I had given an overview of the problem space that Snowflake is trying to address in part 1 of this series. In part 2, I will be diving deeper into the two offerings: data platform and cloud data.
To recap,
Cloud Data platform: It is primarily to address a company's data warehousing and data lake needs.
Cloud Data Marketplace: This addresses a company's need to share data with the outside world or procure data from outside world.
Cloud data marketplace
Though the Data platform is Snowflake's main offering, I would like cover the data marketplace first because it is more exciting than data platform. Cloud adoption is in its very early stages of rapid growth.
Below is a screengrab from their recent investor presentation that shows the actual increase in data exchanges in Snowflake’s data cloud.
Reasons why I like the data marketplace opportunity
New Category
Imagine Netflix in the age of mailbox DVDs. Or more recently, Buy Now Pay Later(BNPL) in the age of credit cards. Data marketplace is a new category that is going through a tornado market. Currently, both the producer and the consumer have to spend a lot of time and effort to prepare their data for sharing and to consume the data. There is friction at both ends of the data-sharing pipeline.
Breaking down barriers- Removing friction
I like businesses that remove friction and make it easier for their customers to do something. Imagine you want to share a file with your friend. A few years back you might have used a flash drive to transfer files to your friend. You have a MacBook while your friend has a Windows OS. your friend realizes that the flash drive is in USB C but his system has a USB type-A slot. So he buys an adapter and once he plugs in he realizes that the flash drive has been formatted in a different file format.
Now imagine Google docs, you upload the file to google docs, click share and your friend receives a link to access the file instantly. You can control which files you want to give access to, what type of access (read-only, read + edit access), how long your friend can have access, etc. Do you see how Google docs have removed the friction in file-sharing?
Now Snowflake's data marketplace does the same thing for enterprises. when it comes to enterprises sharing information, there are more complexities involved with governance.
Snowflake makes it easier to plug and play for enterprises to use data from other companies.
Another benefit of snowflake cloud data will be the governance/management. With a click of a button, organizations can control
What they share?
With whom they share?
How much do they want to share?
How long they wish to share?
What access they want to?
Collaborate (you and your friend) editing the google doc at the same time. This will be more prominent in a decentralized world where ledgers have synced with remaining people on the blockchain.
Traditional data sharing vs Cloud data marketplace
Exploding data exchanges between companies
The rate of data exchanges between companies is spreading like wildfire. below is a screengrab from their snowflake's presentation. As more and more companies start using Artificial intelligence, machine learning, the necessity to augment your AI/ML models with more and more data (eventually external, readily available data) will only increase.
Network effects
Cloud data will bring significant network effects to the snowflake platform. it will be a 2 sided network effect as more and more data producers are on-boarded to the platform, chief data officers from enterprises will prefer snowflake data marketplace that will have a larger catalog of data sets than its competitor (why shop at a convenience store when a supermarket is nearby?)
Stickiness -switching cost
Snowflake's cloud data first-mover advantage will create high switching costs for organizations. Once enterprises have invested time and capital in building data pipelines on the cloud data, they will be reluctant to switch over to another competitor because they will have to spend time and money again to build the data pipelines again. As they start building more and more data pipelines
Monetize your data asset - new revenue opportunity
Before the data marketplace, enterprises had very limited opportunities to monetize their data assets. This brings in an additional revenue opportunity for companies and these opportunities didn't exist before cloud data. There are many data-hungry organizations such as ZoomInfo. Data-centric companies and business models will become more prominent in the coming days.
Now let us look at the Data platform
We looked at the problems that the data platform addresses in great detail in part 1 of this series.
Let's look at some customer case studies
Square: Addressing scalability
Challenges:
The Rapid increase in data volume led to system outages and time-consuming maintenance of their existing data infrastructure
Only one team was allowed to query and only once a month due to resource contention.
Solution:
Snowflake's multi-cluster shared data architecture brought near-infinite scalability to square.
Snowflake allowed Square analysts to build more models to query more data more often to help identify bad actors, detect attack vectors and prevent fraud.
Snowflake has been one of the only tools powerful enough to correlate all of the data and help us identify difficult-to-find fraud that may be occurring.”
—RANDY WIGGINTON, Senior Director, Platform Infrastructure Engineering, Square
Square is also moving closer to self-service data governance and collaboration.
Square case study1
Seismic - Addressing performance
Seismic is a sales enablement SaaS company and it used snowflake to improve its query performance by 1000x.
Snowflake replaced hundred of SQL databases and reduced infrastructure maintenance by 75%.
Queries on snowflake took only 5 seconds whereas the same queries took 83 minutes on their earlier infrastructure.
Snowflake’s Growth
The shift from on-premise software to cloud-first, cloud-only is already in full force. The same shift is happening and is expected to accelerate in the near future for the move from on-premise data warehousing solutions to cloud data platforms.
IDC report estimates that, by 2025, 49% of data will be stored in the cloud. The same report also says that more data will be created in the next 3 years than the data that was created in the last 30 years.
If the amount of data generated is going to increase rapidly, then the demand for storage and compute required to store and process the data will also increase. One important call out here is Snowflake's pricing strategy. Snowflake charges its customers based on their usage or consumption.
This is evident from their Net revenue retention, where existing customers have significantly increased their consumption (data hungry!)
Snowflake's Q1 investor presentation
Targeting Verticals like Financial Services and Advertising
The recent Snowflake events have two traits
specific to verticals like Financial Services, Advertising, Media
Developer focused to encourage developers to build their data apps on Snowflake
Going after customers in industries such as financial services and advertising makes sense because these customers are more ready to adopt cloud data than some of the other industries. Trends such as open banking, growth of fintech and the increase in collaboration between the traditional banks and fin techs have forced the players in the financial services industry to embrace cloud data. According to a Deloitte study, between 2016 to 2018 there was a threefold increase in the number of financial services organizations adopting cloud technology.
Financials
Below are the highlights from Snowflake's Q2 results.
Snowflake's product revenue has been growing steadily. The number of customers adopting snowflake for their data warehousing needs has also been steadily increasing and the number of customers with $1million in product revenue has increased 107% YOY.
Net Revenue Retention: 169%
Net revenue retention is the percentage of recurring revenue that the company can retain from its existing customers. The net revenue retention of 169% is another good sign that existing customer are increasing their usage of snowflake's products.
Rule of 40:
Rule of 40 is another common metric that analysts use for SaaS companies.
Rule of 40 = Growth% + Profit%
Snowflake's growth % is 121% and Free Cash Flow % is -28% which puts Snowflake's rule of 40 at 93% , which is among the top 5.
Risks:
In the Cloud Data platform offering, Databricks is the main competitor for Snowflake. Databricks was the first to bring the lakehouse concept to the market.
In the cloud data marketplace, Databricks has an open-source approach to enable sharing of data between data producers and consumers.
Currently, Snowflake's data marketplace seems to be onboarding data vendors (producers) at a faster rate than other Databrick's delta sharing platform.
Other cloud providers:
Snowflake could also face competition from other cloud players like AWS, Google Cloud Platform and Microsoft's Azure. Look out for product updates from the likes of AWS to see if Snowflake’s advantage is challenged in the future.
Conclusion
Snowflake is establishing itself as the infrastructure on which companies can build their data analytics, Artificial Intelligence, and Machine learning capabilities. At the core of these capabilities will be "quality data" and faster access to data within the organization (eliminating data silos) and outside the organization.
As I mentioned in part 1, think of snowflake as a software infrastructure company that is building
Elevators with a company that makes it easier to DISCOVER and ACCESS data spread across multiple floors - eliminating data silos or unlocking the value in hidden data.
Highways between/among the companies that make it easier to SHARE data with the outside world and monetize the data.
Snowflake has strong tail winds - rapid increase in data volume, data velocity and data variety. Organizations and business models are also becoming more data-centric.