At Tableau’s annual conference, Salesforce introduced Tableau Cloud, the fastest, easiest way for customers to take full advantage of Tableau at enterprise scale. The offering is the next generation of what was previously known as Tableau Online and includes new innovations to increase productivity by providing smart, powerful and easy-to-use analytical tools to help anyone discover insights and take data-driven decisions with confidence. An integral part of Salesforce Customer 360, Tableau enables customers to discover and gain actionable insights from all of their trusted data, creating a single source of truth, accessible anytime, anywhere.
Market volatility and widespread supply chain disruptions are making it increasingly difficult for companies to contain costs and move their businesses forward. Data can help manage these complexities and changes. For example, supply chains and connected production lines generate a wealth of data and customers expect real-time visibility into the arrival of goods. A recent McKinsey study found a strong correlation between an organization’s planning success and the adoption of advanced analytics. Data-driven supply chain management offers new ways to avoid disruptions and respond to unforeseen circumstances with speed and confidence.
Tableau Cloud provides the leading analytics platform to meet customers where they prefer to do business. In fact, 70% of new customers choose Tableau Cloud over an on-premises or hybrid solution to optimize their analytics. Tableau also continues to offer self-managed solutions and is committed to providing our customers with the flexible options they need.
“Speed, ease-of-use and flexibility have been key differentiators for Tableau and why customers rely on us to help them transform their business through data-driven decision-making and increased efficiency. said François Ajenstat, Chief Product Officer, Tableau at Salesforce. “With Tableau Cloud, we’re enabling our customers to achieve even greater analytical success. Tableau Cloud helps our customers deliver the analytics they need to their users, while ensuring the highest levels of trust, availability, and performance.
As part of the launch, Tableau is working with Snowflake to provide an extended promotional trial that includes Tableau Cloud licenses for Snowflake customers and, subject to program requirements, Snowflake credits upon conversion to a Tableau Cloud customer.
New Tableau Innovations Deliver Automated Insights Faster and Easier
Tableau leverages core natural language and augmented analytics capabilities to help everyone use data to make meaningful decisions. Data Stories adds automated, plain-language explanations to Tableau dashboards at scale, helping customers understand and interact with data faster. Automating the analysis, creation, and reporting of insights from data in a modern, easy-to-understand story format eliminates the need to repeatedly explain dashboards, makes data more accessible to business users and helps increase the adoption of analytics across the enterprise.
Tableau is also expanding its accelerator offering and the capabilities of Tableau Exchange, a trusted hub of offerings that extend the Tableau platform and help customers get to time to value faster. Accelerators are out-of-the-box, customizable dashboards that can be used across multiple industries, departments, and enterprise applications to quickly deliver insights and value. Tableau now has over 100 accelerators on Tableau Exchange, including those created by experts in the Tableau Partner Network, further expanding the unique use cases customers can apply.
Tableau Exchange also offers new in-product functionality, allowing customers to explore and use any Tableau Exchange offering directly in-product without requiring a separate download. This keeps people in the flow and allows them to get the right solution when they need it.
New enterprise-ready features to increase efficiency
Table also presents Advanced management, which helps Tableau customers manage, secure, and scale mission-critical analytics across the enterprise. Administrators can gain deep insights into adoption and performance, leverage advanced encryption capabilities to meet security requirements, and gain increased capacity limits to ensure teams and individuals have access to relevant data . Examples include:
- Customer-managed encryption keys helps customers meet organizational compliance standards and add an extra layer of protection for their data.
- Activity Log provides detailed event data to help administrators track user usage of Tableau. It also enables permission auditing to better enforce controls over an enterprise deployment. And with Admin Informationdata is retained for up to one year to help track dataset usage, license adoption, and visualization load times.
“Data is critical to delivering on the promise of leveraging mRNA science to create a next generation of transformative medicines for patients,” said Adam Mico, director, Data Visualization and Enablement at Moderna. “Security, governance, scalability and manageability are important parts of our overall data analytics strategy and we are excited to see how advanced management will make it easier and faster to optimize our deployment. »
Einstein integration in Tableau offers deeper insights into Salesforce Customer 360
Tableau also helps drive Salesforce Customer 360 and enables customers to fully leverage their data to gain actionable insights from their CRM data.
Powered by artificial intelligence (AI) and machine learning (ML) technology from Einstein Discovery, Tableau helps people with domain expertise make better decisions, faster and with more confidence. For example, Model Builder enables business teams to collaboratively create and use predictive models, using the Einstein Discovery engine, without having to leave their Tableau workflows.
Integrating Einstein Discovery into CRM Analytics, the advanced analytics solution for CRM users, will help customers see actionable insights directly in the Salesforce workflow:
- Discovering Einstein: Grouping Text leverages machine learning (ML) models to extract keywords from large text fields to quickly reveal hidden insights and improve decision-making.
- Einstein Discovery: Bias Detection for Multiclass Models expands the use cases for multi-class models by eliminating per-variable bias, avoiding the need to retrain an entire model.