Exclusive Interview with Deb Dutta, General Manager, Datastax

DataStax

DataStax

Data, of late, has become the lifeblood for business operations and market prediction; but the cutthroat competition demands a business house to stay on top of the things. Be it monitoring consumer behavior, uncovering product insights, or catching up with web analytics, there is nothing like real-time insights that can make businesses make quick and productive decisions. Datastax is a data analytics company that develops analytics tools capable of generating insights in real-time to make companies not just catch up with their counterparts but lead the league. Analytics Insight has engaged in an exclusive interview with Deb Dutta, General Manager, Datastax.

1. What is the biggest USP that differentiates Datastax from competitors?

DataStax is a real-time data company committed to helping businesses mobilize their data in real-time and quickly develop smart, global-scale applications that make us a data-driven business. Today, there is a real urgency to utilize real-time data to run agile businesses, engage customers, and, fuel machine learning.

The DataStax open stack combines Astra DB, built on the world’s most scalable database, Apache Cassandra, and Astra Streaming, built on Apache Pulsar,  to harness data in motion and at rest to build rich and engaging real-time applications that deliver high throughput and low latency at massive scale. Our objective is to serve real-time applications with an open stack that just works.      

The most influential trend that has emerged is real-time. Specifically, the use of real-time data to:

  •  Create in-the-moment personalized experiences with integrated real-time analytics, search, and graph capabilities.
  • Provide a 360-degree view of real-time and batch data to get a comprehensive view of your customers.
  • Access to Real-Time Insights with the ability to ingest, channel, and process data instantly, to derive insights for the business to immediately act upon. 

As data architectures become increasingly complex, it’s tougher to optimize data for scale and speed, yet being competitive depends on how quickly and comprehensively a business can activate data.           

3. How is Datastax helping customers deliver relevant business outcomes?

With the use of real-time data, DataStax is enabling its customers to build game-changing applications that power the business and are a part of our daily lives. Think Endowus provides personalized financial product recommendations based on your profile, Uber’s ride-sharing applications track where thousands of drivers are in-the-moment. Or the mobile applications millions use to order a coffee; that is tapping data from the database about who ordered the coffee and their favorite drinks. 

DataStax provides a multi-cloud serverless database that offers pay-as-you-grow pricing leveraging public cloud infrastructures to lower the total cost of ownership. With powerful APIs, developers can easily start developing innovative applications that will set their companies apart from the competition.

Astra DB speeds up modern app buildout, benefits from cloud economics, simplifies      DevOp, and reduces costs.

DataStax also provides solutions such as DataStax Enterprise to customers that prefer a self-managed, enterprise-grade version of Cassandra equipped with advanced workloads like Graph, Search, and Analytics capabilities. No matter where our customers are in their digital transformation journey or transition to the cloud, we meet them where they want us to with our solutions that allow them to manage their data store or opt for a managed service.    

 4. Which industry verticals are you currently focusing on and what is your go-to market strategy for the same?    

Our technology is universal and segment agnostic. We see demand in 3 specific buckets: Government, Legacy enterprises (specifically financial services and manufacturing), and Cloud native-born in the cloud businesses. The first two segments leverage our open-source software fundamentals, hybrid deployment ability, and capabilities like real-time fraud detection, email threat detection, instantaneous personalized offers on e-commerce sites, and transportation and logistics.

The cloud natives love the scalability, super-fast provisioning, Kubernetes-based centralized control plane, cloud economics, and API-fuelled developer velocity that Astra provides.

5. Would you be able to highlight a few use cases where real-time data analytics has benefitted Indian enterprises?

Imagine IoT devices on crops that take real-time data about hydration levels on the crops and deliver that data back to the database. In real-time, automated decisions are made about how much water is needed to sustain the crops. This has the power to reduce water waste.

A company providing email threat detection to its customers around the globe is using DataStax Astra DB to instantaneously process threats and protect its customers in real-time.

The Alpha Ori platform monitors and combines parameters such as ship speed, fuel consumption, machinery operating temperatures, pressures, pump RPMs, torque measurements on the shaft, refrigeration temperatures, wind speed and direction, and thousands of additional data points from the approximately 40 major equipment systems on a typical ship. To provide intelligent analytics, alerts, and insights to vessel stakeholders both aboard and onshore, Alpha Ori built its platform with an open-source Apache Cassandra® database.

6. What are the biggest hurdles companies face in implementing real-time data analytics and how do you recommend they overcome these hurdles?

Harnessing real-time data! It is the most complex part of delivering the world’s innovative applications that are a part of our daily lives. DataStax removes the complexity with its open-source database-as-a-service, powerful APIs, and serverless architecture.

The primary challenge businesses face with the real-time data intent is that data is locked in silos – applications, data warehouses, data lakes, etc. These silos do not talk to one another and therefore the value of the data within is not unlocked. DataStax’s open stack resolves this with an operational data store based on an open-source framework that can consolidate data from disparate systems using open ‘hooks’ – this consolidated data ‘at rest’ can then be queried in real-time for business insights and customer experience. Additionally, any change in this operational data store is also captured in real-time and streamed as ‘data in motion’ to downstream applications, data lakes, and AI/ML engines for processing and analytics.

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