ABSTRACT
Data and analytics leaders must examine the impact on business and adjust their operating, business and strategy models accordingly. Virtually every aspect of data management, analytics content, application development and sharing of insights uses machine learning and artificial intelligence techniques to automate or augment manual tasks, analytic processes and human insight to action. By 2021, natural language processing and conversational analytics will boost analytics and business intelligence adoption from 35% of employees, to over 50%, including new classes of users, particularly front-office workers. By 2022, every personalised interaction between users and applications or devices will be adaptive. The expanded and strategic role of data and analytics in digital transformation is increasing the complexity of data, the number of variables to be analysed, the types of analysis and the speed of analysis required for success.
