How Snowflake’s Founders Architected the Rise of the Data Cloud
Nov 17, 2020 | 5 Min Read
Data Cloud Summit 2020, Snowflake News
According to Gartner, the public cloud services market continues to grow, largely due to the data demands of modern applications and workloads. And data is one of the leading factors in this transition. In recent years, organizations have struggled with processing big data, sets of data large enough to overwhelm commercially available computing systems.
For a long time, the only real solution was data warehousing services. These services relied on specialized computer hardware to increase the scale of data processing. But these systems had major drawbacks in terms of their extremely high cost and performance constraints. Increasing scale this way wasn’t feasible for many or even most companies. With demand continuing to explode, the world desperately needed a more democratic solution for big data delivery.
A new book, The Rise of the Data Cloud, looks at how that problem can be solved over a few short years. As the founders of Snowflake came together to design a better big data solution, they built an entirely new class of cloud computing in the process.
Freeing Data from the Bonds of Outdated Thinking
For data to fulfill its tremendous potential, it first needed to be liberated from the limitations of legacy data warehouse approaches. In the right cloud-based system, any and all forms of data could be taken in, transformed, and then integrated, managed, analyzed, and, most of all, acted upon.
Snowflake’s founders call this unique approach the Data Cloud. Their highly efficient design ensures there is only one version of any data collection: one version of the truth. Inside the Data Cloud, organizations have a single unified view of data so they can easily discover and securely share governed data, and execute diverse analytics workloads. This is the basis for a platform that can make vast quantities of information instantly available to anyone with permission to use it.
Greater efficiency and accuracy
Snowflake’s platform enables enterprises to fully automate core business processes. Data that comes from transactions, IoT devices, the internet, and internal operations triggers actions programmatically. This takes humans out of the loop, which makes processes more efficient, massively scalable, and less prone to error.
Expanded access with zero redundancy
Another critical benefit of the Data Cloud comes from its data sharing capabilities. Snowflake’s customers can eliminate data silos and gain the benefit of the data network effect across all business units, divisions, and ecosystem partners, and even across anonymized third-party data sets. The data network effect is the compounding benefits achieved by sharing data: combining diverse types of data from a variety of sources and making it available to others—one to one, one to many, or many to many.
The Power to Transform Business and Society
Delivering data with volume, variety, and velocity makes it possible to understand on a much deeper level how global causes and effects work. These benefits are what’s driving the creation of an ecosystem where businesses, governments, social enterprises, and individuals succeed or fail based in large part on their ability to extract value from data. Thanks to the cloud, businesses can scale up their efforts to capture, process, and draw insights from all that data. At the same time, the performance of data analytics engines has improved to the point where deriving insights in seconds is possible.
In early 2020, after it became clear that an outbreak of the deadly COVID-19 coronavirus could become a true pandemic, governments, medical scientists, and healthcare institutions worldwide began marshaling their resources in response. One of the essential weapons in their arsenal was data.
Medical researchers from around the world began sharing data to accelerate work on vaccines. Drawing data from numerous sources, a team of data scientists at Johns Hopkins University published a visualization showing the spread of the disease globally in real time. Starschema, a technology services company, picked up some of the same data Johns Hopkins used, melded it with other data sets, and made the entire collection available as its COVID-19 incidence data set in Snowflake Data Marketplace. There, businesses could use the data to help them develop contingency planning and analyze supply chains for possible vulnerabilities; public health authorities could investigate which strains of SARS-CoV-2, the virus that causes the COVID-19 disease, carry a higher risk; and governments could use real-time information about the spread of the disease to plan their responses.
The Future of the Data Cloud
The response to the coronavirus illustrates the power of the Data Cloud’s ability to enable data network effects going forward. The more data that is shared and the more individuals and organizations it is shared with, the more value is created for everyone involved.
This is how the power of the cloud can be applied to big data in a truly transformational way. As a CIO.com opinion piece explains, regardless of the region, industry, or sector, digital transformation is likely to fall short unless it is based on a solid foundation of data transformation.