Predictive IT Improves Reliability & Controls Outages

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The rapid evolution of technology across industries has been a double-edged sword. With the technologies like artificial intelligence and machine learning, organizations can now do more than respond after the fact and instead take a proactive approach to IT operations. Predictive analytics is the use of advanced analytic techniques that leverage historical data to uncover real-time insights and to predict future events. The use of predictive analytics is a key milestone on your analytics journey — a point of confluence where classical statistical analysis meets the new world of artificial intelligence. Predictive analytics can help you transform the way your business operates by delivering value. But how do you know when is the right time to adopt these practices?



The answer is simple: the time is now. Today’s unprecedented convergence of intuitive tools, new predictive techniques and hybrid cloud deployment models makes predictive analytics and modelling more accessible than ever before. As per IBM, for the first time, organizations of all sizes can have the tools to embed predictive analytics into their business processes and to harness AI at scale. Enterprises now have the power to extract value from previously unexplored “dark data”— including everything from raw text to geolocational information. If your organization can evolve from departmental, small-group AI projects towards an enterprise data science platform, you stand to gain significant competitive advantage. Those who don’t seize the opportunity might risk falling behind their competitors.


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    Predictive IT Improves Reliability & Controls Outages

    The rapid evolution of technology across industries has been a double-edged sword. With the technologies like artificial intelligence and machine learning, organizations can now do more than respond after the fact and instead take a proactive approach to IT operations. Predictive analytics is the use of advanced analytic techniques that leverage historical data to uncover real-time insights and to predict future events. The use of predictive analytics is a key milestone on your analytics journey — a point of confluence where classical statistical analysis meets the new world of artificial intelligence. Predictive analytics can help you transform the way your business operates by delivering value. But how do you know when is the right time to adopt these practices?



    The answer is simple: the time is now. Today’s unprecedented convergence of intuitive tools, new predictive techniques and hybrid cloud deployment models makes predictive analytics and modelling more accessible than ever before. As per IBM, for the first time, organizations of all sizes can have the tools to embed predictive analytics into their business processes and to harness AI at scale. Enterprises now have the power to extract value from previously unexplored “dark data”— including everything from raw text to geolocational information. If your organization can evolve from departmental, small-group AI projects towards an enterprise data science platform, you stand to gain significant competitive advantage. Those who don’t seize the opportunity might risk falling behind their competitors.


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    For instance the healthcare sector is the most critical sector, you want to respect the patient, understand the way operations are happening, how patients are monitored, how things can become more effective for nurses in how they administer treatments, all these kinds of aspects. By knowing all this, your solution - your technology - will be different and more effective. It’s basically a single source of truth, through which you’re getting data from the different critical systems in the data centre and you are bringing them together to really get the key outcome. By having this information available, you can far easier understand a problem, go deeply into it, find its root cause and then solve it faster.

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