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Alteryx
Alteryx

As a part of our continued enhancements to the Alteryx platform, we recently announced in-database capabilities with Snowflake, an innovative data warehouse re-built and re-invented for the cloud. To learn more about the offering that is already making several joint customers excited, I reached out to Saqib Mustafa, Director of Alliance Marketing with Snowflake, and Alex Patten, Product Manager with Alteryx, to discuss the benefits of using Alteryx and Snowflake together, as well as the technical “how to” of connecting the two. Below is a summary of the respective conversations:

 

Saqib Mustafa
The Power of Alteryx + Snowflake:

 

More organizations are empowering large groups of users with data analytics to answer questions and produce performance-based business insights. As technologies like IoT and mobile become more prevalent, vast amounts of new data - in a host of formats - is available. The demand for data from analysts and executives is only growing exponentially as more challenging questions are being asked.

 

Given the growth in the demand and consumption of data, difficulties often arise when it comes to creating repeatable and easy-to-use analytics workflows. Legacy technologies aren’t helping solve the problem. In fact, many organizations continue struggling with a proliferation of data marts and extracts.

Together, Snowflake and Alteryx remove analytic barriers by helping you to:

 

  1. Analyze all your data in one system: Snowflake is the data warehouse built for the cloud that allows you to easily analyze diverse datasets. Alteryx allows you to blend, prep, and analyze multiple datasets from various sources and then bring the data back into Snowflake in the format that meets your organization’s unique needs.
  2. Deliver scalable performance for advanced analytics: Snowflake provides distinct performance advantages compared to other data warehouse and big data solutions. With the new In-DB connector for Snowflake in Alteryx, you can leverage this performance by running advanced predictive and spatial analytics, in-database, to analyze large sets of data quickly.
  3. Provide concurrency for self-service analytics: Snowflake provides high concurrency, enabling organizations to extend advanced analytics throughout the entire organization. Alteryx makes running advanced analytics a fast and easy process with its drag-and-drop interface.   

 

Alex Patten
Integrating Alteryx + Snowflake:

 

With the seamless integration between Alteryx and Snowflake, you can now access data stored in Snowflake via the standard input and output tools, as well as the In-DB tools. To read and write data using the standard input and output tools, select the appropriate DSN from these tools:

 

 

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Via the Input tool you can read in data from tables stored in Snowflake.  Once the data is ingested in memory in Alteryx, you can blend, prepare, and cleanse the data using the drag-and-drop Alteryx interface. Once done, you can write that data back to Snowflake in the form of new tables or as updates to existing tables.

 

The new 11.5 release of Alteryx also provides support for Snowflake In-DB, which means that the data processing will be pushed down into Snowflake. This greatly increases workflow performance by eliminating the need to transfer massive amounts of data into and out of Alteryx. This functionality can be accessed via the Connect In-DB Tool:

 

 

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It goes without saying, the Alteryx and Snowflake partnership provides a scalable, performance-based solution that keeps business data and analytics readily accessible, and insights flowing across the organization.

Raman Kaler
Manager, Alliance and Product Marketing

Raman is an Alliance and Product Marketing Manager at Alteryx, where she focuses on defining strategy and executing programs for joint marketing efforts with key strategic partners. She currently focuses on partner marketing efforts with Tableau, Amazon Web Services, Salesforce and Cloudera. Raman has proven success in creating strategic marketing and business development programs that support pipeline growth.

Raman is an Alliance and Product Marketing Manager at Alteryx, where she focuses on defining strategy and executing programs for joint marketing efforts with key strategic partners. She currently focuses on partner marketing efforts with Tableau, Amazon Web Services, Salesforce and Cloudera. Raman has proven success in creating strategic marketing and business development programs that support pipeline growth.

Comments
gerconn
Meteor

Snowflake and Greenplum are not widely used compared to DB2. What is the criteria for selection when prioritising In-Db data sources?

 

https://db-engines.com/en/ranking

 

 

Alteryx
Alteryx

Hi @gerconn,

 

There are many factors that go into what we support In-DB, but in the case of Snowflake, we looked at market trends and got feedback from our customers around which data sources they're evaluating for their data storage needs. We ran across Snowflake quite a bit while doing this research and we think Snowflake complements our platform well. So, we partnered with Snowflake and worked with them to provide seamless integration in hopes of staying ahead of the market needs. We already see Snowflake being widely used across our customer base and we think that will continue to grow.

 

Best,

Alex

fpinchon
Atom

You guys might want to work with Snowflake on updating their documentation, because you are not mentioned here:

https://docs.snowflake.net/manuals/user-guide/ecosystem.html 

 

Which is a shame...