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Analytics in sentence

102 examples of Analytics in a sentence

And there's video analytics that are tracking our movements.
Turns out, the analytics here are easy, simple.
The analytics are easy here.
The technologies that are coming, high-performance computing, analytics, big data that everyone's talking about, will allow us to build predictive models for each of us as individual patients.
It brings together intelligent machines, advanced analytics, and the creativity of people at work.
Increasingly sophisticated analytics then sift through the data, providing insights that allow us to operate the machines in entirely new ways, a lot more efficiently.
Another medical center, in Washington state, is piloting an application that allows medical images from city scanners and MRIs to be analyzed in the cloud, developing better analytics at a lower cost.
And to be sure, new high-skilled jobs will be created: mechanical digital engineers who understand both the machines and the data; managers who understand their industry and the analytics and can reorganize the business to take full advantage of the technology.
So Andrew asked me if I'd want to maybe work with him a bit, work on some of the math and the analytics and see if we could figure out something we could do.
We didn't even know who was in our criminal justice system, we didn't have any data about the things that mattered, and we didn't share data or use analytics or tools to help us make better decisions and to reduce crime.
I wanted to introduce data and analytics and rigorous statistical analysis into our work.
So when I started my job at the Arnold Foundation, I came back to looking at a lot of these questions, and I came back to thinking about how we had used data and analytics to transform the way we did criminal justice in New Jersey.
So I decided to focus on using data and analytics to help make the most critical decision in public safety, and that decision is the determination of whether, when someone has been arrested, whether they pose a risk to public safety and should be detained, or whether they don't pose a risk to public safety and should be released.
What we need in this space are strong data and analytics.
We're now working on risk tools for prosecutors and for police officers as well, to try to take a system that runs today in America the same way it did 50 years ago, based on instinct and experience, and make it into one that runs on data and analytics.
And soon, we'll turn our attention to launching a constellation of 24 or more of these satellites and beginning to build the scalable analytics that will allow us to unearth the insights in the petabytes of data we will collect.
The fact is, it would be irresponsible of us not to rigorously test our designs when so many people are counting on us to get it right, but data analytics will never be a substitute for design intuition.
He was teaching himself to communicate, but we were looking in the wrong place, and this is what happens when assessments and analytics overvalue one metric — in this case, verbal communication — and undervalue others, such as creative problem-solving.
We've seen examples here of extraordinary innovation, and much of it coming from this room, The police are engaging in predictive analytics.
And four years later, we're analyzing over 25 million transactions, providing real-time analytics on thousands of sneakers.
Sneakerheads can track the value of their collection over time, compare it to others, and have access to the same analytics you might for your online brokerage account.
One reason for that is, the data analytics that drive the internet get us not just more information, but more of the information that we want.
But what's most exciting is that we help humanitarian and service organizations collect the data and the analytics that's necessary to understand the changing needs of newcomers in real time.
I provided the data and the analytics to help businesses reduce food waste at the source by letting them know the items that they waste repeatedly on a regular basis, and they even saved millions of dollars.
We use CAT scans, we use isotopes, we use genomes, we use robots, we use mathematical simulations and all kinds of analytics.
With the proliferation of so-called people analytics – behavioral and intelligence tests, digital performance scorecards, and better information systems – companies know their workers like never before.
This brings us to the second part of the argument against optimism: analytics.
So, despite the Brexit unknowns, they are continuing to invest in future-oriented areas like cloud computing, artificial intelligence, and data analytics.
Cheaper sensors and better data analytics are already enabling infrastructure operators to track maintenance issues and predict investment obsolescence more accurately, and in real time.
Indeed, machines are becoming smarter, with innovations like advanced robotics, 3D printing, and big data analytics enabling companies to save money by eliminating even highly skilled workers.
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