You’ve heard of the infrastructure cloud provided by AWS, Azure, and GCP because it has revolutionized the way organizations run the servers and tools that power their business. You’ve heard of the application cloud provided by companies such as Salesforce, Workday, and ServiceNow that’s brought the “front office” to the cloud, with massive efficiencies of scale along the way. Now we are seeing the emergence of a third layer, one devoted to data, analytics, and cross-cloud collaboration: the Data Cloud. The trends that have brought us the Data Cloud should come as no surprise. As the adoption of both the infrastructure and application clouds has accelerated, businesses have been left with massive amounts of data spread across multiple different systems and cloud provider platforms. It is common for large corporations to have operations and data sitting in two or more infrastructure clouds like AWS, Azure, and Google, along with even more data in applications like Salesforce, Workday, Coupa and ServiceNow. This has left them looking for a way to un-silo, govern, and secure all of this private data. What’s more, there is increasing demand from within the business to actually use this data for analytics, business intelligence, machine learning and artificial intelligence. Running these workloads on top of unified and secured cross-cloud data is the vision for the Data Cloud. It all sounds promising, but what would you need in order to accomplish all of this? First of all, you need a way to combine and unify disparate data across multiple cloud platforms. Second, you would need to be able to support data of all types, including structured and semi-structured data. Third, you’d need to be able to run any number of workloads on top of your unified data in order to actually put this valuable resource to work. One of the most important workloads would be the ability to easily and securely share all of your newly unified data with trusted partners or customers, and augment it with outside data from third-party providers. If an organization were able to accomplish all of that, the potential benefits could be enormous. Although all data is valuable, it becomes infinitely more so when it is combined with other contextual data sets. To use a pertinent example, imagine having all of your product usage data in a data lake on AWS. Separately, you would likely have data about your customers in Salesforce and Marketo. Combining these datasets would enable you to create an end to end vision of the customer life-cycle that simply isn’t possible with the data in disparate silos. Having that vision of the full customer lifecycle enables the types of insights that drive new revenue streams, efficiencies, and a better customer experience. Of course, that is just a single example of the way that the Data Cloud can drive value. These are some of the concepts that we will explore in this presentation. You’ll walk away with a deep understanding of the future of data in a multi-cloud world. You’ll see how the world’s most data-centric organizations are embracing the Data Cloud and the potential it provides. Last but not least, and how you can take maximum advantage of the opportunity the Data Cloud presents you with.