The Industry's Premier Big Data Community Event DataWorks Summit Berlin 2018 will feature two full days of content in eight tracks dedicated to enabling next-generation data platforms. You'll hear industry experts, architects, data scientists, and open source Apache developers and committers share success stories, best practices, cautionary tales, and technology insights that provide practical guidance to novices as well as experienced practitioners of modern data infrastructure.
This year, I'm honored to be the chair of the Artificial Intelligence and Data Science track at the DataWorks Summit in San Jose. Reviewing the submissions and working with the experienced and sharp committee members has been an education in itself, in particular the chance to see what's trending in the open source world. My day-to-day data science work gives me the chance to dig into a few open source projects, but it's hard to find time to get an overview of which topics and projects are hot and worth exploring more deeply. The key topics emerging this year are deep learning, graph-based machine learning and model inference in production. Not surprisingly, the topics and tools around deep learning (DL) still top the list of big trends, and top-notch research in math and computation are driving progress across vision, speech and text.
IBM's Project DataWorks in action: A NYC-based startup that develops clean energy projects in American inner cities used Project DataWorks to build a cognitive application that performs a comprehensive energy audit of individual properties to simulate energy savings and ultimate determine the correct mix of high-efficiency technology to reduce each customer's energy consumption. IBM's Project DataWorks uses Watson Analytics to analyze and create complex visualizations IBM's Project DataWorks uses Watson Analytics and natural language processing to analyze and create complex visualizations with one line of code – like this one, which illustrates correlations between product purchases by customers of a sporting goods store. IBM's Project DataWorks helps users access and gain insights from the 90% of unstructured data that goes untapped by organizations (according to IDC). The Console pictured here provides a snapshot that categorizes and previews an organization's data assets for easy access while also providing a full audit trail that allows users to understand who else on their team is interacting with the data and how.
DataWorks Summit Berlin 2018 will feature two full days of content in eight tracks dedicated to enabling next-generation data platforms. You'll hear industry experts, architects, data scientists, and open source Apache developers and committers share success stories, best practices, cautionary tales, and technology insights that provide practical guidance to novices as well as experienced practitioners of modern data infrastructure.
The time for enterprises to gain market advantage through Artificial Intelligence is now. Already many AI-enabled advances are transforming business processes and customer experiences, but the vast majority of AI-enhanced use cases are still to be discovered, developed, and deployed. In order to discover and capture the value available through deployed AI, new deep learning techniques are the focus of feverish research and development in academia and business. However, even successful AI experiments are often never deployed to business operations, resulting in wasted effort, time, and money, and leaving businesses dangerously exposed to competitors that have integrated AI into their ongoing operations. Experimentation with AI is essential to realizing the promise of AI, but enterprises face substantial risks that their experiments with AI, even successful ones, will do nothing to improve their business outcomes.