Kudos to Tableau for pulling off a fully virtual TC 20 conference. Wow! Amazing orchestration of content, entertainment, speakers and technical delivery. Here is hoping we we can be back together in-person in 2021!
As we come out of the amazing TC 20 conference, we wanted to reflect on a couple of the sessions we attended and a general point of view of what we saw and heard this year.
Here are some thoughts from our team:
Einstein Analytics, Layers, Iron Viz & More
Tableau is continuing to expand to capture the full end-to-end data pipeline. Einstein Analytics embedded throughout the pipeline will add some options for many organizations. The integration of Tableau with the broader SF framework is definitely picking up full steam. Overall this is probably a good thing and opens up some opportunities.
With the rebranding of Einstein Analytics to “Tableau CRM” indicates to me a commitment to Tableau as the analytics platform within the broader SF framework. Will be interesting to see the continuation of this positioning as these two organizations become even more integrated.
The layers feature is very cool! Tableau continues to expand in its geospatial capabilities.
IronViz was amazing! Giving the contestants the ability to shape the data however they want ahead of time makes for a different contest but the results are stunning. (It’s been this way for a few years now). The virtual setup worked really well.
Observations About Tableau Community
Lots of opportunity around how to think about visualizing data for use; beyond just the chart, but also the purpose behind the visualization. The user community continues to get much deeper into how they are thinking and presenting the data, leading to better insights and even more sharing across the organization.
Tableau Prep continues to evolve and is an important tool in an end to end platform. Users are better understanding how to showcase data shape and the effect it has on the analysis of the data is something to keep in mind. Users continue to develop their requirements gathering skills and becoming real “solutionists” that has measurable impact on the organization.
Lastly, the Tableau user community are discovering the power of deeper data scientist type tools/functions like Python and R and will want to continue to expand their skillsets beyond traditional Tableau work.
Making Interactive Dashboards Pop
Shay and Samantha presented a focused storytelling session on making dashboards more interactive and user-friendly to facilitate on-the-go analysis. As their proof of concept, they built an interactive dashboard to pitch their vegan ice cream shop to investors – no PowerPoint deck involved!
Through text navigation buttons at the bottom of a dashboard, adding animations to clearly demonstrate dashboard actions, utilizing show/hide containers, and placing a viz inside a tooltip, Shay and Samantha demonstrated interactive concepts that drive data discovery and improve dashboard performance. A particular use case of interest is slightly slowing down the speed of animations to guide a user on a particular viz. These animations work automatically upon interaction, and dynamically update when the underlying data of a viz changes, say due to a filter action. Your dashboards don’t have to be static – use them to communicate! Shay and Samantha’s dynamic and lively dashboard goes to show that leveraging Tableau as an interactive data presentation and discovery tool is both achievable and persuasive.
Map Layers: Hurricanes, Puppies & Burritos
Tableau map builders rejoice – no more dual axis maps!Map layers, a new feature in an upcoming Tableau release, allows users to easily add geographic layers to maps. Each layer receives its own marks card, allowing for independent, layer-specific formatting that can be reordered and hidden for on-the-go analysis. The presenters demonstrated this by showing a hurricane path through the East Coast, the locations of animal shelters only within the path of the hurricane, a buffer zone surrounding the shelter as an area to search for lost puppies in, and – for when you’re hungry – the locations of a burrito chain that fall within the buffer zone.
The specific impact is in lowering the barrier to geospatial analytics. The Map layers feature allows more than two layers to be overlaid, something dual-axis maps could not easily do. To have all four of these layers with a dual-axis map would be very challenging; it would require hefty shaping and combining spatial object fields before bringing the data into Tableau. With Map Layers, the presenters simply brought in a hurricane shape file as the base, used a ‘Makepoint’ join calculation with a file that had lat/long for animal shelters, used a ‘Buffer’ join calculation to identify an area around each shelter to search for lost puppies in, and lastly, used a ‘Makepoint’ join calculation with a file that had lat/long for burrito joints to find ones that intersected the animal shelter buffer zone.
Rumor has it: Layers will make an appearance elsewhere in Tableau. Stay Tuned!
Einstein Analytics and Tableau are joining forces as an integration within Tableau. The new platform will be called Tableau CRM.
Einstein Analytics (EA), originally created for use exclusively for the Salesforce application, provides predictive modeling using Artificial Intelligence (AI) and Machine Learning (ML). Predictive modeling is complex and typically requires a data scientist to build models. EA has simplified this process for their users.
The integration will initially include Einstein Discovery inside of Tableau. Einstein Discovery provides AI-powered analytics that enables business users to automatically discover relevant patterns based on their data without having to build sophisticated data models.
During this session, the speakers showcased three powerful examples inside the Tableau platform:
While these tools provide some powerful new capabilities inside of Tableau, many users may require some assistance setting them up to provide value to their business users. As a Salesforce | Einstein Analytics partner we look forward to help you take full advantage of these new capabilities.
Learn more about Einstein Analytics here.
What are your take-aways from TC-20ish? We would love to hear from you to get your perspective!