Cutting-edge technology company lowers cost by 38% while increasing customer base by 10x by integrating and unifying data in the AI Data Cloud

Speaker 1

[0:04]

I am Himanshu Shrotri. I work as Vice President of Engineering at Graas. So at Graas we are building a cutting-edge data platform that helps our e-commerce customers to unlock the true potential of their data. We integrate this data, we push it into a unified data warehouse, which acts as a single source of truth. And for that we are using cutting-edge technologies like Snowflake for data warehousing, which are helping to generate growth recommendations. One of the reasons we chose Snowflake was it helps us scale with the number of customers that we are growing. We had a steep target of growing the number of customers from say, hundreds of customers, that time, to around five hundred plus customers today. It actually helped us integrate the data system that we had earlier and migrate it to Snowflake very seamlessly. At the same time, you know, managing the customer data in their own schemas, for example, for security purposes, the flexibility and configurations, everything which is related to metadata, configurability handled using SQL-like statements actually helped us to integrate seamlessly with Snowflake. So, we don't code for every customer, for example, right? We code once and the use of that code is done for all the customers seamlessly. And then Snowflake actually fit the bill because it provided us flexibility to configure compute separately and storage separately. It is probably only Snowflake, which provides billing visibility in two seconds, like every second they are billing. So it's not that you run a query for one second, but you're charged for a minute, right? You are charged for only a second.

Speaker 2 

[1:43]

Hi, I am Ajinkya Patil. I'm director of product here at Graas. The ease of access on Snowflake I would say is really good because for us - product managers as well as product analysts - we require access to the data in addition to all the data engineers that work with us. And for those who are not so technically savvy or someone who doesn't understand the languages as much, it is fairly easy for us to use Snowflake. Snowflake has helped us build a rules engine that is robust and scalable. We also created a feature store on top of Snowflake, which is helping our data science team come up with better algorithms and come up with better intelligence. 

Speaker 1

[2:27]

With Snowflake, in the past couple of years, we have scaled a lot, like the customer base has increased by 10x. Our data volumes have grown from certain terabytes to hundreds of terabytes today. The second part of it is something called a Snowflake Snowpipe Streaming. We started implementing it recently, for our workloads, where the data in the system has started ingesting within a few seconds, which has helped us deliver analytics dashboards in near real-time. The third part of it is the cost. So, we are operating at, you know, 38% lower cost than earlier, which has helped us scale further, multi-fold, with the same cost, essentially. If I have to talk about query performances, I have seen queries performing much better on Snowflake, and most of the queries are returning the data within milliseconds. 

Speaker 2

[3:26]

Our roadmap revolves mostly around two areas. One is helping customers get data from more data sources that are relevant to them and access that data easily. Second is generating intelligence on top of that data that helps them take actions quickly. Snowflake is at the center of both these areas. 

Speaker 1

[3:50]

So, currently we are serving over 250 customers across India and Southeast Asia region. The goal is for companies to expand the customer base in the same region, and also implement more features which will help customers take better decisions. So, we are working on certain use cases which are revolving around implementing GenAI techniques and also using Snowflake's out of box features such as Snowflake Arctic, and Cortex, to implement various AI/ML algorithms. 

Speaker 2

[4:24]

The experience using Snowflake has been amazing. It has helped us scale to hundreds of customers without getting into any scalability issues, while managing our costs effectively. It has also helped us product managers and product analysts get access to the data fairly easily and generate our requirements in a faster manner. 

Speaker 1

[4:46]

Snowflake has helped us scale effortlessly and with our customer base growing and the out of box features that Snowflake is providing, it is actually helping us deliver faster.