Past Meetup

Data Science for NOAA Chief Data Officer and Big Data Predictive Analytics

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66 people went

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• 6:30 p.m. Welcome and Introduction (New Tutorial and Mentoring) Slides (http://semanticommunity.info/@api/deki/files/31094/BrandNiemann11032014.pptx)

• Background: Data Science for NOAA Big Data (http://semanticommunity.info/Data_Science/Data_Science_for_NOAA_Big_Data) and DHS Global Terrorism Database (http://semanticommunity.info/Data_Science/Global_Terrorism_Database). See Big Data Symposia (http://semanticommunity.info/Big_Data_Symposia) Google Find: Department of Homeland Security and see Recent Presentation below

• Data Science for the NOAA Chief Data Officer Story (http://semanticommunity.info/Data_Science/Data_Science_for_the_NOAA_Chief_Data_Officer#Story) and Slides (http://semanticommunity.info/Data_Science/Data_Science_for_the_NOAA_Chief_Data_Officer#Slides)

• 7:00 p.m. Brief Member Introductions

• 7:10 p.m. Treeminer.com Video, Mark Silverman and Biplab Pal

• Background: Data Science for Vertical Data Mining (http://semanticommunity.info/Data_Science/Data_Science_for_Vertical_Data_Mining)

• Video Demo 1: HL7 classification: https://docs.google.com/file/d/0B8SK...Bna1pOeTQ/edit (https://docs.google.com/file/d/0B8SKiJjCk_TFWWM2VTBna1pOeTQ/edit) and Demo 2: How Treeminer works for document classification reference to a patent invalidation: https://docs.google.com/file/d/0B8SK...JiMjAtYXM/edit (https://docs.google.com/file/d/0B8SKiJjCk_TFSEV4bVJiMjAtYXM/edit)

• 7:30 p.m. Predictive Analytics in the Era of Big Data, Dave Vennergrund, Director, Data Analytics Center of Excellence, SalientFed Slides (http://semanticommunity.info/@api/deki/files/31197/Big_Data_Predictive_Analytics_Oct_2014_v2.pptx)

• I will discuss advanced analytic opportunities opened by the confluence of ever-expanding machine learning libraries and algorithms, unprecedented amounts of data, and the distributed computing platforms that support at-scale analysis of both relational and Big Data (HDFS) data structures. In addition, I will share lessons learned from past predictive analytic efforts in federal healthcare, intelligence, finance, personnel, benefits, improper payment, fraud detection, and tax analytics.

• I am responsible for leading and expanding innovations and best practices for the Salient Data Analytics Center of Excellence – in data science and predictive analytics. I have over 25 years of Federal R&D, IT management, solution development, and research experience. I have led dozens of successful business intelligence, predictive analytics, and data mining-based projects across the Federal government including budget forecasting for HUD and DOD; improper payment prevention for IRS, USDA, CMS, VA, DFAS, and OPM; and predictive modeling for DOI, EPA, US AID, and VA. I was the Director of CACI's (formerly Delta Solutions and Technologies, Inc.) Business Analytics Practice and built a service line that offered advanced business intelligence, big data solutions, data mining analytics, fraud detection, and predictive analytics. I spent over 14 years with SRA International, Inc. where I had founded a data mining center of excellence and a data warehousing practice. Recent publications at Predictive Analytic World Government 2011 (forecasting attrition at DOI) and 2012 (forecasting HUD housing budgets); Medicare and Medicaid Statistics and Data Analysis Conference 2011 (Fraud Detection method survey) and 2012 (Profiling providers with Big data methods). Masters in Computer Science (Artificial Intelligence) from Arizona State University 1986. Co-Chair KDD-2003.

• 8:30 p.m. Open Discussion8:45 p.m. Networking9:00 p.m. Depart

• Rescheduled to January 5th or February 2nd, 2015: Wolfram​ Alpha (http://www.wolframalpha.com/), Data Science Platform (http://www.wolfram.com/data-science-platform/), Discovery Platform (http://www.wolfram.com/discovery-platform/), Language (http://www.wolfram.com/language/?source=nav), and Data Summit​ 2014.​ (https://www.wolframdatasummit.org/2014/attendee/schedule/)

• Rescheduled to January 5th or February 2nd, 2015:Big Data Science for DHS, Qasim Hussain, COO, Greenzone Solutions, Inc. (http://www.greenzoneinc.com/)

• Recent Presentation (http://semanticommunity.info/Data_Science/Data_Science_for_Big_Data_Analytics#Day_One:_September_23.2C_2014) and Slides (http://semanticommunity.info/@api/deki/files/31139/Dennis-TTC__BigData_fl14.pdf): Stephen Dennis, Director, Innovation, Science and Technology Directorate, Department of Homeland Security, Big Data Analytics and Homeland Security

My Notes:

I don’t know what this “data” stuff is, but I want some of it…

DHS S&T Mission: Strengthen America’s security and resiliency by providing knowledge products and innovative technology solutions for the Homeland Security Enterprise (HSE)

Superstorm Sandy (Initial Findings) from NUSTL My Note: FAIRport this!

Statement of Big Data Problem in DHS

S&T’s Big Data Survey: Goal is to improve operational effectiveness and efficiency within the Department and HSE

Continue to work cultural issues that tend to plague big data

FEMA: Improved Utilization of Data Sets My Note: I worked on this!

Leveraging Leading-edge Data Science Research My Note: That is what he asked me to show him!

Big Data Lessons Learned

Determine what data exists and how it can it be manipulated to make it useful

End of My Notes