Navdeep Manaktala, Head – Business Development, Amazon Internet Services in conversation with Shipra Malhotra, Executive Editor, dynamicCIO deep dives into the company’s enterprise strategy for India. He explains how every conversation that business teams strike with prospective customers today revolves around building their complete data strategy rather than just selling cloud.
- What is the mainstay of AWS’s enterprise strategy in India?
Every discussion that we have with enterprises today involves a data discussion that has a thread around a data lake. When I say data, it includes databases, big data analytics and AI/ML. If you see today data is very critical for organizations. That involves three things – to be able to capture all the data that’s being generated across the organization, to be able to process all that data meaningfully and to be able to derive insights from that data to take appropriate actions. And, that’s the underlying premise of the data lake strategy that we introduced around one and half years back. Today, this key innovation around our data lake offering forms the mainstay of our enterprise strategy.
- Can you explain your data lake offering and what does it really mean for the enterprise customers?
Data lake is a concept and not one single solution and the whole driver behind it is to address the biggest challenges that enterprises face with their data today. One is that they are not able to capture all the data that is being generated across the organization. Even what they capture exists in silos and they are not able to meaningfully access that data, get a comprehensive view of it and then take appropriate actions using it. So, what we are saying to organizations with our data lake is that we will help you capture all the data that is being generated across the organization – social media, ERP data, POS data, data coming from mobile app or website and aggregate all of this data in one central repository, which is S3, our storage service. Thus, the data lake gives you immense power because it lets you aggregate all the data in a single place, which gives a central view of your data and becomes the single source of truth.
And, once you have put all of this together in one place, then you can process the data the way you want to with the tools you want to. If you want to do ad hoc querying you can use Athena. For large scale processing of structured data you can use RedShift. To convert unstructured data to structured data you can use a service called EMR, which does Hadoop. If you want to visualize the data you can use QuickSight. Finally, the icing on the cake is that with all this data sitting in one place you can finally do a lot more with AI/ML and bring in all that intelligence. Hence, it brings all our services together. While we are going to the customer with 125 services we also offer them a holistic approach of where they can bring across their data in one place.
The proposition is extremely powerful and organizations can get it set up very quickly and efficiently and derive tremendous insights from it. With data as the new oil, the data lake is the refinery. We see this as the foundation for a more data driven enterprise. In India we have organizations like Aditya Birla Group, Vistara and Jubilant Foods building their data lake with AWS.
- Your rivals, Microsoft Azure, Google Cloud, IBM Cloud and Oracle Cloud may not be very close to AWS in the start-up environment but they are now fully engaged and aiming to make headway against AWS in the segment that AWS isn’t that strong in – the large enterprises. What is your take on that?
Let me give you a few examples to dispel the notion that AWS isn’t that strong in the enterprise segment. Almost all of the digital workloads of Vistara are built on AWS – right from analytics, website and mobile app to customer engagement. Another example is HDFC Life. The insurance company’s data platform, which optimizes customer engagement and on-boarding experience, aggregates all the touch-points and gives a single view of the customer, is built on AWS. And, then they have a data lake with all that data that they can run multiple analytics on. Then there is L&T Infotech, where SAP S4 HANA is in production on AWS and Kent RO, where the whole CRM platform is built on AWS. We have Tata Motors that has moved 90 of its digital properties to the AWS cloud, including its telematics application. From the financial services industry, Bajaj Capital, Bajaj Finserv, Aditya Birla Capital and Edelweiss are just some examples of AWS customers. Another great example is the Media & Entertainment (ME) industry where Hot Star, Sony, Tata Sky and Sun TV, all have their OTT platforms built on AWS. In fact, Hot Star is entirely built on AWS and they are using AWS not only for the OTT platform but also for analytics. Some of them have started to use us for AI/ML as well as for our Transcoding service, Elemental.
- According to you, what really differentiates AWS and puts it ahead of its competitors?
First would be the whole culture and pace of innovation that’s reflected in the fact that though we have become this scale and size we are still innovating faster today than we were the year before. And, that’s because of the way we are organized. The teams that develop and deliver services are pretty autonomous. It’s typically the concept of two pizza teams. Very small and flexible teams, empowered to work directly with the customer, get feedback and launch services. So, you will not have a whole army today working on a particular service. Almost 90% of the roadmap today is dependent on what customers are telling us are their requirements vs. our view of the world. Secondly, we are extremely long-term focused. Nothing that we do is from a short-term perspective. When we build relationships with customers and partners, the perspective is that the relationship should outlast all of us. Everything that we do is driven from a long-term perspective.
- When you say 90% of AWS’ roadmap today is dependent on what customers are saying and asking, can you give a few examples?
We have some great examples of services that were initially not on our roadmap but we heard about them multiple times from our customers and thus decided to build them. On such example is RedShift, which is a fully managed petabyte scale data warehouse at one-tenth the cost of the traditional warehouses. So, how did we go about it? It’s not that one fine day we said that data warehouse is interesting and let’s get into it. It was because customers over a period of time were telling us that they need to be able to analyze large quantum of data, which they cannot do in databases, and hence need a DW, which can cater to petabyte scale of data. After we launched RedShift and for a few years till we launched Aurora it was our fastest growing service.
Another example is Aurora, which is the fastest growing service in AWS history. Again, this service about around three years ago because customers had been asking us for a while to help them get out of the commercial databases, which they find to be expensive and restrictive because of licensing and other issues and move to databases that can take away all that pain.