Artificial intelligence is impacting all aspects of the business, including enterprise search and big data applications. But it comes with some challenges Businesses have been relying on search and big data analytics for many years to gain insight into their data.
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In recent years, these technologies have evolved rapidly and now incorporate machine learning and artificial intelligence, and they increasingly allow enterprises to more fully integrate their big data results into business action, whether it be for customer service, assembly line production, precision medicine or any of a number of other business use cases.
Big data applications today must be built to provide real-time results for businesses to compete in today’s fast-moving marketplace. Powered by search and big data, artificial intelligence (AI), machine learning, natural language processing (NLP) and cognitive (or “intelligent”) search are leading the way.
As we enter this new age, the time is near for businesses to incorporate these technologies — though they must be cognizant of the challenges that exist and the resources that will be required.
Using Search to Deliver Big Data Analytics
As the result of the growing demand for AI, machine learning and NLP applications, a tremendous amount data is being pulled into big data platforms at massive scale. And, as the volume of data grows rapidly, organizations are increasingly seeking intelligent information discovery and analytics platforms. Navigating a traditional SQL database or typing in keywords is no longer enough!
In recent years, we’ve seen a shift toward search engines becoming the preferred mechanism for the output and delivery of complex big data applications. Examples include visualization dashboards and question-answering systems. In 2017, we stepped into a new era where search engines have become an integral part of big data, providing natural, total and proactive search and insight discovery.
New Technologies for Better Big Data
Artificial intelligence has been around for a long time, but for many enterprises seeking to extract more meaning from their data, the future is now. A recent Gartner report finds that expectations will soar for AI-enabled assistance as it becomes pervasive in consumer services and customer/citizen-facing applications using virtual support assistants. And, according to this report, AI and machine learning investments are already in the top five CIO priorities. […]
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Artificial intelligence is impacting all aspects of the business, including enterprise search and big data applications. But it comes with some challenges Businesses have been relying on search and big data analytics for many years to gain insight into their data.
copyright by www.cmswire.com
In recent years, these technologies have evolved rapidly and now incorporate machine learning and artificial intelligence, and they increasingly allow enterprises to more fully integrate their big data results into business action, whether it be for customer service, assembly line production, precision medicine or any of a number of other business use cases.
Big data applications today must be built to provide real-time results for businesses to compete in today’s fast-moving marketplace. Powered by search and big data, artificial intelligence (AI), machine learning, natural language processing (NLP) and cognitive (or “intelligent”) search are leading the way.
As we enter this new age, the time is near for businesses to incorporate these technologies — though they must be cognizant of the challenges that exist and the resources that will be required.
Using Search to Deliver Big Data Analytics
As the result of the growing demand for AI, machine learning and NLP applications, a tremendous amount data is being pulled into big data platforms at massive scale. And, as the volume of data grows rapidly, organizations are increasingly seeking intelligent information discovery and analytics platforms. Navigating a traditional SQL database or typing in keywords is no longer enough!
In recent years, we’ve seen a shift toward search engines becoming the preferred mechanism for the output and delivery of complex big data applications. Examples include visualization dashboards and question-answering systems. In 2017, we stepped into a new era where search engines have become an integral part of big data, providing natural, total and proactive search and insight discovery.
New Technologies for Better Big Data
Artificial intelligence has been around for a long time, but for many enterprises seeking to extract more meaning from their data, the future is now. A recent Gartner report finds that expectations will soar for AI-enabled assistance as it becomes pervasive in consumer services and customer/citizen-facing applications using virtual support assistants. And, according to this report, AI and machine learning investments are already in the top five CIO priorities. […]
read more – copyright by www.cmswire.com
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
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