PPT-SIGDSA Workshop: Analytics and Visualization with SAS

August 14 th 2019 Ron Freeze University of Arkansas Rhonda Syler University of Arkansas Lakshmi Iyer Appalachian State University Liz Moran SAS Academic Programs James Harroun SAS Academic Programs. Nicholas Del . Rio. University of Texas at El Paso Computer Science. Workshop Objectives. U. nderstand . notion . and purpose of visualization . queries. Understand why writing queries may be easier that writing visualization programs. Ray Hoff (UMBC). Amy Huff (Battelle Memorial Inst.). Shobha. . Kondragunta. (NESDIS). AQPG is in its third year. Two Workshops have followed this paradigm:. 3. rd. AQPG Workshop. Was to be held on November 1, 2012, but defeated by Sandy… now will be held March 14, 2013. Information . Visualization and . Visual Analytics. Remco Chang. Associate Professor. Computer Science, Tufts University. Human + Computer. 1. http://www.collisiondetection.net/mt/archives/2010/02/why_cyborgs_are.php. Senior Database Specialist. Division of Management Information. Kim Nystrom. Management Methods Analyst. Office of Undergraduate Admissions. Data Visualization: . Branching out Beyond Excel. Getting to this point. Philip Kim. Senior Director, Big Data and Analytics. UNDER ARMOUR. ®. pkim@underarmour.com. Overview. OPPORTUNITY. CENTER THE VISION. TECHNICAL ARCHITECTURE. USER STORIES. ENGAGEMENT MODEL DESIGN. TEAM STRUCTURE. Remco Chang. Assistant . Professor. Department of Computer Science. Tufts University. Big Data Visual Analytics:. A User-Centric Approach. “The . computer is incredibly fast, accurate, and stupid. Man is unbelievably slow, inaccurate, and brilliant. The marriage of the two is a force beyond calculation. Yair . Levy, Ph.D.. Graduate . School of Computer and Information . Sciences . Michelle M. . Ramim. , Ph.D.. Huizenga School of Business and Entrepreneurship . “Procrastination . is the art of keeping up with yesterday. VOLUME. VARIETY. VELOCITY. VALUE. TODAY. THE FUTURE. DATA SIZE. THRIVING IN THE BIG DATA ERA. High performance computing. Computers have become increasingly powerful.. Required for Big Data Analytics. Principles of Data Visualization. Focus of this Course. Analyze. Communicate. Manage. …using data. Discuss (5 minutes). From reading Matchmaking with Math, what is a good definition of . analytics. Industry Landscape. BIG. DATA. Data that is . TOO LARGE . & . TOO . COMPLEX . for conventional data tools to capture, store and analyze.. Shares traded on US Stock Markets each day:. 7 Billion. Data generated in one flight from NY to London:. Challenges . and Opportunities. Remco. Chang. Tufts University. Visual Analytics = Human Computer. Visual analytics . is . “the . science of analytical reasoning facilitated by visual . interactive . (Insights on AACSB Curriculum Design). Workshop Coordinators:. Paul . Cronan. , Ron Freeze & Rhonda Syler. Sam M. Walton College of Business. , University of Arkansas. Faculty & Industry Representatives. It’s no secret that this world we live in can be pretty stressful sometimes. If you find yourself feeling out-of-sorts, pick up a book.According to a recent study, reading can significantly reduce stress levels. In as little as six minutes, you can reduce your stress levels by 68%. Expanding . Analytics . Offerings. Data, Analytics, and Statistics Instruction . DSI . 2016 . Austin, TX. Kellie Keeling. Department of Business Information & Analytics. University of . Denver (DU).