How to Improve Data Readiness for Tableau Cloud

How often have you heard, “Without good data, you won’t have good AI?” It sounds simple, but studies show that “ensuring scalable, reliable data” is one of the top analytics challenges organizations face according to the Salesforce State of Data and Analytics Report. This challenge has significant downstream effects. Organizations that cannot confidently confirm they have reliable data cannot confidently adopt AI or self-service capabilities. To scale responsibly around AI and self-service-driven capabilities, organizations need a better process to explore, improve, and validate the data sources that drive them.

This blog provides the tools to monitor your Tableau data sources more effectively and a framework to drive iterative improvements, so you can be more confident in your data.

The framework consists of four steps:

1. Monitor your data
2. Identify a meaningful objective
3. Create and promote data sources
4. Enable your users

Improving data confidence starts with a baseline understanding of your data. Consider one of your top-level Tableau Projects, and ask yourself:

• How many data sources are in that project?
• How do users distinguish trusted, governed sources from experimental ones?
• Is there supporting documentation to help new users understand the data?

If you can’t answer these questions, scaling for AI or self-service discovery may make you nervous. The first step to alleviate these concerns is to monitor and explore your data sources. Any Tableau Cloud Admin can do so by connecting the Data Source Manager Accelerator to your Tableau Cloud Site, and then sharing for other users to see.

Start by reviewing the “Know your data sources” section to see how users can interact with their data.

A published data source makes a single source of data accessible to permissioned users, enabling self-service and Tableau Pulse capabilities. Certified data sources go a step further, assuring users that the data has passed organizational governance standards and can be trusted. Embedded data sources, however, are embedded within a Tableau workbook, making them inaccessible for exploration outside of the dashboard through web-authoring or Tableau Pulse. Monitoring and managing your data assets along these categories will help you assess your readiness to embrace Tableau’s AI and self-service capabilities in your Tableau Sites.

Instead of overwhelming yourself by attempting to improve all of your data at once, focus on achieving short-term wins on meaningful objectives. To identify these use cases, take any potential initiative, a digital whiteboard, and answer the following questions for the initiative:

The initiatives you choose to focus on should confirm all of the above. It should impact relevant organizational goals, use data that can feasibly be brought into Tableau, and demonstrate that analytics can indeed drive meaningful progress. Once confirmed, you have a worthy use case to focus on. Create a designated Tableau Project and follow the next step to equip users with explorable data assets.

Learn more about creating value maps to help select meaningful objections on our website.

You’ve listed the necessary data sources for your initiative in step 2 above, now make sure they are available in your Tableau Site by referring to the Data Source Manager Accelerator. 

Here, all of your data sources are categorized as Certified, Published, or Embedded, as discussed in Step 1. Filter the Accelerator for your Tableau Project, and explore the following sections of the dashboard to learn more about your data.

Embedded Data Sources (bottom right)

On the bottom right, you see all your embedded data sources, sorted by repetitions. Remember, these data sources are embedded within dashboards, meaning they cannot be explored with Tableau Pulse or web-authoring. Review this section to:

1. Consider publishing highly-used embedded data sources to enable features and consistency
2. Redirect embedded dashboard connections to their Published/Certified equivalent, if it exists 

Published Data (bottom left)

On the bottom left, you see all your Published data sources, sorted by user activity. While these data sources enable enhanced Tableau features, they lack any indication of whether the data has passed governance checks and can be trusted. Review this section to:

1. Consider retiring unused data sources
2. Consider certifying highly-used Published data sources
3. For certification candidates, collaborate with data owners and experts to complete the certification checklist

Learn more about how to publish data sources on our website.

Certification Checklist (hover over the checklist on the dashboard)

The certification checklist is your organization’s process for vetting data sources, which ensures users understand why they can trust their data. This checklist typically includes a variety of checks to confirm accuracy of the data and the presence of supporting documentation. While we can’t directly monitor data accuracy with this Accelerator, we can track other variables to help data owners organize their certification efforts. Hover over the checklist on the dashboard to view the following six checklist items for each data source.

• Licensed Owner: Confirms the data owner is still a licensed Tableau user;
• Refreshed Last 30 days: Confirms the data source has been refreshed in the last month;
• Description: Confirms the data source description includes specific background about the data and guides users where to go with questions (format customizable by you);
• Data Source Type: Confirms the data comes from preferred sources and databases;
• Title Format: Confirms the title is legible without special characters;
• Accessed Last 90 days Confirms users still use the data;

Note: This is a starting point. Customize your checklist items by editing the “Score_” calculations in the Accelerator or adding new ones.

Once a data expert vouches for the accuracy of the data, the data owner can use this Accelerator to ensure the necessary supporting documentation is included. These combined checks, done inside and outside of this dashboard, will ensure data sources are ready to receive the Certification label in Tableau.

Certified Data (top)

At the top, you’ll find all data sources given the Certification label on Tableau Cloud, sorted by user activity and an icon confirming compliance with the checklist.

These are your prized data assets. They have been reviewed by a data expert to ensure accuracy, supplemented with supporting resources to address user questions, and have passed organizational governance standards to ensure trust and consistency. Review this section to:

1. Confirm data adoption
2. Ensure compliance with the certification checklist
3. Consider retiring unused data
4. Identify missing data sources from step 2

Learn more about how to certify data sources on our website. 

With a defined symbol to distinguish trusted data and a credible process to back it up, it’s time to enable your users. Start by informing your users via discussion forums, user group meetings, and other channels that they now have access to new, high-quality data sources. Next, teach them best practices on how to validate and explore these data assets by guiding them to free Tableau Modules on Trailhead. Lastly, regularly check the Data Source Manager Accelerator to ensure data adoption levels meet expectations. 

By implementing our four-step framework for a meaningful objective, you have successfully converted the challenge of “ensuring scalable, reliable data” into an ongoing discussion. This dialogue unlocks new features, improves users’ speed-to-insight, and creates a catalog of quality data ready to inform AI and self-service at scale across your business. Now, identify the next meaningful initiative, and repeat the process. Eventually, you’ll flip the narrative and be able to say, “we have great data, so we know we have great AI.”

Download the Data Source Manager for Tableau Cloud Accelerator on the Tableau Exchange to help monitor best practices.