Here’s how Databricks helped leading cloud-native enterprises in India make the most out of their data strategies at Destination Lakehouse

By Christopher Isaac
November 30, 2022, Updated on : Fri Dec 02 2022 05:12:12 GMT+0000
Here’s how Databricks helped leading cloud-native enterprises in India make the most out of their data strategies at Destination Lakehouse
Data lakehouse pioneer Databricks helped businesses understand and leverage the power of data and AI, through its Destination Lakehouse summit which was held in Bengaluru recently.
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According to the report ‘AI Gamechangers: 2022 Realizing India’s AI promise’ by IndiaAI, a government-led industry group, AI is expected to raise India’s annual growth rate by an addition of $957 billion by 2035, or 15% of current GVA (gross value added) to India’s economy. Another report by IDC projected India’s AI market to reach $7.8 billion by 2025, growing at a CAGR of 20.2%.


Data being one of the most crucial components in an AI and machine learning (ML) project, managing and leveraging your data in efficient and cost effective ways is something every enterprise aims for, and having a great data strategy is just as important as having your business model. As Dr. Mohit Kumar, VP & Head of Data Science, Data Platform and Product Analytics, Udaan, explained at the Databricks Forum in Bengaluru, “Data science should be pervasive, embedded in your business processes. That’s the intention.”


One of the ways companies can do just that is by adopting a data lakehouse strategy that combines the best of data warehouse and data lake technologies, giving enterprises the ability to store their data securely while integrating analytics and machine learning. The Destination Lakehouse summit — hosted on August 24 and 25, 2022 — served as a platform for Databricks to showcase real world use cases of their Lakehouse platform through early adopters of the technology including well-known Indian brands Meesho, Udaan, and Freshworks.


“The Destination Lakehouse summit aims to bring data lakehouse to the global data community with tailored local content and use cases to spark off conversations and share best practices for businesses across every industry,” said Anil Bhasin, Vice President and Country Manager for Databricks India.


Day 1 pitched the platform to Indian enterprise leaders, with Ed Lenta - SVP of Asia Pacific and Japan, Databricks who kicked things off with the introduction of the company and its data solutions to empower data science teams.


This was followed by Katreddi Kiran Kumar - Vice President for Data Platform, Meesho, who demonstrated how partnering with Databricks helped the company overcome four main challenges they were facing with their data strategy: platform scalability, collaboration across data teams, total cost of ownership (TCO), and time to market.


This, Kiran explained, was achieved through implementing the data lakehouse strategy to compile and migrate their data in an organised manner, making it easier for in-house data science teams to apply AI/ML processes to gain insights, and innovate new services and features quicker. “Fast and effective, the Databricks Lakehouse Platform enables Meesho teams to improve their TCO, developer experience, get better price performance, and helps developers to focus on extracting business value instead of maintenance overheads,” Kiran added.


The presentation was followed by a panel discussion with industry leaders Soumya Simanta - VP for Data & ML Platform, Swiggy; Dr. Mohit Kumar - VP & Head of Data Science, Udaan; Vishal Singh - Head of Engineering, Data Platform, Razorpay; and Kiran, on the need for enterprises and companies to invest in data science to help build better products and services for their customers. The session was moderated by Kunal Taneja - Director, Field Engineering, Databricks, who summed up the discussion saying, “If there’s one thing that many of us have in common, it’s that we believe in the impact that data and AI can and will have on the world. It is still very early days but, today, data and AI is transforming every major industry.”


Day 2 at Destination Lakehouse saw data science teams and engineers from startups across India learning about the lakehouse paradigm, with customer presentations from Udaan and Freshworks.


Udaan’s Dr. Mohit reiterated the need for data science to power product innovation, stating that any company’s data strategy should follow on three key principles: ease of discovery and access, ease of data insights, and data fidelity and reliability, keeping security, governance and cost efficiency in check. Likening data to the “new electricity” powering e-commerce and data platforms the electricity utility provider, added that through the Databricks Lakehouse Platform Udaan was able to run real-time applications for its data teams, implement AI and ML, and gain tangible business insights and analytics.


Jeganathan Velu - Director Business Analytics, Freshworks followed up with a detailed outlook on Databricks’ effect on the SaaS company’s data strategy. This included a 75% reduction in platform maintenance costs by significantly reducing the number of components in the data ecosystem, a 70% reduction in time to deliver newer integrations onto their platform thanks to templatized ingestion framework and CI/CD support, and created user-friendly interfaces for the whole data journey — from data engineering and science to ML and business analytics. Jeganathan added that Freshworks would also soon be partnering with Databricks in the future for their Unity Catalog solution as well as for other custom support capabilities.


The day ended with Kunal taking stage once again to summarise the sessions, explaining how FAANG companies were the pioneers in showing the world how data and AI could disrupt industries, and how Databricks’ solution would help companies leverage that through its unified approach to data management: “It’s an open source project based on open standards that’s committed to bringing the best of data warehouse and the best of databases into a single bucket.”


If you would like to explore data lakehouse through Databricks and learn how to leverage your data for exponential scalability,


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