There is currently a lot of movement in the Tableau and Salesforce community: Tableau Next is the talk of the town. With the new platform, Salesforce is showing where business intelligence could be heading. The central concept is called Agentic Analytics - a vision in which data, AI and automation interact seamlessly to not only enable analyses, but also to translate them directly into actions.
Before we continue, it is worth taking a brief look at the term "agentic analytics": the idea behind it is that analytics systems no longer just provide information, but act independently. Instead of humans evaluating data and reacting to it, intelligent agents take over this step. They recognize patterns, derive recommendations for action or even carry them out automatically. This transforms analytics from a purely descriptive discipline into an active, action-oriented one.
Sounds ambitious? It is. Tableau Next is at the beginning of this development, and many of the announced functions are still being developed or rolled out. Nevertheless, the time to get to grips with the concept is now.
Especially for companies with CRM data in Salesforce, there is an opportunity to implement initial proof-of-concepts (PoCs) and explore the potential of Agentic Analytics in practice.
As an experienced partner in the field of data, analytics and visualization, we are accompanying this change - with interest, but with a healthy dose of realism. There is undoubtedly a lot of potential behind the big promises, but there is also a level of technological maturity that needs to grow. The best way to assess the potential of Tableau Next is through concrete PoCs with real CRM data.
Salesforce is positioning Tableau Next as the next step in the evolution of business intelligence. The claim: Data analyses become intelligent dialogs that lead directly to action.
In the vision of Tableau Next, users ask questions in natural language and receive not only answers, but also recommendations or automatic actions. Analysis becomes an interactive process, supported by generative AI.
Tableau Next is closely embedded in the Salesforce platform and uses the Data Cloud as a shared database. This is intended to bring together data from sales, service and marketing without additional integration efforts.
The Swiss data location (Zurich) has also been available for some time. This allows companies to host their Salesforce and Data Cloud data within Switzerland. An important step for Swiss customers.
The semantic layer is particularly exciting. It is intended to serve as a common semantic basis that combines business logic, aggregations and metadata. This creates a central level on which key figures, calculations and relationships are defined, regardless of who creates a dashboard or which data source is used.
The goal is standardized KPIs, less room for interpretation and more trust in the data. For example, if the term "active customers" is defined in one place, this change is automatically applied to all associated visualizations. This reduces maintenance effort and inconsistencies and is therefore particularly interesting for large organizations with many data teams or decentralized reporting structures.
An important promise: Existing Tableau environments remain usable. Semantic models and data sources can be shared between classic Tableau and Tableau Next. The changeover can therefore take place gradually and without system disruption.
A core promise of Tableau Next is the so-called Zero Copy Data architecture.
data no longer needs to be physically copied or replicated in order to be analyzed. Instead, Tableau Next accesses external platforms such as Snowflake, Databricks or BigQuery directly, while the data remains where it is.
The advantage: less redundancy, lower storage requirements and always up-to-date data. Governance and security also benefit because sensitive information is not moved multiple times. In practice, however, the benefits depend heavily on the performance of the underlying systems. Network speed, query optimization and cost control remain decisive factors.
In our view, zero copy data is an exciting approach with a lot of potential, but one that should be closely monitored and tested in practice before it becomes standard. Especially in hybrid landscapes with complex security or compliance requirements, a clean architectural design is needed to turn theory into real efficiency.
Salesforce is talking about modules such as Data Pro, Concierge and Inspector, which facilitate AI-supported data preparation, monitoring and interaction. The first versions of these functions are already available and show where the journey is heading.
From today's perspective, this concept is still in its infancy and much of it is more of a preview than an actual reality. Nevertheless, the direction is exciting. If Salesforce manages to seamlessly integrate these functions into everyday analytics, this could become a central building block for truly intelligent analytics experiences in the coming years.
Tableau Next follows a modular architectural approach that provides for clearly structured responsibilities. From data source to action.
| Layer | Fuction | Data Layer | Importance for projects |
| Data layer | Access & storage of data | Salesforce Data Cloud as central system, zero copy data | Uniform database without redundant data movement |
| Semantic layer | Business logic & KPIs | Tableau Semantics - AI-enriched model for definitions, relationships and governance | Standardized KPI definitions, more trust in data |
| Visualization Layer | Exploration & visualization | Visualization Builder (low code coupled to semantic models) | Faster dashboard creation, consistent visualization |
| Action Layer | Act from insights | Salesforce flows & workflow triggers | Integrate insights directly into business processes |
In this architecture, the semantic layer forms the link between data and visualization. It is still difficult to assess the extent to which this architecture has already been implemented. But the direction is right: away from isolated reports and towards a networked, active analysis platform.
After all the announcements about Tableau Next, the crucial question for many is: How does the new system fit into the existing Tableau landscape?
Because even if Salesforce is pursuing big plans with Tableau Next, the classic Tableau ecosystem - with desktop, server and cloud - remains relevant. Tableau Next does not replace these tools, but extends them.
In short: Tableau Next builds on the tried and tested and adds further promising features.
Focus on manual exploration and visual analysis
Dashboards and data sources as primary assets
Separate but flexible connection to Salesforce and external data sources
Proven stability and governance structures
Closer integration with Salesforce ecosystem and Data Cloud
Introduction of the semantic layer as common business logic
AI-supported interaction via voice or recommendation system
Action layer for automated or embedded workflows
For existing Tableau customers, this is not a replacement, but an enhancement perspective. Now is a good time to get to know Tableau Next, gain initial experience and familiarize yourself with the new functions. Those who start early can take advantage of future competitive advantages.
Tableau Next is less a product release than a promise - a glimpse into the direction in which business intelligence will develop.
The integration of AI, language and action is a logical, exciting step. But as with any new technology, the rule is: first gain experience, then scale up.
Proof-of-concepts with CRM data in particular now offer the ideal opportunity to familiarize yourself with the platform. Together with our customers, we are developing compact pilot projects in order to recognize the potential, limits and future opportunities of Tableau Next in practice at an early stage.
Now is the right time to get active. Development in the field of agentic analytics is progressing rapidly. What is still considered beta today may be ready for the market tomorrow. It is worth gaining experience early on and testing the potential of your own data landscape with a proof of concept (PoC).
Companies that learn how to deal with this new generation of analytics now will gain a clear competitive advantage.
Anyone who would like to delve deeper into the topic or start a PoC is welcome to get in touch with us. We will share our experience and provide pragmatic support at eye level - from the initial concept to the concrete use case.
Many organizations already work with a Salesforce partner for their CRM environment. This is ideal, as we do not see ourselves as competition, but as a complement.
With our experience from the Tableau and analytics world, we expand existing expertise to include data visualization, insights and AI-supported decision-making processes, creating a strong team together with the Salesforce partner: the optimal combination of CRM expertise and data excellence.
Value beyond data.
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