The New Year has brought many new resolutions for everyone, including data professionals. If Big Data conferences are on your 2019 to-do list, then it is time to scope out some of the best conferences that can help you learn about new technology, build your network, and adopt these new technologies in your SMB. Attending Big Data conferences can help anyone meet their responsibilities for data management. Almost all SMBs have actionable Big Data in their repositories right now. To use these sets of gargantuan data they need the next-gen artificial intelligence and machine learning technology.

The 2018 University of Delaware Department of Civil and Environmental Engineering "Big Data in Railroad Maintenance Planning Conference," held Dec. 13-14, spotlighted the progression the industry is making in dealing with Big Data--"converting the mountain of data collected by railway systems into effective maintenance planning information, with a focus on railway needs and practical applications. More than 200 students, consultants, suppliers and railroaders from both the freight and passenger sectors attended the fifth annual conference, organized by Dr. Allan M. Zarembski, Professor and Director of the university's Railroad Research and Safety Program. Federal Railroad Administrator Ron Batory was a featured speaker, along with presentations from such companies as Norfolk Southern, BNSF, CN, ENSCO, GREX, RailInc, Alstom, Uptake and VisioStack. The February 2019 issues of Railway Age and Railway Track & Structures will contain feature articles on the annual event. Following is a summary, as presented by David Staplin, consultant to HNTB, Amtrak Deputy Chief Engineer (retired) and University of Delaware Railroad Advisory Board Chairman, with additional reporting by railroad economist and Railway Age Contributing Editor Jim Blaze. "In prior years, the presentations focused on dealing with data, on potential," said Staplin. "This year, we are seeing more problems tackled and solved.

Amazon Web Services used a big data conference in the backyard of some of its largest government customers to showcase its AI and machine learning tools that are helping to funnel ever-larger volumes of data into its storage and computing infrastructure. Making a pitch for better data management tools like metadata systems, AWS executives addressing a big data conference in Tysons Corner, Va., said the the public cloud giant aims to go beyond democratizing big data to "demystify" AI and machine learning. The combination of organized data and analytics will accelerate the building and deployment of machine learning models, many that currently never make it to production. Those that are deployed often require up to 18 months to roll out, noted Ben Snively, a solution architect at AWS (NASDAQ: AMZN). Open source tools for model development often advance a generation or two in the time it takes many enterprises to develop, train and launch a machine learning model, he added.

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