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KNIME, which offers a no-code/low-code toolset that enables – in a manner of speaking – square data sets to fit into round storage holes, announced a new partnership with cloud data lake provider Snowflake, designed to democratize access to data analytics across line-of-business roles inside an enterprise. 

Using KNIME, Snowflake customers can now use all the data stored in a Snowflake node — whether structured or unstructured — to create predictive machine-learning models in a low-code/no-code environment, Paul Treichler, VP of global partnerships at KNIME, told VentureBeat. Business users can access Snowflake data and build models without writing any code; however, data scientists and advanced users have the flexibility to also code in Python, R, or JavaScript through built-in integrations in KNIME if they choose, Treichler said.

This is significant news for users of Snowflake’s Data Cloud, which has more than 6,300 enterprise customers, including 506 of the Forbes Global 2000, and continues to grow rapidly. 

“Snowflake seems to be running the table lately,” CEO Dave Sikora of ALTR told VentureBeat in a separate conversation.

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Data centralization, a major trend

As data warehouses and data lakes become more and more commonplace in the current trend for enterprises to centralize their data stores, there is a growing opportunity for organizations to use the value that has been hidden in their data. However, not every team within an enterprise has developers or data scientists to unlock this value. Visual programming or low-/no-code tools such as KNIME help to fill this gap and democratize the access and use of the data locked in massive platforms like Snowflake, Treichler told VentureBeat. 

KNIME Analytics Platform is based on open-source code and used by 250,000 community members and 4,000 commercial organizations in 60 countries. It connects Snowflake with thousands of other capabilities, and there is no cost to use it. The same capabilities elsewhere would require multiple tools or come at a price point of thousands of dollars per user, Treichler said. KNIME’s business model relies on enterprise services that it sells above and beyond the main software platform.

Data creates business value

Understanding data is critical for creating business value. With the global data analytics market worth more than $200 billion, it’s necessary for as many people as possible across roles, departments, and industries to have access to analytics in their daily jobs for overall better productivity, Treichler said.

“Many of our customers rely on Snowflake to power virtually any data workload at scale, while utilizing KNIME to gain value from that data,” Treichler said.

How do users facilitate the integration of these two tools?

“In KNIME speak, we have a ‘node,’ which is an individual piece of functionality that can be dragged and dropped into a data process,” Treichler said. “This node contains the connectors between KNIME and Snowflake. This means that you don’t need to code any connections, and that you are immediately able to access anything you have in Snowflake in a visual environment. You can explore your data, prep and blend your data, use it to train a machine learning model, or create a web service, visualization, or data app for less technical team members to contribute to or consume.” 

KNIME Product Manager Tobias Koetter wrote a blogpost on Medium that discusses these processes. 

“There is a strong global ecosystem of consulting and implementation partners who have the domain knowledge, local capability, and technical ability with both KNIME and Snowflake to help teams take advantage of the full capabilities of these tools in a broader enterprise context,” Treichler said.

KNIME is flexible and extensible, giving data experts the freedom to work in their preferred environment. Users can build sophisticated analytic models in its low-code/no-code environment or script custom algorithms in a language of their choice with built-in integrations with R, Python, Java and others, Treichler said..

KNIME, headquartered in Zurich with offices in Austin, Texas, and Berlin, competes in a market that includes Alteryx, RapidMiner, Orange, R Studio, SAS and SPSS.

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