No More Half Fast: Improving US Broadband Download Speed. Georgetown University Data Science...
-
Upload
brittne-nelson-phd -
Category
Data & Analytics
-
view
2.983 -
download
0
Transcript of No More Half Fast: Improving US Broadband Download Speed. Georgetown University Data Science...
No More “Half-Fast”: Improving
US Broadband Download Speed
Georgetown University – 2015 Data Science
Capstone Brittne Nelson PhD, Amgad Sirag, Ernest S.
Approach and Overview
What?
• Broadband Data Story
• Research Problem
• Data Science Pipeline
So What?
• Data Visualization Story
• Findings
• Lessons Learned
Now What?
• Future Research
• Conclusions
WHAT?
There were communities with no broadband access
Every day, residents and businesses had limited or no access to resources, services, content, new customers, and new technology limiting opportunities and community empowerment
One day, the US government created the SBI to facilitate the integration of broadband and information technology into state and local economies
Because of that, states did more to quickly expand broadband to more areas
Because of that, the SBI, decision makers, and researchers-including us-were able to assess how broadband is being implemented across the US
Until finally, residents and businesses gained more access to resources services, content, new customers, and technology that empowered and gave them a competitive edge
Data Story
Benefits of Broadband• Increased job opportunities
• Increased employment opportunities due to telework
• Higher pay
• Increased economic security
• Recruitment of job seekers, especially in rural areas
• Increased access to and quality of healthcare
• Availability of a wide variety of entertainment
• Increased participation in everyday economic, social, and community life
• Improved social connections to existing friends and acquaintances
• Creation of new relationships based on common interests
• Improved social integration of minority populations
• More positive attitudes toward aging
• Higher levels of perceived social support and connectivity among seniors
• Lower prices for online purchases
• Improved variety of items available for purchase
• Better purchasing decisions based on online information
• Savings in time and money for online vs. paper-based activities
• Improved connectivity for social or political actionSources: Center for Social Inclusion,. (2010). The Promise and Challenge of Community Broadband Models. New York City: Center for
Social Inclusion.
Analytics ASR,. (2014). Final Report: Social and Economic Impacts of the Broadband Technology Opportunities Program. Potomac
Maryland.
Research Problem
• Does broadband availability and speed make a state’s economy and it’s residents competitive?
• When will every state reach 98% broadband connectivity?
• How are community economic features impacting or related to broadband development?
Hypotheses• Broadband speed and accessibility will cluster in
urban areas• Areas with more broadband speed will have lower
unemployment, more businesses, and larger populations
• Broadband growth is not consistent across all counties
• Based on past growth, broadband coverage is not expected to be available in 98% of all counties in 2016
Data Sources• National Broadband Map Maximum and Minimum Download Speed by
County, June 2011-June 2014
– National Telecommunications and Information Administration http://www.broadbandmap.gov/data-download
• Labor Force Data by County Annual Average, 2011-2013
– U.S. Department of Labor Local Area Unemployment Statistics http://www.bls.gov/lau/
• Demographic Population by County, 2010
– U.S Census Bureau http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
• Total Number of Business Establishments, 2011-2012
– U.S Census Bureau http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml
Resources
Data Science Pipeline
Sources: Ojeda, T., Murphy, S., Bengfort, B., & Dasgupta, A. (2014). Practical data science cookbook. Birmingham: Packt Publishing.
SO WHAT?
Switch to Tableau Data Visualization
Hypotheses Results• Broadband speed and accessibility will cluster in urban areas
• “URBAN” TOO DIFFICULT TO DEFINE GIVEN PROJECT TIMELINE, NOT ANALYZED
• Areas with higher broadband speed have lower unemployment, more businesses, and larger populations• NOT TRUE
• Broadband growth is not consistent across all counties• TRUE
• Based on past growth, broadband coverage is not expected to be available in 98% of all counties in 2016 • NOT ENOUGH DATA TO COMFORTABLY FORECAST
Summary of Findings
• Identified economic features are mild drivers of technology implementation specifically broadband speed.
• Broadband availability makes a state economy and it’s residents competitive.
• Implementing broadband is not the silver bullet to community development or economic growth, it should be incorporated with other economic and social features.
Lessons Learned
• Quantity of data is important for forecasting
• Source of data is important. SBI reports data from providers which makes it somewhat difficult to assess
• Plan a significant amount of time for data wrangling
• Master each step of the data science pipeline before moving on
• Operationalize more factors to provide a clear picture of relationships when identifying hypotheses
NOW WHAT?
Future Research • Develop a matched pairs analysis framework that
compares changes in the availability of broadband at the
state level between counties
• Measure how much of the growth in availability within
these counties occurred due to funding (Grants, Federal
Government, Private Organizations)
• Examine broadband’s long-term quantitative
extrapolations and impact on social and economics
• Index and model additional community factors such as
education, adoption, tax rate, etc in order to broadly
define economic impact
Conclusions
• There is a business case for continued focus on
broadband improvement
• Broadband improves the overall communities
• Drives economic development and shared
opportunities
• Improve quality of life across the United
States
Thank You to the Georgetown University 2015 Data Science Program
Faculty
Benjamin Bengfort
Allen Leis
Sacha Litman
Laura Lorenz
Salil Mehta
Tony Ojeda
(and lady!)
Questions?
ADDENDUM: TABLEAU STORY