Alteryx Analytics Cloud is an end-to-end enterprise-class data and analytics platform supporting the entire data and analytics lifecycle from ingestion, data preparation, and data enrichment to productionizing and driving business outcomes through business intelligence or predictive modeling. And now, organizations that have chosen Google Cloud as their cloud provider to help them in their digital transformation can leverage Alteryx Analytics Cloud with seamless integrations.
You can learn more about the available applications and features of Alteryx Analytics Cloud here, but this blog will focus on the integration of Alteryx Analytics Cloud and Google Cloud for customers looking to understand how this will complement their technology stack.
Deployment Overview
Data Connectivity
Alteryx Analytics Cloud supports several Google Cloud data sources, empowering users with robust data and analytic tooling to uncover insights and drive business outcomes. This includes foundational data sources such as Google Cloud SQL, and files stored on Google Cloud Storage (GCS). Many users still need to work with flat files, and with Alteryx Analytics Cloud, users can work, transform, and process Google Sheets to perform analytics and produce summary reports. Additionally, Alteryx Analytics Cloud works with Google’s proprietary Cloud Data Warehouse BigQuery, giving users not only the ability to read and write data, but Alteryx Analytics Cloud can also use “pushdown processing” to execute transformations natively within BigQuery.
Workspaces and workspace storage
Alteryx Analytics Cloud is a multi-tenant environment that uses “Workspaces” to provide separation of projects, users, data assets, reports, and predictive models. These Workspaces can be defined by each organization as they see fit, with some common examples being by department, by workstream, or by environment stage (Dev, Test, Prod).
Each Workspace has its own “Workspace Storage,” which is used to store uploaded files, sample data, or data assets you’ve created that you’d like to share with other users across the platform. This Workspace storage is built on Google Cloud Storage (GCS). You can find more details on the GCS workspace storage setup here. When combined with BigQuery as a Cloud Data Warehouse, Alteryx Analytics Cloud can efficiently and quickly load data into the warehouse using GCS workspace storage as a staging location.
Security
Security is top of mind for all IT leaders, and Alteryx Analytics Cloud leverages industry-standard single sign-on (SSO) integration based on SAML 2.0 or OpenID Connect (OIDC). With a Google Cloud deployment, this SSO works by authenticating users to Google Cloud Identity, which is the standard for most organizations using Google Cloud. The process of configuring Single Sign-On is entirely self-service, following the documentation here. Each Workspace can define its own SSO integration and must explicitly “invite” users to be a member of the Workspace for extra security.
Users authenticated into the Workspace are assigned roles from within the platform, which grant privileges and application access.
Architecture
Alteryx Analytics Cloud features a flexible architecture, giving organizations choices in a deployment model that meets the needs of their business. Alteryx’s full SaaS model allows organizations to work with a cloud platform completely hosted by Alteryx, offering the simplest and fastest way to get up and running. For organizations that desire data samples, uploaded files, and data outputs back to Workspace Storage to all be kept in their Google Cloud environment, organizations can leverage Alteryx Analytics Cloud’s deployment with Private Data Storage (shown below). With this approach, Workspace Storage is a customer-owned Google Cloud Storage. In this configuration, a customer owned BigQuery environment can also be used for SQL “pushdown” processing and Dataproc can be leveraged for scalable execution using Spark.
For organizations who want more control with a desire that all data is processed within their Google Project or need special requirements to “privately” connect to other Google or On-Prem data sources, a Private Data Handling deployment model (shown below) is available. This architecture could be chosen to support data sovereignty or regulatory requirements.
In this approach, all job execution, data processing, and data connectivity occur within the customer-owned Google Project defined on the Workspace. Google Cloud Storage is used for Workspace Storage, and Google Kubernetes Engine (GKE) is used for efficient, scalable, and resilient orchestration of jobs. Optionally, a customer owned Dataproc can still be used to efficiently process large data volumes using Spark, and BigQuery pushdown processing is available for natively processing data within the customer’s BigQuery environment.
Conclusion
Alteryx Analytics Cloud provides seamless integration into Google Cloud for organizations that desire to optimize their data and analytics processing with a Google Cloud environment. If you’d like to learn more about how you can take advantage of these integrations, please reach out to your Alteryx sales representative.