In the brand new release of Tableau 2024.2 and upcoming release of 2024.3, impactful features are set to redefine data analytics and visualisation. From the introduction of Einstein Copilot, enhancing data exploration and calculation creation, to the extended functionalities in Tableau Pulse, allowing for dynamic sorting and grouping, Tableau is undoubtably entering a new phase of impactful analysis and visualisation.
The addition of new visualisation types such as the Sankey chart and the introduction of custom themes further expand the toolkit available to users. Additionally, the introduction of local file saving for Tableau Public addresses a long-standing limitation, making Tableau more accessible to beginners and organisations. These updates not only streamline workflows but also pave the way for enhanced collaboration and innovation in data analysis. With these advancements, Tableau is empowering a wider audience and setting new standards in the world of data analytics.
Einstein Copilot
Einstein Copilot is set to transform Tableau development by allowing AI capabilities to make data exploration and calculation creation more accessible, efficient, and less time-consuming than ever before.
Einstein Copilot for Tableau is an AI assistant embedded within Tableau products, including Tableau Desktop, Tableau Prep, and Tableau Cloud. In Tableau Desktop, Einstein Copilot will revolutionize data exploration. You can ask Einstein questions and receive instant, impactful visualisations, or choose from a list of suggested questions presented by Einstein. This feature is especially beneficial for calculation creation, providing guidance through Tableau’s extensive range of functions and complex calculations. This is particularly useful for beginners, intermediate developers, or those not well-versed in building calculations to enhance their analysis. I am personally excited about this new feature and the transformative effect it will have on my daily work. It promises to simplify exploratory analysis, enabling me to uncover insights that might have otherwise remained hidden.
Another significant feature of Einstein Copilot is in Tableau Cloud, where it can automatically generate data source descriptions. This automation saves valuable time otherwise spent on writing manual documentation.
Tableau Pulse: embedded component
Tableau Pulse, introduced in 2024.1 as an AI tool for automatic metric tracking, has unveiled exciting updates in the 2024.2 release this summer, beginning with the embedded component. This feature allows seamless integration of Tableau Pulse insights directly into web applications. Users have the flexibility to display individual metrics or utilize the full suite of Tableau Pulse capabilities, including insights into trends and natural language descriptions.
Tableau Pulse: dynamic sorting & grouping
Another exciting update just released to Tableau Pulse is the ability to dynamically sort and group your Tableau Pulse metrics and monitors. You can sort elements such as Data Source, Metric Name, and Recently Followed, providing greater flexibility and personalization to your Pulse page within Tableau Cloud. It’s amazing to see Tableau releasing early upgrades on Pulse which they introduced just back in February this year, I think these upgrades will encourage more Pulse users and improve business outcomes with the insights it gives organisations. Pulse was a huge release from Tableau and I would encourage anyone to read more about it on Tableau’s official website Tableau Pulse. Additionally you can check out my blog on Tableau Pulse and How It Can Help Business Leaders written by myself on this feature when it was released.
Multi-fact relationships
Multi-Fact Relationships in Tableau significantly enhance data modelling capabilities by enabling the inclusion of multiple facts within data models. This allows for simultaneous analysis of data from multiple fact tables, greatly enhancing the analytical capabilities of your workbook. However, this also emphasizes the importance of a solid understanding of data modelling principles. It’s important to be cautious with poorly built or overly large models, as these can potentially decrease workbook performance. Fortunately, Tableau offers robust performance monitoring capabilities to monitor and analyse these issues effectively.
Our Head of BI & Analytics at Dufrain, Colin Gresham, said that “Introducing multi-fact relationships brings Tableau’s data modelling capabilities in line with its competitors and provides it with the flexibility necessary for solving complex business scenarios more efficiently.” Although enthusiastic about the feature Colin also shares concerns about potential performance drawbacks: “While this feature can optimise workbooks, developers must ensure that data models are built in accordance with best practices so that large, messy models do not impact workbook performance.”
Additionally, in Tableau 2024.3, users can import multiple disparate data sources into the logical pane. This feature enables the creation of relationships between existing data models, facilitating the construction of large models to enhance analysis within worksheets.
Viz extensions: new viz types & custom themes
This summer, Tableau is expanding its repertoire of available chart types, and one particularly exciting addition is the Sankey chart. Previously, constructing a Sankey chart required intricate workarounds due to its absence from Tableau’s default options. Now, with just a few clicks, users can effortlessly build Sankey charts, eliminating the need for complex methods.
In Tableau 2024.3, custom themes will be introduced. This feature allows users to import custom themes using a JSON file, enabling easy alignment of workbook designs with company standards or project requirements for online analytics portfolios. This update mirrors the functionality already present in Power BI, streamlining the process for Tableau developers and empowering organizations to implement custom themes, thus standardizing Tableau outputs across the company.
Local file saving for Tableau Public
The introduction of local file saving for Tableau Public marks a significant update with immense value for numerous reasons. Tableau Public, being the free version of Tableau, previously had a major limitation: the inability to save work without publishing it online to a Tableau Public account. Now, with the capability to save Tableau files locally, learning and development for beginners become much more accessible. It empowers users to save and share their work with others for collaboration.
Moreover, this update benefits organisations seeking to explore Tableau as a reporting tool without committing to a license purchase until they’re satisfied. It also caters to small businesses engaged in analysis and reporting projects that don’t necessitate sharing with colleagues. With these enhancements, Tableau becomes significantly more accessible to a broader audience, addressing a long-standing need in the Tableau community.
Summary
The features discussed above are set to make a massive impact, and although these are the biggest and most exciting features in this release, it’s not the extensive list. To find out more about the additional features that are part of this release you can go to Tableau’s official website or watch the full conference for all the details.
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