Cloud, going forward, needs to interest with machine learning and artificial intelligence and at the intersection of it all: DATA.
Mar 30, 2018
“Data is the new oil.” If only I had a dollar for every time I’ve heard that phrase over the past few months I’d be able to buy more than a few bitcoins! This mantra is obviously something core to who we are at Delphix; the underpinnings of our mission from the very beginning almost a decade ago to help people and teams distribute data.
I just returned from the IBM Think conference where I had the privilege to present to developers and business leaders at the IBM Optim User Community Day about the transformative powers of opening up access to a growing - seemingly endless - supply of data?
And, whereas it’s widely known that cloud platforms would be a focus of this event — and it was — imagine my excitement when the conversation broadened to move beyond cloud, to the intersection of data and things like AI and machine learning with overall cloud strategies. In fact, IBM is taking this approach to our joint customer base... it’s not just cloud anymore. It’s much more than that. Cloud, going forward, needs to interest with machine learning and artificial intelligence and at the intersection of it all: DATA.
IBM customers took stage at the conference: American Airlines, which had migrated to an IBM cloud, was also looking to pursue machine learning to help them plan major events to strategies to divert planes, if need be. When people are stranded and unable to get to their destinations, their customers understandably are frustrated, calling airline representatives and worrying about their itineraries. American Airlines understood the anxiety behind this phenomenon and realized they needed to get ahead of it. They decided to work with IBM to work on rerouting those planes in real life situations, like, last year’s hurricanes.
Not only was that plan successful, it was successful beyond their wildest dreams. Integrating their cloud strategy with machine learning is now a pairing that they’ll continue to pursue.
Hearing many more case studies from IBM customers, it was clear that they all had business-critical objectives that they were trying to meet. American Airlines was working towards improving their customer service in one of the most painful areas of their business – for the passengers, for the pilots, and for the crew. The adoption of these cutting edge technologies was secondary to meeting that huge pain point.
This was a key takeaway for us: the improvement was the goal, not cloud migration or the adoption of some other cool DevOps technology.
In practically every customer example that showed up on IBM’s stage, data sat at the core for each of these customers; data that, in most cases was growing in size and complexity and which served as a major bottleneck to bring the promise of this new innovation to life. Moving data into clouds and machine learning landscapes can take such a long time that the insights generated by these technologies grow stale
Just this week, in a call discussing the recent acquisition of Mulesoft, SalesForce COO Keith Block said that he "is hearing from almost every CEO he talks to that they need to unlock the data in their legacy systems to drive their digital transformation processes." This is exactly the same sentiment that the IBM customers on stage at IBM think we talking about as well. The good news is, as we partner more and more with IBM, we will be tackling this journey with our joint customers together and ensuring data is not a bottleneck going forward.