Engine Works
Under the hood of Alteryx: tips, tricks and how-tos.
So you’ve just purchased Alteryx Auto Insights (AAI), and you don’t know where to start. Or maybe you’ve used AAI for a while now but aren’t sure what good practice for managing AAI looks like. Here’s where you can start – the foundations for scaling AAI within your organization:
Here are some key steps to ensure you're set up for success with AAI:
1. Single Sign-On (SSO) Set-Up: Setting up SSO in AAI ensures data access controls are aligned with your organization’s policies. When you have SSO set up, this helps reduce the risk of unauthorized access into your instance of AAI and also provides users with a more seamless login experience. For more information on setting up SSO in AAI for your organization, refer to this help article.
2. Automated Data Pipeline: Setting up a schedule for automated data refreshes in AAI from your data source is essential in distributing insights at scale. This means whenever users access AAI or receive mission summary emails, they get access to accurate and up-to-date data and insights without the need for an analyst to manually refresh data each time. Here’s a help article on how you can set up automated data refresh.
3. Dataset Repository: A repository for use cases and datasets provides traceability and accountability of use cases and who owns them. It acts as a source of truth for AAI datasets, ensuring that everyone has access to the same information and not working in silos.
It typically sits in a central location (e.g., Sharepoint site, link on the intranet) for users to easily access and reference. So whenever a user has a new use case, they can first reference the dataset repository for any relevant datasets they can leverage. This helps reduce potential time wasted creating duplicate datasets due to users being unaware the data they need already exists in AAI.
The repository may also include links to a data dictionary to provide business users with context on what each data field means. Here's an example of the information you may want to include in your dataset repository:
4. Data Security Best Practices: It’s important to design best practices for managing data for AAI that align with your organization’s IT policies. Users can then reference these best practices and ensure that when they’re creating datasets for AAI, the relevant data controls are embedded in their design and process. Data security best practices can include:
- Using only data sources approved by your organization
- Validating data before sharing it with the business
- Processes that ensure personal identifiable information (PII) is not uploaded
- Following best practices on designing groups for access permissions in AAI
5. User Provisioning SOP: By leveraging your organization's IT’s standard license provisioning process, you can design standard operating procedures (SOP) for provisioning licenses to users across your organization. Following the SOP will help you keep an audit trail of access provisioning. It also standardizes procedures, so key person risk is reduced if only the initial organization had access to this knowledge. The SOP may include:
- AAI as part of your organization’s application selection
- Training up IT to provision AAI licenses
- Establishing a triaging process within your organization for users to raise inquiries
- Setting up a process for requesting dataset access which can be supported by the dataset repository
6. Business reviews: Setting up a quarterly Executive Business Review (EBR) is a great opportunity to showcase the value achieved with AAI. When users share success stories, it creates opportunities for other teams to get a better idea of where AAI can add value to their teams and stakeholders. This is when new use cases arise, further increasing AAI adoption and value across your organization and, ultimately, increasing your ROI from the tool.
These steps form the necessary foundations for you to be successful at getting started with and scaling AAI across your organization. For more information about best practices for organization admins, check out this help article.
The next step is to productionize a use case to get the most out of your data in AAI through for your business to make better-informed decisions. Here’s a help article on how you can achieve that.
