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The biggest change has been the continued and rapid growth in interest in augmented analytics. For organizations to move to a culture of self-service business analytics in a world of big data takes more than just the right analytics skills, it takes embedded machine learning techniques, natural language interfaces and a focus on data storytelling to communicate business meaning.  

Too many organizations are getting distracted by the “shiny new thing of AI” without recognizing that the basics of analytics and BI not only deliver huge value in themselves, but are also a necessary component of an analytics strategy that stretches from traditional reporting to the undoubted potential of artificial intelligence (AI). Although most organizations have some type of analytics and BI capability already, thinking of this as a mature space overlooks continuous improvements in the automation of analytics processes that are delivering new insights across the organization at a previously unobtainable depth, speed and reach.

The value of analysis lies in its ability to challenge assumptions and change the status quo. As analytics and BI become ubiquitous across the organization, all parts of the business have the chance to recognize when old ways of thinking are no longer sufficient for modern digital business and so refine their decision making in the light of new data. In this era of continuous change, the need for a consistent, accurate way to uncover and establish new opportunities and challenges, and then establish a strategy to meet them is critical.

… lose their best employees and customers to those who do.

IT executives will see a variety of thought-leading frameworks that will put in context the mixture of real-world examples and survey data that showcase the best practices and actions other IT executives across a variety of industries and business models are pursuing.