Stonebraker focuses on the current market for Big Data products, specifically those that deal with one or more of “the 3 V’s.” On the one hand, the Volume problem for business intelligence applications is pretty well solved by data warehouse vendors. However, upcoming data science tasks are poorly supported at present. On the other hand, there is rapid technological progress, so we need to stay tuned. In the Velocity arena, recent “new SQL” and stream processing products are doing a good job, albeit with some storm clouds on the horizon. The Variety space has a collection of mature products, along with considerable innovation from startups. He identifies opportunities, particularly those enabled by possible disruption from new technology. And then there’s that 800-pound gorilla in the corner.

While organizations have dramatically more data readily available, few are leveraging this data for true competitive advantage. McKinsey found that data-centric companies are driving a 9-fold increase in customer loyalty and an almost 20-fold increase in customer profitability. As data and analytics leaders, you have the opportunity to drive organizational focus on identifying, curating, and leveraging valuable data to support better strategic decision making. Levitt shares information management frameworks and anectotes that highlight the value of thinking outside box, discusses critical success factors, and recommends specific actions to improve your organization's competitive advantage.

Lynda Partner, VP Analytics at Pythian and her team of big data and analytics professionals work to solve the toughest data challenges for their clients. As veterans in the continually-evolving big data space, her team has been helping clients break down their data silos by bringing together data from disparate sources, and enabling use cases from BI to ML. When it comes to big data they’ve seen it all. In this session, you will hear how data professionals like you are dealing with the most challenging issues with data and keeping up with innovations. Learn through real-world examples how you too can be ready to address tomorrow’s opportunities with ever-advancing cloud analytics technologies and emerging practices, — in other words, what’s coming and how can you maneuver today to take advantage.

Learn about next-generation cloud data warehousing and what it takes to deliver insights from real-time data economically and at scale with hybrid data regardless of location, in the cloud, on-premises or both, while you enjoy Boston's finest deep fried pastries!

Elsevier is a 130 year old company with a long legacy of providing quality content that serves professionals in their fields. Its digital transforming is aimed at transforming that content into actionable intelligence for users. However, digital transformation is not just a matter of updating legacy systems and workflows, it also requires the capacity to transform the entire business; from pricing models to company culture. In this talk, Deus explores Elsevier’s journey to transform its business so it is able to incorporate advanced technologies like machine learning and AI technology to better serve customers.

We find ourselves continuously copying, transforming, and aggregating data into various large scale, complex, proprietary systems for the purpose of Digital Transformation in order to gain some competitive edge. Unfortunately, this process ends up exacerbating the problem by creating more silos, complexity and making the process of extracting knowledge more difficult overall. Deyette reviews where we are, how we got here, and what must come next with regard to leveraging Big Data Analytics.

Companies are not lacking in technology options; in most cases, more advanced technologies exist than can be absorbed into the organization all at once. As data and analytics leaders, you need to determine how to make the biggest business impacts with advances in AI and ML for analytics, enable self-service with governance, and support BI and data engineering processes with the data lake. To establish this solid enterprise foundation, it is essential to recommit to data management principles and prioritize platform technologies and ecosystems accordingly. In his closing keynote, O’Brien shares a clear path forward based on the evolving concepts in data and analytics within the context of an enterprise-scale data strategy.