Analytics and BI platforms are rapidly transforming from focusing on enabling the analyst to augmenting the consumer. This is being driven by a convergence of capabilities including, conversational and consumer experiences and augmented analytics, a disruptive trend that leverages machine automation and AI to transform how data is prepared, how insights are generated and shared and how data science and ML models are created and operationalized. This presentation provides insight into how you can prepare for and leverage these market disruptions in your organization.

Modernize your analytics and BI capabilities by selecting the products that best meet your needs. See side-by-side, scripted demonstrations of four leading vendors. What are the key features to consider and how do they compare in action? How can you improve your own evaluation process and internal proofs of concept? What are the main strengths and weaknesses of these vendors?

This networking reception will explore three main topics: Empowering Women For and With Each Other — Addressing gender bias between women and how they can support each other up the leadership ladder. Engaging Men to Advance Women — How men can help women work to their full capacity as leaders — and why they would want to. Removing Institutional Barriers and Blind Spots — Whether gender bias is subtly build into the system or does its damage unconsciously, there is clear path to eliminating it.

Data and analytics is becoming strategic to organizations as they digitally transform. Yet, most organizations don’t have a systematic way to assess and optimize their data and analytics (including AI) investment options. This presentation details Gartner's Return Opportunity Appetite Risk (ROAR) Portfolio Optimization Model is a framework to help CDOs, CIOs and data and analytics leaders across the organization identify, prioritize and select combinations of investments in data and analytics (value streams) that align to key business initiatives and strategic intent.

AI is not the only thing driving rapid change in data and analytics. From the next generation of augmented analytics tools to the use of continuous intelligence to interpret streams of data from IoT or the potential of intuitive interfaces, there is rapid evolution in how and where analysis can be deployed. Understanding the business impact of these changes will allow organizations to prioritize the innovations that will drive digital business.