KNIME improves the democratization of data science through collaboration with Snowflake

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KNIME, which offers a no-code/low-code toolset that allows – so to speak – square data sets to fit into circular storage holes, announced a new partnership with cloud data lake provider Snowflake designed to democratize access to data analytics. about different line-of-business roles within a company.

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

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

“Snowflake seems to be starring lately,” ALTR CEO Dave Sikora told VentureBeat in a separate conversation.

Data centralization an important trend

As data warehouses and data lakes become more common in the current trend for enterprises to centralize their data storage, there is a growing opportunity for organizations to leverage the value 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 like KNIME help fill this gap and democratize 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 is used by 250,000 community members and 4,000 commercial organizations in 60 countries. It connects Snowflake with thousands of other features, and there is no cost to use it. The same capabilities elsewhere would require multiple tools or cost thousands of dollars per user, Treichler said. KNIME’s business model is based on business services it sells alongside its main software platform.

Data creates business value

Understanding data is critical to creating business value. With the global data analytics market worth more than $200 billion, it is imperative that as many people as possible in various roles, departments and industries have access to analytics in their day-to-day work for overall better productivity, Treichler said.

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

How do users facilitate the integration of these two tools?

“In KNIME language, we have a ‘node’, a separate 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 you don’t have to code connections and you have instant access to everything you have in Snowflake in a visual environment. You can explore your data, prepare and combine 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 or consume.”

Product manager Tobias Koetter of KNIME wrote a blog post on Medium in which these processes are discussed.

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

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

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

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