TDWI research reaffirms the majority of organizations are challenged with the scarcity of data scientists, and they plan to “upskill their business analysts to build. The process requires collaboration between data scientists to train and tune models, and data engineers for data preparation and integrating model predictions into analytics. Similarly, TDWI’s Analytics Maturity Model defines “The Chasm” as challenges organizations must overcome to benefit from advanced analytics.Īmong the leading challenges that stymie analytics maturity is a skill deficit-a problem affirmed by surveys conducted by Gartner, Deloitte, and McKinsey & Company.Īdvanced analytics that enable foresight have historically required scarce resources to develop predictive models using techniques like machine learning (ML). Yet, analysts like Gartner report that “87 percent of organizations have low business intelligence (BI) and analytics maturity,” as they are limited to hindsight.
It also enables customer churn or employee attrition prediction to help drive proactive action.
Organizations that have foresight into their business have a competitive advantage.įoresight can enable demand forecasting to optimize the supply chain, inventory, and avoid lost opportunities. By Dylan Tong, Global Segment Lead Architect, AI Augmented Analytics – AWSīy Holt Calder, Data Architect – InterWorksīy Madeleine Corneli, Sr.
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