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Infuse Analytics with AI and Machine Learning

Analytics is expanding beyond merely providing historical insights. For decades, analyses have been largely limited to displaying information about what happened in the past. These analyses offer some insight into why things happened but very little information about what should be done in the future. The viewer of the information was expected to know what to do with the analysis. Today we can do more with our analytics. Artificial intelligence (AI) and machine learning (ML) can be used to predict outcomes and behaviors to help guide business personnel on which actions to take to accomplish their objectives. When coupled with analysis of what has happened in the past, these AI- and ML-based analyses offer a more complete picture than is otherwise available.

AI and ML analyses employ algorithms that improve their results – in effect, that learn – as more and more data is processed. Neither technology is new, but they have only recently gained wide adoption. This is because the algorithms used for AI and ML analyses can be extremely resource intensive, requiring large amounts of data as well as significant processing resources. Fortunately, the costs of these resources have declined, making it more economically feasible to use AI and ML more frequently.

 
 

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About the Author

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David Menninger

SVP and Research Director
Ventana Research

David Menninger is responsible for the overall direction of research on data and analytics technologies at Ventana Research. He covers major areas including artificial learning and machine learning, big data, business intelligence, collaboration, data science and information management along with the additional specific research categories including blockchain, data governance, data lakes, data preparation, embedded analytics, natural language processing (NLP) and IoT.