The Next Evolution of the Cloud:
Q&A with Kailash Sawant, Enterprise Cloud Architect at Microsoft
Cloud technology has altered nearly every aspect of the IT industry, along with the way we work and the way we live. But what’s next? We sat down with Kailash Sawant, Enterprise Cloud Architect with Microsoft, to discuss the next evolution of the Cloud, the future of Digital Transformation, and how predictability and automation will further shape our world.
Q: How long have you been at Microsoft?
I’ve been with Microsoft for a little over three years. Prior to that, I worked on a joint venture that specialized in Microsoft technologies, and in that role, I had an opportunity to focus on Cloud backbone technologies. Since then, I’ve worked on Cloud technology exclusively - particularly the Microsoft Cloud.
Q: Give us an idea of the kind of work you do with larger organizations.
I assist customers with their end-to-end journey into the Cloud—and that might mean different things at different times. Sometimes it's tactical, sometimes strategic. I may be advising them on the Cloud or introducing new features on Azure. Or I may help them discover how their current technology potentially integrates with the Cloud and advise them on best practices and design as we build out their Cloud strategy. Often, I'll spend a good amount of time on a white board, architecting with the customer.
Q: Is the technology getting to the point where the Cloud Generalist role will replaced by more specialized roles?
If you look at the feature list today versus six or seven years ago, the Cloud is a completely different product. I don’t think any one person could know all that there is to know. Just like any other technology, the Cloud has grown and matured. There are areas around data and analytics and areas around hosting and infrastructure, and areas around AI and machine learning in the Cloud. All of these have developed into their own individual silos that essentially warrant their own expertise.
Q: When you speak to large organizations about their Cloud strategy – and their goals concerning the Cloud - how has that conversation changed? Are the initial goals different?
Our typical customer journey starts with the off-loading of hosting and maintenance. That has not changed. Those are overhead costs for any organization that is not in the business of hosting or maintaining data centers. For example, if you were a retailer and you wanted to concentrate on your retail aspects of your business, whether it was online or brick and mortar shops, there was no way to avoid maintaining your own data centers in the past. Essentially you were in a business of selling goods, but at the same time, you had to manage this overhead. Dealing with the operational administration of being able to rack and stack servers, providing the cooling for your data center, leasing your space if necessary, and of course, dealing with user management. Migrating to the Cloud reduces this operational overhead instantly. That is nothing new, but that is always one of the primary benefits that our customers see.
Another big aspect is the fact that the Cloud is a pay-as-you-go service. When you own your own data centers, you are essentially paying for it - whether you use it or not. And on top of that, you have the racking and stacking, the maintenance, the cooling, potential leasing space, and the list goes on. Businesses don't have to do that anymore.
Cloud has become a one-stop shop and has provided companies the ability to concentrate on their core business—the processes and the tools—that are needed to succeed. And you don't have to worry about hosting your own data center. Most of our customers that we talk to, and those that we have spoken with over the last few years - their priority is data center consolidation, or data center closures, or some flavor of Cloud migration. That is one of their top IT priorities. That’s the push that gets them thinking about migrating to the Cloud.
Q: I assume most companies are focused on migrating their infrastructure to avoid the constant maintenance and labor costs involved. But what’s next? Once they’ve done that and migrated some data, how do you get them to open their eyes to the next stage of digital transformation and begin experimenting with machine learning and data science?
That is a really good question. If you think about what Cloud has to offer - these tools for machine learning, AI [Artificial Intelligence], app development, infrastructure hosting, etc. What we have seen in a typical Cloud journey from our customers is that it is initially designed around infrastructure duplication and there's nothing wrong with that. But once they move to the Cloud, once they have all the data migrated, they realize the power of these additional tools and features that the Cloud provides.
What they realize is: Now that I have my data in the Cloud, I can get more insight into that data – bring in the power of business intelligence, AI, data warehousing, machine learning - and make these insights more intelligent. We can predict outcomes and bring a whole different dimension to that data. This is the journey and evolution of businesses as we see today.
Now, how does digital transformation fit in? Not too long ago, every company we spoke to was focusing on their online strategy. Since around 2013, that conversation started to incorporate digital touchpoints, as devices like Fitbits, smartphones, other wearables exploded in popularity. Digital Transformation became the jargon that every service provider and every business was talking about. What has digital transformation done in these past five years? Well, if you are an online retailer and you haven’t made your product purchasable on a smartphone, you lost the sale. If you make your customer reach for their laptop, you lost the sale.
If you’re a commuter who has to wait to get home to watch your favorite TV program or movie, the value is lost. This has been digital transformation up until now. Being able to provide that interface right there. Provide the digital touch point right where your customer can access it. Let the customer buy their favorite product, watch their favorite movie—whether they’re sitting on the tarmac at an airport or commuting on a train. That's been digital transformation up until now. Most businesses are already there.
If there is a new business that is just starting out online, they typically start with those basics. The strategy is to ensure that their products have a nice online presence, regardless of the device. Now we need to think about the next stage.
The next stage is about predictability and automation. How do you empower your customers, your employees, or anyone that you touch digitally, with the power of predictability and automation? Being able to precisely predict what your customer or your employee needs at a specific point in time—projecting that onto his interface. That is the next stage. Imagine, for example, your employees who read 300 emails each day. If you could precisely predict, based on what their colleagues are reading and working on, based on the projects they are involved in, using intelligence to bring that list down to around 50 emails—imagine the kind of productivity that you would gain across an organization.
Think about something like a sporting goods store selling running shoes to customers. If they have the capability to predict when the shoe is going to wear out—and that's possible with data—that sporting goods store can make running shoes a part of that customer’s relevant shopping items while they are browsing online. You made an impact. You've presented your customer with a relevant purchasing option based on intelligence. If organizations are not thinking in these terms, they are waiting to be disrupted. This is all possible and will get increasingly easier as time goes on.
All of this is possible with the power of the Cloud. It doesn't take a huge investment to do this. Business intelligence, AI, machine learning—it’s all readily available in the Cloud. All the building blocks to construct these intelligent platforms is right at your doorstep.
Q: The shoe example is a good one. The sporting goods store could get the customer the right type of information based on a product that they know you previously purchased. It wouldn’t really matter if, for instance, the shoes were connected and providing data. The store could still make predictions around that purchase based on other factors.
Absolutely. You can make a lot of intelligent predictions based on the relevant data. We are not even talking about things like IoT [Internet of Things]. Data is available in several forms that might not be directly related, but will certainly be factored in while bringing the data together to form predictions. Apply AI, machine learning, on top of it to drive intelligent insights and uncover a whole new dimension to your data. That’s going to impact your business.
Q: How much of an initial investment will an organization have to take on, both in developing the skills necessary to take that next step, and the cost. Is it a huge mountain to climb?
No, absolutely not. Whenever we talk about data and machine learning, people generally think about the need to either be a Data Scientists or to have one on staff. Looking at Cloud solutions from Microsoft, or even Google, they provide machine learning and AI tools right at your fingertips, so you don't need to hire a team of scientists to be able to use these tools today.
For example, imagine you're a small airline company. Even a smaller company can purchase weather data and flight records from several regions and apply deep learning on top of that information to create a fairly predictable model of flight delays or preventative maintenance. How valuable would that information be for a smaller airline trying to compete with the majors? The small airline does not have a huge fleet of airplanes that can be quickly used as a replacement. If one of them was about to be sidelined for maintenance, and you were able to predict that instead of reacting to it, you can schedule that to better utilize the remaining planes in your fleet and maximize your profits.
As more organizations take on machine learning, and they get more intelligent with their data, do you think it will be as much of a game changer as the move to the Cloud itself?
If you follow our CEO Satya Nadella, or other technology leaders, like Sundar Pichai at Google, most of their conversations publicly revolve around AI, cognitive services, and bots. Bots are here to stay. And what powers bots to make them intelligent? Machine learning is at the core of that intelligence. And from what we read, by the next decade, we will not be able to spot the bot. Given this, I believe machine learning will be the one of the biggest game changers the industry has ever seen.
The examples will be everywhere. Healthcare companies using machine learning to be able to predict cancer. The airline industry that we spoke about a moment ago. The list goes on. Machine learning is a technology that's here to stay, and it's going to advance dramatically over the next decade.
Let’s talk about the opportunity in these areas. Microsoft has been talking about the Cloud skills gap for a couple of years now. Do you see AI, and machine learning also introducing a significant skills gap that needs to be filled? How much of an opportunity is out there? I would assume limitless.
I believe that this is more of a perceived gap than anything else. Given all these tools out there, this gap can be quickly spanned. If I wanted to learn new technology prior to Cloud, I would have to invest in costly licensing, racking, and stacking huge computing environments. You don't have to do that anymore. Cloud gives you that at your fingertips. When we are talking about AI, machine learning, bots, we are at the very nascent stage. We’ve just begun. This world is about to explode and opportunities are out there.
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