Data serves as an increasingly valuable and strategic asset for any organization. Data — in its multiple formats — is being generated and captured across systems in greater volumes and at increasing levels of granularity. And while the volume of data is accelerating, many government organizations are struggling with the double-sided threat of inefficient manual processes and the lack of skilled data resources. This is creating more demand for organizations to streamline their access to data and build a robust self-service analytics capability that can drive business outcomes.
Alteryx and Snowflake are leading technologies that address these two challenges. The Alteryx Analytic Process Automation (APA) Platform™ provides a unified, human-centered platform experience that automates access to data, analytics, data science, and process automation all in one end-to-end platform. Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance.
Snowflake’s cloud-native data platform, coupled with the Alteryx APA Platform, offers a scalable, governable analytics and data-centric process automation solution for the entire organization. Users with different skills and needs across the enterprise can work together —using hundreds of Alteryx automation building blocks with Snowflake’s Data Cloud — to bring data-driven projects of any size into production.
Outcomes With Seamless Sharing
Not only is this the easiest way to drive analytic and data science outcomes, but it also helps federal agencies support the public by delivering a single source of truth for data, along with the ability to generate insights quickly and easily for decisions related to federal policies and programs.
In-Database Advanced Analytics
With Alteryx, the Snowflake environment can benefit from a wide array of in-database advanced analytic capabilities and data science use cases. This extends the value of Snowflake’s rich and secure capabilities by opening the aperture of robust data science to an expanded class of data workers, including business analysts, domain experts, citizen data scientists, and traditional data scientists who may not have deep SQL coding skills. With in-database/pushdown capabilities, all types of government data workers can engage with large robust datasets within a no-code/low-code environment and execute their workflows transactions with speed.
Integration from the start
The integration between Alteryx and Snowflake takes place in in five key
- In-Database ─ The Alteryx In-Database tools inject SQL for execution in the Snowflake data platform.
- Read/Write ─ Alteryx can read data out of the Snowflake Data Cloud and write data in.
- Bulk Loader – Alteryx has a bulk loader for moving large datasets into the Snowflake Data Cloud.
- 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. Note, this is not actually a separate connector but instead functions with the standard read/write and in-database capabilities.
In a recent article posted on CDO Trends, Colleen Kapase, VP of Global Alliances, Snowflake, said, “Our partnership with Alteryx can help make scalable analytics and data science on Snowflake more accessible to citizen analysts across an organization, to help drive business outcomes,” and “as demand for analytics and data science on Snowflake increases, partnerships with organizations, such as Alteryx, help us serve customers globally and supports our mission of mobilizing the world’s data.”
Case in Point: From Manual Processes to Meaningful Insights
A government organization in Australia faced tedious manual processes in their efforts to utilize many sources of data to run analyses for anomaly detection. This meant that any meaningful analysis took months, seriously impacting the productivity of the data team of four who were already doing the work of 20 analysts.
They adopted the APA Platform and built up the strength of it by adding Snowflake to organize their disparate data. With the creation of a few macros, the required data in Snowflake was ingested into Alteryx for in-database processing. With Alteryx, the team was able to automate the heavy lifting of prepping, blending, and joining multiple data sources for analysis. With the data ready for analysis, the APA Platform enabled the team to conduct extensive analysis and create insights that could be shared directly into Tableau for visualization.
With automation and the right technology stack, this data team is operating in a self-service capacity that preserves valuable IT cycle and can be shared, repeated, and adapted to additional business challenges.
With Alteryx and Snowflake, government agencies now have a powerful, modern data solution to ultimately help them better accomplish their missions in support of the health, safety, and support of citizens through data-driven insights.
Read This Next.
Download the Best Practices for Using Alteryx with Snowflake guide to understand:
- How to supercharge your analytics workloads by unlocking the near-unlimited scale, concurrency, and performance of Snowflake with the Alteryx In-Database building blocks
- Where to use Alteryx In-Database building blocks in place of standard building blocks to optimize your analytic workloads
- Insights on developing your analytic workloads to take advantage of the unique capabilities of each platform