Alteryx and Snowflake, the end-to-end platform for the data lifecycle

AlteryxCloud ExperienceSnowflake

In our previous blog we addressed some of the key data management problems that immobilize organizations. The biggest issue is a data architecture problem. Data silos exist within different departments because organizations use many different apps and storage systems that don’t communicate or share data. This makes it almost impossible to perform data analysis or make global reports for an organization or even just a department.

Another impediment is the inability to handle large volumes of data, especially in cases where organizations try to deal with big data, querying it becomes a time-consuming and resource-intensive task.

And then there’s the inability to address and support as many use cases as possible within the organization. Data architecture within organizations is often build for a specific case, this makes it very inflexible and resource-intensive to adapt to new cases. To conclude the longlist of showstoppers, we see that data still inherently means high exploitation costs.

Most of these problems can be solved with a migration to data platform components that can truly integrate and offer end-to-end support for the data lifecycle.

One of these solutions is the partnership between Alteryx and Snowflake. Together they offer a full data architecture, data science and analytics platform that enables you to unify data and that has the flexibility to take on any data case.

Let’s look at the main functionalities of this new platform.

In-Database

Pushdown processing provides an effortless way to analyze large datasets. This integration offers significant perfomance benefits when compared to standard building blocks.

When analytic processes are powered by Snowflake & Alteryx APA, users are given unprecedented choice on not only how data is uploaded, stored, managed, and analyzed (whether the preference is ETL or ELT), but also where it’s processed. In- Database analytic building blocks in Alteryx make it easy to supercharge analytic throughput and outcomes by unlocking the near-unlimited scale, concurrency, and performance of the Snowflake Data Cloud. This eliminates the need to load data queried from Snowflake into Alteryx, giving a significant performance boost. Additionally, you can blend data originating from sources other than Snowflake with Snowflake data in an Alteryx workflow and push it to Snowflake using the native Alteryx to Snowflake Bulk Data Loader.

Typically, you would use SQL or Python to perform transformations on your data in Snowflake. These Alteryx building blocks allow you to visualize every step of the process and easily add, adapt or remove any transformations as needed.

In-database workflow Alteryx

Read/write

You can’t just process data with Alteryx, users can also read and write data to Snowflake databases. The simplest  way to connect to Snowflake data is using the input and output tools. The only prerequisite is to set up and ODBC connection to a specific Snowflake web server. When the ODBC is configured and Snowflake credentials are provided users can read, write, create, and delete data tables.

The Snowflake/Alteryx integration gives users more visibility and access to their data.

Bulk loader

Alteryx has a bulk loader for moving large datasets into the Snowflake data platform. As organizations increase their data footprint within Snowflake Data Cloud, Alteryx’ APA makes it simple to send the datasets originating from other sources to Snowflake.

This native integration enables all data workers to increasingly receive the benefits of scalability, elasticity, and processing power for more of their data. This greatly simplifies the technology stack by minimizing the locations that data workers need to retrieve data from, as more data is served directly within Snowflake.

Snowflake Data Exchange

Alteryx connects easily to the Snowflake Data Exchange, making it easy to combine third-party data from the exchange with customer data. The Data platform offers a massive store supporting any data type, from simple data types to full texts, images, and geo-spatial data.

Conclusion

Snowflake and Alteryx integrate, to create an offering, that makes analytics fundamentally easier. The Alteryx Analytic Process Automation (APA) Platform combines with the Snowflake Data Cloud platform to offer a flexible and secure backend that powers enterprise productivity.

Together, they create an elastic and secure cloud data platform with Snowflake Data Cloud powered by data preparation, analytics, no-code data science, process automation, AutoML, and AI from Alteryx.

Want to see Alteryx and Snowflake in action? Don’t hesitate to contact us. We will be happy to give a demo or brainstorm on your case with you!

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