My name is Henry Baltzer. I'm the research director at 4:1 research, now a division of S&P Global Market Intelligence. And my area of coverage is storage. Organizations today want to become data driven. By data driven, what we're talking about is they want to be able to take advantage of the data that their organization creates and be able to get insights in a timely fashion. For us to be able to do that, we need to make sure we're optimizing our storage infrastructure, not only for cost, but also in terms of performance and capabilities such as resiliency and security. [music] When we start looking at the challenges we're facing today, there are many things that we have to keep in mind. First and foremost is the fact that data growth is rapid for many organizations. In our most recent study, we saw that respondents were seeing average annual growth rates of 24% [music]for data they have under management. What makes matters worse is the fact that when we start asking them about their budgets for storage [music] and their budgets for be able to deal with this problem, storage budget growth are only growing at about 12% of an annual increase, [music] which is clearly being outpaced by what's going on with data growth today. Another key thing that we have to think about going forward is application and workload portability. As we start moving workloads around between clouds and other different execution venues, [music] venues, [music] venues, [music] we need to make sure that we're doing the right job in terms of data management because data management is going to become much more complex across these different clouds and different venues. The other thing we have to make sure of is we're doing a good job of cost control management because a lot of things may happen in terms of using these resources in an interession manner which could greatly increase the cost of what's going on with the infrastructure. Finally, we need to make sure that there's consistency across all the different execution venues [music] to make sure as we move these workloads around that there's still a consistent experience for customers. One of the biggest technical inhibitors that I see from customers is many of them are still struggling with data migration and how they're moving their data to the cloud. One of the biggest reasons for that is the fact that many organizations today are still relying on their network bandwidth to be able to move a lot of that data. But the problem is with shared networks, you have the issue of these data migration uh workloads interfering with what's going on with production workloads, which becomes a big challenge for many organizations. As a result, what we've started seeing is more and more organizations are starting to rely on physical transports to be [music] able to move large data sets to the cloud, which is great because that allows us to get past the physics limitations of trying to move hundreds [music] of terabytes or larger data sets to cloud environments. Another key thing that we have to think about is with some of the public cloud storage services, some of them are limited in terms of their data efficiency capabilities. And by that I'm talking about their ability to do dduplication or compression to be able to shrink down workloads, which in effect would be a great thing for networks because that would [music] allow us to reduce the amount of payload that has to actually travel over the wire. So it's another thing we have to start thinking about there. But probably the most important problem that we need to deal with is the fact that many organizations today that I've talked to are struggling with the fact that they have a lack of data insight to be able to judge which data is actually really important and [music] be able to react to the changing importance of data. As a result, I believe we need to have better tools going forward to be able to look and analyze data because the best data move is the ones you don't have to make. For many of the organizations we talk to, one of the key issues they're dealing with is cost control. And to us, we believe that the use of third-party cloud cost estimation tools can help organizations a lot, especially in terms of data and workload placement. Over the long haul, that's going to wind up saving your organization a lot of money in terms of compute cost and storage costs. Another thing we have to start thinking about [music] is what's going on with application deployment criteria. We need to make sure that those criteria match what business expectations are. And by that cloud resources have to have the right levels of performance, resiliency and also things like API support to make sure that the workloads are running in an efficient manner. Next thing we have to think about is monitoring. A lot of these cloud environments are dynamic. Things are changing rapidly. A lot of workloads are changing rapidly. As such, our monitoring has to keep up with those changes to make sure that we're doing the right things to make sure these workloads are running smoothly regardless of what's happening in terms of utilization and the [music] need for more performance and other capabilities. Another thing we have to start thinking about is we can't rely on public cloud security to be able to protect us. Organizations need to take the time to invest, make sure they're doing the right types of automation to protect to improve their security and also automation to improve the efficiency of their data protection. Finally, we have to start thinking about the people themselves, the IT professionals that are running these things. And we need to make sure we're investing the right amount of funds to get them training because the smarter your IT team members are, the more efficient things are going to be. And as a result, over the long haul, you'll be able to save on your operational cost.