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Kafka Summit San Francisco 2018

Streaming platforms at massive scale.

October 16-17, 2018 | San Francisco

Where Fast Gets Faster—How OVO Leverages Apache Kafka and a GPU-Accelerated Engine to Get Instant Insight

Session Level: Beginner
Video & Slides

Most organizations are faced with data sources from only one industry, be it telco, finance or retail. That’s hard enough. OVO is the payments, loyalty, and financial services app of the Lippo Group, a major conglomerate in Southeast Asia. OVO wanted to integrate data across different businesses into a single digital ecosystem to serve over 120 million consumers. Talk about a new level of complexity! OVO set out to consolidate customer data generated by their various subsidiaries into a centralized analytics platform to generate a 360-degree view of the customer. However, they found that their legacy databases and data lakes couldn’t analyze streaming data fast enough.

In this session, Irina Farooq, vice president of product at Kinetica, will share how OVO has leveraged Apache Kafka along with Kinetica’s GPU-accelerated engine to modernize their data stack and instantly ingest and analyze streaming data. This helps OVO to improve customer experience, deliver targeted marketing offers and increase operational efficiencies.

Learn how OVO moved to real-time streaming data analysis to power an innovative customer 360 initiative that stretches across their business units. OVO brings together customer data into a central analytic platform using multiple customer attributes including cross-channel behavior, demographic/behavioral/geographic data, brand sentiment, social media actions and purchasing patterns to enable personalized interactions throughout the customer journey. The technology behind this includes an analytic API that enables queries on huge volumes of streaming data in under seconds, compared to something that used to take minutes to hours. With Kafka and Kinetica, OVO can now analyze streaming data in real-time to gain insights into consumer trends and behavior, ultimately improving the customer experience, conversion rates, inventory life cycle management and future purchasing predictions.


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