Introduction to Salesforce Wave & The Analytics Cloud
Salesforce Analytics Cloud was the major product announcement at Dreamforce ‘14. The Analytics Cloud is new age cloud BI (Business Intelligence) tool built on the Wave platform. There has been a lot of buzz around this new product over the year since its release, but a lot of people are unsure how this product fits into the existing Salesforce product suite. This post was inspired by a fantastic presentation by Scott Gassmann & Minesh Patel at the London Salesforce Admin group and contains contributions from them.
What is Business Intelligence?
Business Intelligence software is the bridge between a large collection of unstructured data and meaningful insights. BI has been around for many years and uses techniques such as data warehousing, data mining and predictive analytics to provide users with the insights to make informed business decisions. BI makes use of graphical representation for the large amount of data that it deals with, providing graphs, charts and other data visualizations to make the information easy to interpret.
Wave vs Analytics Cloud
You may have heard both of these terms being used interchangeably when people have talked about this new product, but they are actually very different.
The Analytics Cloud is a Salesforce product, much like the Sales & Service Cloud, you can buy this product and start using it out of the box. However, Wave is the platform that that the Analytics Cloud is built on. This means that in the future, Partner App companies will be able to build their own BI applications on the Wave platform. This relationship might seem familiar, and that’s because it’s exactly the same as Salesforce.com and Force.com. If you are unfamiliar with how these two applications interact then check out this post.
Analytics Cloud vs Reports & Dashboards
You might be thinking to yourself, “Why would I need Analytics Cloud? Reports & Dashboards provide graphical representations just fine?”. Depending on the type of business you work for, this statement may very well hold true, not all companies are going to have a need for the Analytics Cloud. However, for the ones that do, it will be down to limitations of Salesforce Reports & Dashboards.
R&D are fantastic for viewing quick real time operational data to get a snapshot of what is happening inside your CRM. But to try and determine trends from extremely large sets of data can become problematic. One of the main attractions of the Analytics Cloud and other BI tools is the speed they can process large amounts of data. R&D in Salesforce can process a moderate amount of data, but it definitely is not suited to processing millions of rows.
Speed and processing power becomes even more apparent when you realise that Analytics Cloud can process data from external systems as well. It can grab data from ETL, CSV upload (Which can also be done on iOS devices) and of course data from your Salesforce CRM.
A couple of other points include is the fact that R&D can only historically report on data over 90 days, and the graphs and visual representations of data is far superior in the Analytics Cloud. For more information around Analytics Cloud vs R&D, please check out this comparison complied by Salesforce.
Analytics Solution Elements
Dashboard
Similar to the dashboard in a standard Salesforce instance, the Wave dashboard is a combination of reports (known as “Lenses”) with possible filters, links, images, etc.
Lenses
This is basically a single report based off a dataset in Analytics Cloud.
Dataset
The name says it all for this one — a dataset is simply a set of data. For example, it could be a list of opportunities or a list of users. You also might have an augmented dataset, which basically combines two datasets into one (e.g. opportunity line items and opportunity information).
The data used in these datasets can enter Analytics Cloud through any of three channels:
- A built-in standard Salesforce connector, which makes for a really nice GUI
- A manually uploaded CSV file
- Custom integrations through a middleware layer such as Informatica
Dataflow
The easiest way to think about dataflow is to view it as the bridge between the part of Analytics Cloud that receives data and the part that packages that data into datasets. Dataflow handles aspects of dataset augmentations as well as any translations that are needed before the final datasets can be created or updated.
Trailhead
You’ve guessed it, there is also a trail dedicated to understanding and exploring the Salesforce Analytics Cloud, and when I say “explore” I mean, you get your own dedicated Analytics Cloud environment to put your newfound skills to test. The modules that make up the trail are:
- Wave Analytics Basics (Where you learn how to get your Analytics Cloud environment)
- Wave Desktop Exploration
- Wave Mobile Exploration
I thoroughly recommend you follow the detailed steps on how to provision users to the Analytics Cloud. It’s very easy to get excited about your new shiny Wave enabled environment, however there are a few special steps around both Permission Set Licence Assignments as well as Permission Set Assignments that you will want to make sure you are familiar with.
