Einstein vs Tableau vs Custom Development: Salesforce BI Comparison

Einstein vs Tableau vs Others

So… you’ve implemented your new Salesforce CRM and began to systematize your most critical institutionalized processes. Congratulations! Now, if you’re like most of our clients at this point, more and more data is populating and you’re doing your best to couple this ever-expanding dataset with external system data to inform your team, managers, and executives on business performance. Before most of us find ourselves weighing Einstein vs Tableau, we typically find ourselves running Salesforce reports and exporting them to Excel or Google Sheets, and as we put the finishing touches on the final pivot table, we take to Google to explore alternatives. For those of us who run Salesforce, the common comparison is Einstein vs Tableau, but we will also discuss other methods.

There is a lot of information out there, and it can be hard to “know what you don’t know” when it comes to finding the right BI method. Luckily, we’ve implemented many methods for companies from SMBs to international enterprises, and we’ve compiled our notes below to help make your transition simpler. 

Throughout the many long meetings & late nights our consultants have spent with our clients defining key KPI’s, architecting master data management strategies, integrating systems, and configuring datastores, there has always been one question that every client asks in one form or another – “Great. Now how do I surface it all in Salesforce?”

In this article, we will be focusing on the most popular methods to surface external data within Salesforce and b) visualize that data in your Salesforce CRM.

Einstein Analytics 

If you’re looking to keep everything in one place & enhance everything you love about Salesforce Dashboards & Reporting — look no further then Einstein Analytics. Formally known as “Wave Analytics”, Einstein Analytics provides intuitive, insightful & gorgeous visualizations right from the Salesforce interface we all know. Einstein Analytics will be your path of least resistance to surfacing external data right where you need it inside the SFDC platform. A community version of Einstein provides the scaffolding for creating insightful & data rich experiences for partners & customers alike. This method is typically recommended for any client who is looking to surface Salesforce data beautifully within their CRM, or a Community built on their Salesforce environment.

The Cost: Starting at $125/user/month billed annually as per Salesforce

Unique Benefits

• Built right into the Salesforce Platform & easy to configure & deploy anywhere. 
• Leverages native Salesforce security & data. 
• Pre-Built Connectors for many popular services & web connectors. 
• Pre-Built Insights for Sales, Service ,FSC & Health Analytics etc.
• Smart Notifications for alerts
• Looks fantastic on mobile without much configuration
• Can store data from external sources without incurring Salesforce Platform fees. 

Considerations

• Least amount of license types to operate at enterprise scale
• Not as robust as other platforms on this list 
• Subject to Salesforce limits and may incur additional costs at scale
• Synchronization of external data must be scheduled, often requiring middleware which may bring additional fees. 

Tableau 

Salesforce made waves in 2019 with its blockbuster acquisition of business intelligence giant Tableau. Seeking to fill a gap between it’s on platform visualization tools such as Einstein & more robust BI tools such as Microsoft BI. The acquisition bought Salesforce a seat at the multi-channel data aggregation & analysis table. Tableau, which features both on-prem & cloud-based versions, is able to connect to a range of data sources & stores to compile & report on data. Transformations & rules can be built on platform as well.  

The Cost: Creator License Starting at $75/user/mo as per Tableau. Note, your organization will have a mixed environment of license types.

Unique Benefits

• Enterprise BI Tool that can deploy On-Prem & in the cloud.
• Can be embedded on Record pages & filtered — but lacks record level security. 
• Ease Of Use, Beautiful & Interactive Visualizations & built with Big Data in mind.  
• Pre-Built Connectors for many popular services & web connectors. 
• Support for Python Transformation
• Flexibility in license types can present more appealing economics at enterprise scale

Considerations

• Embedding reports, while possible, is not as strong as other options on this list

External Objects & Salesforce Connect

Visualization & Reporting is great. Having the raw data visible in Salesforce at times can be better. Salesforce Connect allows you to access data exposed through Odata agnostic of the underlying source and surface the records inside of Salesforce. Those records can be viewed, searched & modified inside of Salesforce.

The Cost of Lightning Connect: Roughly $4,000/month

Unique Benefits

• Allows you to treat external data in a very familiar way. 
• Can provide real time insights into underlying data. 
• A great way to handle large data sets that you do not want to replicate in Salesforce. 
• Can leverage standard reporting to make use of the external data. 
• Added benefits such as the ability to modify the external data from within Salesforce. 

Considerations

• Additional incurred expense could be cost prohibitive for smaller organizations
• Requires exposing the underlying database over the web which could raise red flags in compliance departments
• Limitations of Salesforce Connect and External Objects per Salesforce

Aura & Lightning Web Components 

Sometimes you just want to build it yourself. Powerful javascript frameworks & beautiful visualizations libraries such as D3 can be leveraged to build stunning & insightful components that can be embedded anywhere lightning components can. Data can be dynamically accessed on demand through Web Service APIs & transformed in flight!

Unique Benefits

• Complete control over data & how it’s displayed. 
• Ability to create custom functionality & interactivity with the data & dashboards. 
• Ability to reload fresh data based on system actions
• No recurring fees for subscription software

Considerations

• Most labor-intensive option on this list
• Requires either an internal engineering team to own, or retained augmented staff agreement like The Plative Alliance Plan
• Data volume limitations which could incur additional fees for storage

  As you can see, there are many factors to take into consideration when you’re creating your strategy for data surfacing and visualization at scale. If this article has inspired you to plan your next data consolidation and BI implementation, get in touch with us here at Plative to learn more!