It’s been great to see Salesforce embrace the idea of analytics for any business user at Dreamforce 2014. That’s the very idea that Tableau was built on, and something most of us here feel quite strongly about. And we are passionate advocates of the cloud, which is why we launched our cloud analytics product Tableau Online over a year ago, and why Tableau is a big customer of Salesforce and other hosted solutions.
We know how important sales analytics are, because we see the value customers get, and use them extensively ourselves. Here’s a view of Tableau analytics embedded in a SalesforceOne using Salesforce Canvas.
Reality is is a heterogeneous data architecture
One of the main questions to answer in an analytics solution is: where’s the data? There was a time when organizations aspired to have all their business data in one place. But putting aside the point of whether any company ever achieved that, which is doubtful in itself, things have changed. The reality for most organizations is that they have data in many places.
The cloud is one of many great places to put data
While the cloud offers another option, it doesn’t change the trends moving companies to a more diverse data infrastructure. Companies want to take advantage of the tremendous amount of innovation in the world of data, from solutions based on Hadoop, application data to unstructured data.
Why move your data to start analyzing it?
Tableau partners with a great many of these data source providers, including Salesforce, so that our customers can implement their data architecture as best fits them. Tableau can connect to the data where it lives, or bring it into Tableau’s fast Data Engine. Your data architecture is your choice, and our feeling is that you ought to be able to analyze data wherever it lives. In fact, you ought to be able to blend data from different data sources, on the fly, wherever that data lives.
We look forward to continuing our partnership with Salesforce as it rolls out Wave. We will also be working with Salesforce to connect to Wave via its APIs to make it easy for customers to analyze Wave data, alongside all the many other data sources that they have. And we will continue to do what we do best: Help People See and Understand their Data.