Applying Governance to Business Processes

Alternative data and AI (artificial intelligence) are increasingly being explored by investors as ways to gain ESG and potentially water risk insights. In this Ceres Webinar, speakers Ashby Monk, PhD from Stanford and Steven Fortier and Dr. Toby Messier from Aquantix explore the reality and possible future use of alternative data, natural language processing and AI in developing new approaches to collecting and analyzing E. risks – particularly those related to water.

To compete in today’s digital economy, enterprises require new ways to expand AI across their entire organization. Nearly all firms want to do more with data science, but they don’t know where to begin or how to properly empower citizen data scientists to avoid common AI gone wrong accidents. In this session, we will discuss how to approach your journey into citizen data science with existing analytics talent. Proven best practices and lessons learned from successful early adopters of augmented data science will be shared. We will walk through example initiative roadmaps, recommended staffing, upskilling, mentoring and ongoing governance.

Your team is serious about ensuring database performance at scale. But legacy NoSQL technology could be eroding the impact of your achievements. Following best practices for efficient data modeling, query optimization and observability is fundamental. But their power can be limited – or enhanced – by specific database capabilities. Often-overlooked database innovations can serve as a force multiplier, paving a much smoother path to speed at scale (e.g., millions of read/write operations and millisecond P99 response).

If you missed out on all the trends for 2019 published in December, or even if you caught some of them, this one merits your time. We’ll be going into 2019 and beyond, since the winners will have an eye on the long view for the source of competitive advantage that is analytics. It is a fascinating, explosive time for enterprise analytics. It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.