“Advanced Analytics vs Artificial Intelligence: How Are they Different?”

(Janet Wagner, Zylotech, 15 November 2018)

"“Data is generated from just about everything --smartphones, cars, utility grids, appliances, wearables, social networking sites, weather satellites--. Companies use analytics to discover valuable business insights from many sources of data”."

Are Advanced Analytics (AA) and Artificial Intelligence (AI) synonymous terms? I present you hereby similarities and differences between them. 1) Predictive, prescriptive and AI-driven analytics, data mining, machine learning, forecasting and pattern matching are some of the analytical categories that fall under the heading of AA. AA is also a marketing term that can generate actionable business intelligence (BI) insights on a deeper level. In contrast, AI is an area of computer science that emphasizes simulation of human intelligence, and processes and understands natural language to interact with humans in a human-like way. 2) All analytic tools and AI models require quality data in order to make accurate predictions or to provide the best insights. Data scientists spend much time preparing data for use in models and business systems. However, Zylotech, one of the analytic tools, can automate data preparation tasks. 3) AA is broader than AI when it comes to analytics capabilities. However, Al use cases include autonomous vehicles, chatbots and automatic image tagging. AI involves the development of self-learning algorithms, which enable analytics tools to learn from and make assumptions based on data. Companies using advanced AI-powered analytics will have a competitive advantage over companies that are only using traditional business intelligence tools.

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