experience of data streaming believing it simplifies these technologies' implementation. This capability drives innovation and competitive advantage, allowing Indian companies to stay at the forefront of technological advancements and market responsiveness.


DQ: Given the importance of governance in data management, how do data streaming platforms assist Indian companies in maintaining compliance and managing data risks?

Rubal Sahni: Most of our customers operate mission-critical workloads (like payments or orders) with Confluent. Having continuous and up-to-date visibility into a business is important, and 80% see data streaming platforms as a key or important enabler for achieving this visibility and 81% of leaders stated that data streaming helps address governance-related problems. Our complete data streaming platform provides customers with tools for operations, management, monitoring, security, and SLAs / support guarantees to meet required compliance requirements with confidence. With the real-time capabilities of the platform, customers can quickly detect emerging risks in their environment.  

DQ: How are Indian companies leveraging data streaming, and what benefits have they observed in terms of cost savings and operational efficiency?


Rubal Sahni: Data streaming is enabling companies to gain real-time insights and improve their operations, allowing them to analyze customer behavior, track industry trends, and understand competitor strategies in real time. According to our survey, 67% of businesses believe that data streaming activities enable more data-driven operational decisions, while 87% of IT leaders think real-time data streams promote consistency and a more accurate, unified business view.

For example, Mobile Premier League (MPL), one of the world’s largest eSports and mobile gaming platforms based in India, needed to strengthen its systems architecture to support the scale of over 90 million registered users. With data streaming, MPL achieved savings of $35K per month. It was also able to generate tailored offers and identify fraudulent users in real-time for better user retention.

Apna, an Indian professional networking platform adopted Confluent Cloud to power an event-driven architecture. This led to a two-times increase in speed to market for business solutions, elastic scaling to support their 30 million users, and 99.99% uptime. The platform now efficiently serves job seekers and employers with real-time, responsive services.


DQ: Can you discuss any notable partnerships or collaborations Confluent has undertaken in India to bolster the data streaming ecosystem?

Rubal Sahni: We recently announced a new partner program called 'Build with Confluent' which specifically targets system integrators and offers them a comprehensive toolkit to accelerate their development and monetization of data streaming solutions. This program fosters a network of skilled partners who can deliver robust data streaming solutions tailored to the needs of Indian businesses. In India, Persistent and Platformatory have joined the program as our launch partners.

In today's digital-first world, businesses require a modern platform to manage the ever-growing stream of data they generate. This "data in motion" is crucial for providing exceptional customer experiences and ensuring smooth business operations. Accelerate with Confluent, is another program for systems integrators (SIs) that prioritizes excellence in Confluent Professional Services to empower partners to deliver comprehensive data streaming solutions. 


Moreover, the public sector in India is emerging as a key focus area for data streaming adoption. Over the next 12-18 months, we look to significantly push our partnerships with Indian public sector entities. We are seeing that government agencies and public services are recognizing the potential of data streaming to improve efficiency, transparency, and service delivery.

DQ: What challenges do companies face when implementing data streaming technologies, and how can they overcome these obstacles?

Rubal Sahni: Apache Kafka and Apache Flink, the de facto standard for data streaming and a widely adopted standard for stream processing respectively, effectively cover the two key components of an event-driven architecture - streaming and processing. The open-source nature of Kafka and Flink lowers the entry barrier for working with streaming data, allowing companies to easily build use cases and solutions. Their wide adoption provides a standardized framework to build upon rather than reinventing the wheel. So most organizations probably already have Kafka and/or Flink in their organization.


However, there are some limitations with solely relying on open source streaming technology. According to the data from our 2023 Data Streaming Report, the two most prominent obstacles India’s IT leaders faced while implementing data streaming are data silos and skill gaps. 72% of them said that uncoordinated teams and budgets can be a challenge or a major obstacle to advancing data streaming initiatives. This fragmentation can lead to inefficiencies, inconsistent data usage, and difficulties in realizing the full potential of data streaming across the organization. 78% of them identified the lack of relevant skills, expertise, and experience as a significant challenge. The complexity of data streaming technologies requires specialized knowledge that many organizations currently lack.

As such, companies often end up spending more to efficiently manage, scale, secure and evolve the streaming infrastructure. This is where enterprise-grade streaming platforms like Confluent can complement open source with connectivity, security, management and optimization capabilities suitable for mission-critical workloads.

DQ: How do data streaming technologies integrate with existing IT infrastructure and what impact does this have on overall business performance?

Rubal Sahni: At Confluent, we strive to be cloud-native, comprehensive, and ubiquitous. As a cloud-native solution, we provide elastic scalability for managing gigabit-per-second workloads with ease, allowing for seamless scaling up or down while ensuring 99.99% uptime and unlimited data retention. Our platform is complete, offering an enterprise-grade data streaming solution with over 120 pre-built connectors that integrate seamlessly across all your applications and data systems. Additionally, we offer fully managed services on AWS, Azure, and Google Cloud, as well as self-managed software for on-premises and private cloud workloads.

Building integrations to be available across major cloud infrastructure providers ensures that we can reach businesses wherever they are. This allows them to focus their resources on the areas that matter most, instead of managing IT infrastructure.

Besides reducing risks as mentioned earlier, our managed data streaming platform can allow businesses to:

  • Reduce the total cost of ownership (TCO) by up to 60% compared to using open source Apache Kafka
  • Ensure faster application development and time to market and greater data reuse by developing data products