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Einstein Analytics & Tableau: What’s the Right Choice for Your Organization

Einstein Analytics & Tableau: What’s the Right Choice for Your Organization

The similarities, differences and when to choose one over the other, or both

Written by

David Rees

Principal Strategist – Analytics, Traction on Demand

It has been almost a year since Salesforce made its largest acquisition to date, which brought Tableau, an industry-leading data visualization technology, into their extensive suite of analytics capabilities. The year prior, Mulesoft was acquired which further cements Salesforce as a powerhouse of all things data. 

If you were already a user or interested in Salesforce’s existing analytics product, Einstein Analytics, the first question that you may have asked is “which is the right product for me?” The answer now would be the same as before these acquisitions — it all depends on the use case.

What is Einstein Analytics?

“Einstein AI capabilities augment a user’s workflow allowing them to work smarter and more efficiently.”

Our journey with Einstein Analytics began with another acquisition, when Salesforce completed the purchase of EdgeSpring in 2013, releasing its data preparation, storage, and visualization application under the product name “Wave” a year later.

At the time, the product promised the democratization of data, allowing business users to answer their own data questions with clicks, not code. We were amazed at the sub-second query time when crunching hundreds of millions, and even billions of records. This along with the deep integration into the core Salesforce platform, allows data from Salesforce and third-party systems to blend together, giving users the ability to take action on the insights they discover with the built-in Action Framework. 

In the five years since release, we’ve seen the application become even easier to use with more declarative data exploration capabilities, built-in support for dozens of external data sources, and the addition of predictive and prescriptive analytics capabilities powered by Salesforce’s AI platform, Einstein. 

While my favourite sci-fi movies often depict AI as a threat to replacing human workers, the Einstein AI capabilities augment a user’s workflow allowing them to work smarter and more efficiently. 

Some of the common ways we implement Einstein for our customers are:

  • Predicting which deals are most likely to close and convert
  • Scoring propensity for a customer to buy a product or service
  • Identifying the risk of subscription services being cancelled with attrition scoring
  • Providing early warning when forecasts won’t be achieved and prescribing corrective user actions to increase chance of success

This all results in users having the ability to better prioritize their tasks, focus on valuable customers and make better data-driven decisions. 

With Einstein’s capability to collect data from virtually any external system, the customer data in Salesforce can be augmented with biographic and demographic information, financial and invoicing records, and marketing engagement activity that live outside of Salesforce. This enriches the Salesforce records, enables a 360-degree view of the customer, and adds more context to predictive models.

An embedded Einstein Analytics 360-degree scorecard showing a customer’s lifetime spend and purchase history to a support agent in Service Cloud.

What is Tableau?

“Tableau made us rethink the way we interact with and consume information”

Compared to traditional Business Intelligence (BI) vendors, whose products operationalize data by generating complex (often static) reports, and require developers to make them digestible, Tableau made us rethink the way we interact with and consume information. 

Even if IT professionals are comfortable with the plethora of existing tools available to them, it’s business users who gravitate towards Tableau due to its ability to take data from anywhere and build interactive visualizations with an intuitive drag-and-drop interface.

The platform can be deployed in any manner required:

  • Server for on-premise implementations
  • Cloud for those that do not want to maintain their own infrastructure (aligning nicely with how Salesforce delivers its platform) 
  • Public for those that want to share their data explorations with the world

Business users were responsible for Tableau’s exponential growth in market share and revenue, leading Gartner to describe it as the “Gold Standard” for BI and Analytics, and placing it in the Leaders quadrant for 8 consecutive years. Strengthening the relationship with business users, Tableau has made the preparation and governance of data less technical, more user friendly, and has implemented its own set of AI functionality to automate the generation of insights to support natural language querying.

A Tableau dashboard visualizing sales and profit of various product categories by region

Einstein Analytics vs. Tableau

One practical example to highlight the difference between Einstein Analytics & Tableau is how each is being used in response to the current health and economic crisis caused by the COVID-19 pandemic. 

Since Tableau has such strong adoption amongst analysts and data scientists, we quickly saw interactive data exploration apps built using publicly available data that allowed anyone to track the impact of the virus. A few of the best examples of this are hosted on Tableau’s own COVID-19 Data Hub and showcase how anyone can take complex, but publicly available data sets and make them accessible to the entire world in an easy to use and understandable way.

Compare this to the app Traction on Demand developed with Thrive Health, where we focused on leveraging the power of the Salesforce platform to better support managing staff, supplies, and equipment in healthcare facilities. Einstein Analytics played a critical role in the ability to quickly implement embedded analytics capabilities into the same platform that would be used to log the availability of PPE, hospital beds, and ventilators, and manage the availability of frontline healthcare professionals. Because this data was already being entered and managed in Salesforce, it met the definition of a “CRM-centric” use-case, and made building the analytics components much quicker than traditional methods that would have required us to build a separate datastore, and configure separate applications to move data between systems.

Key Differentiators: Einstein Analytics & Tableau

Both products give us the ability to better understand the data we have access to, and there’s a huge overlap of capabilities that both do extremely well. In order to know which one will work best for your use case, it is worthwhile to do a side by side comparison highlighting the key differences. Keep in mind these items are not mutually exclusive and the overlap will include some of the best capabilities from both platforms.

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While choosing the right system is difficult, in this situation there is a brightside; regardless of which application is selected, by having both under the same Salesforce umbrella, they will continue to innovate, push capabilities, and ultimately enable end-users to work smarter.

For example, we’re already seeing the blending of capabilities between both products, with the ability for Tableau to now surface predictions generated by Einstein, extending insights across the organization, even to users that don’t use the CRM.

Sometimes it works to implement both solutions to handle different use-cases, and coupled with Mulesoft to orchestrate the movement and governance of information across all systems, there are options that will enable organizations to better leverage all of their data sources.

How Traction on Demand Can Help

“The overlap in functionality can make choosing the right platform difficult, but we’re here to help.”

With analytics implementations across small to enterprise clients and a dedicated Analytics Consultant team, we love talking data. Get in touch with a member of our data team to discuss how we can help make your organization more efficient and empower your users to make better data-driven decisions.

Not sure where to start with Einstein Analytics & Tableau? We have a 12-week methodology to help you get up and running by focusing on the use-cases that will provide you with the most value. 

Let’s Talk Data

Get in touch with a member of our data team to discuss how we can help make your organization more efficient and empower your users to make better data-driven decisions.

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