Snowflake Shovels On Platform Updates, Ushers In Data Cloud

Snowflake unleashed an avalanche of enhancements to its cloud data platform including an engineering tool called Snowpark, an expansion of Snowflake Data Marketplace, new data governance technology, and support for unstructured data.  Snowflake unleashed an avalanche of enhancements to its cloud data platform including an engineering tool called Snowpark, an expansion of Snowflake Data Marketplace, new data governance technology, and support for unstructured data.  These updates take Snowflake one step closer to bringing the Data Cloud to reality. The vendor introduced the concept of the Data Cloud over the summer. It’s an ecosystem of partners, customers, data providers and data service providers that can share data through the Snowflake Cloud Data Platform and, particularly, that platform’s Secure Data Sharing technology.  “The whole concept of the Data Cloud is to allow data not to be siloed, not to be bunkered, so that data can be effortlessly combined and joined and we can drive far greater and far faster insights [from the] data and then act on it,” said Snowflake CEO Frank Slootman during a press briefing. Snowflake provides data warehouse services using a cloud-based architecture offered through an as-a-service model. This allows enterprise customers to analyze data stored in a central repository using business intelligence tools or other analytics applications. Its platform supports the three largest public clouds — Amazon Web Services (AWS), Microsoft Azure, and Google Cloud — however, it also competes against these platforms. Also today, the cloud data platform provider announced its first-ever global Startup Challenge. Snowflake is inviting early-stage startups to build applications and products in its namesake Data Cloud. The vendor will choose three finalists to pitch their innovations to a live audience – either in-person or virtually – at the Snowflake Summit next year. The winner may receive up to a $250,000 investment from Snowflake.  Snowflake also unwrapped a new engineering service called Snowpark that will allow developers to program data in their languages of choice and then execute extract, load, and transform (ELT) and extract, transform, and load (ETL) data modeling, data preparation, and analytics on Snowflake. It features native support for Java, Scala, and Python. By bringing more data pipelines into its Snowflake’s platform, Snowpark offers users a single platform for building data exchanges to easily share governed data and simplify an organization’s IT architecture.  Snowpark’s technology sounds similar to Birst, a cloud-based business intelligence (BI) vendor that Snowflake became acquainted with through its partnership with Infor – which acquired Birst in 2017. However, Snowflake executives declined to answer a question about how Birst fits into the new product.  Snowpark is currently in private preview. The company expanded Snowflake Data Marketplace, its third-party data sets hosting platform that can be accessed through Snowflake accounts, with new data service providers to make it easier for customers to “unlock, discover, and access data,” Kleinerman said.  Data sharing technology isn’t confined to a single box of sharing data sets, raw transactions, or item level data. For example, Kleinerman said there are many use cases where service providers offer customers endpoint business logics via a data powered experience that can be made available to others without having to share the actual data. The data services update now allows users to create live, bi-directional access to data sets for a service provider to deliver endpoint business logics such as risk assessments or behavioral scoring.  The marketplace already hosts over 100 market providers – 50% of which were signed in the last four months – and the company is “obsessed” with bringing additional content providers into its embrace, Kleinerman added.  Snowflake announced enhanced object tagging capabilities that will enable customers to associate name value pairs to any object in Snowflake. According to the vendor, the updated feature can be used for metadata management, classification, and annotation, but also use cases for resource allocation and tracking.  “This framework of tagging objects is completely changing the dynamics of how a user driven overlay of metadata can exist over every single object in Snowflake,” Kleinerman said.  In June, Snowflake announced Dynamic Data Masking as a way for customers to create a policy for a column to conditionally redact or partially redact the visibility of data. Complimentary to that policy, Snowflake announced a row access policy that can conditionally display or hide  a row depending on whose querying. IT affords security administrators the ability to create policies for restricting returned result sets across all workloads. This feature is expected to be in private preview later this year. And finally, alongside structured and semi-structured data, Snowflake will soon support unstructured data such as audio, video, pdfs, and imaging data. Unstructured data support is currently in private preview.  The Cloud data platform unicorn shot to meteoric fame this year when it became the largest-ever initial public offering (IPO) for a software company. The company’s current valuation sits at $77 billion and underscores enterprises’ desire for a highly scalable, centralized, and tailor-made platform for emerging workloads.  “Snowflake took the cloud playbook, rewrote it and won,” said Clumio CEO Poojan Kumar in a previous interview. Clumio provides cloud-based enterprise backup services, and Kumar is a self-described “strong admirer” of Snowflake. However, Snowflake’s story is just beginning, and a happy ending hinges on the company’s ability to materialize its valuation and grow its market share. But stealing shares from the on-premises data warehouse vendors won’t be enough – it must tap further into the cloud data market and create a new opportunity separate itself from Amazon, Google, Microsoft. Snowflake CEO Frank Slootman sees a path forward by changing the way organizations think about monetizing data. “We’re envisioning a marketplace where parties freely transact gain access and provide access to data,” he explained. “This will become a gigantic industry unto itself, but obviously you need to have very powerful both scale and architectural underpinnings to be able to power something like this. There’s a lot of opportunity here for data to flow freely between parties and for these parties to be able to monetize it as a business in the process.”