In 2013 Salesforce acquired a company called Edgespring, which was the start of the Analytics Cloud. A year later at Dreamforce we came to know Edgespring as Wave Analytics, and that later changed name to what is now Salesforce Einstein Analytics. Needless to say that regardless the names Einstein Analytics is an analytics solutions that allow you to quickly drill down into any data since data can be sliced and diced to explore the answers to your questions.
When Wave was launched in Europe in 2015 I was lucky enough to attend the Brown Belt training delivered in Paris and I’ve been in the space since implementing analytics solutions, done public speaking and delivered training, so I’ve had the chance to follow how Wave has evolved and become Salesforce Einstein Analytics. Interestingly there are a few questions that keeps coming up that dates back to the first days of Einstein Analytics.
Two main questions are “is it still expensive?” and “do you still have to manually write your own instructions?”
If you walk in the Salesforce circles and attended a World Tour, Basecamp, user group or maybe you are lucky to have attended Dreamforce, then I am sure you have seen the eye-catching dashboards from Einstein Analytics. In my opinion this is because of two things.
First companies are gathering so much data every day and we want to have insight and know the status. Salesforce standard reporting have some great options, but some use cases are simply not suited for standard reporting and we need more powerful tools like Einstein Analytics, that has been created with the sole purpose of getting insight from vast amount of data. Second it’s been more than 4 years since Wave was introduced to the Salesforce world and much has changed since then. There has been several restructuring of the licensing model, last when EA+ was introduced at Dreamforce 2018. This same introduction of EA+ is also an indication of how hard the product team has worked to make Einstein Analytics more powerful. Because of this it’s time to say a final goodbye to Wave and look at what it has become with Salesforce Einstein Analytics.
To answer the question if it’s still expensive, well that will be relative. To get the prices you should refer to the list prices on the Salesforce website or contact your Salesforce AE. But here’s the main thing to remember between now and then. There is no minimum licenses to be bought and the license include a lot more features than back in 2014. In fact since the Winter ’19 releas,e Einstein Analytics include Einstein Discovery and with your license you can get predictive intel – something we didn’t have back in 2014.
The second question is not that straightforward to answer. Do you still have to write your own code or instructions in form of SAQL (Salesforce Analytics Query Language) or mess around with the code (JSON) that makes up the dashboard? That depends on what you want to do. The honest answer is that you can write your own SAQL and customize any of the dashboard instructions and we shouldn’t remove that, that’s the power of the platform. But the key thing is the product team has listened to the feedback from the community and has worked very hard to bring more power to the user interface. You do not have to sit a navigate through code to modify how you are bringing data into Einstein Analytics in the Dataflow neither would you have to manually write the instructions for the mobile-optimized dashboards. It is now possible with clicks and not code to create datasets and dashboards and it’s been that way for a while. Of course, there will always be edge cases where we need to go deeper, but that is why Einstein Analytics is a platform and not just a tool.
If you look beyond the questions that dates back to the beginning of Wave, Einstein is a force to be reckoned with that gives you a lot more than you get in standard reporting. How about creating custom maps to illustrate any data, enable Salesforce Global Actions to act on the insight you get, create complex calculations with compare tables (no code needed), bring data from external sources into your dashboard or get automatic intel on what’s going on in your business? Listing all the features may sound a little abstract if you haven’t worked with Einstein Analytics before. But imagine you are selling tickets at a stadium and you want to be able to see where in the stadium tickets are selling. Well, this is where custom maps comes in. Instead of viewing a table you will see the actual stadium that is clickable to drill down into different sections of the stadium. If you want to see the quantity of the sales for this month compared to last month then compare tables can make this easy for you and when your users are exploring the dashboard they have all the Salesforce global actions available with one click directly from the dashboard.
The fact is with all this data companies are gathering across systems they are not able to get insight out of all of it without an analytics platform. While standard reports in Salesforce are great they are not geared to handle data the way Einstein Analytics is. So if you are struggling with creating derived measures in your report, maybe your report times out or you need to combine data from more than three objects I would encourage you to start looking at Einstein Analytics.
As with most of the Salesforce products, there are a vast amount of opportunities to learn on Trailhead. You can get your own org with Analytics enabled to try out the whole suite of analytics tools. To make your learning even easier there is an official “one stop to all you need to know about Einstein Analytics” website the Einstein Analytics Learning Map (www.einsteinanalyticslearningmap.com) plus if you are a customer you can ask your AE to nominate you to a two-day free academy learning the A to Z of Einstein Analytics. Also if you want a little more guidance on how to get started I wrote a blog to help people that are embarking on their Einstein Analytics Journey (http://www.salesforceblogger.com/2018/02/05/embarking-on-your-einstein-analytics-journey-start-here/).