2. Welcome
Steve Ressler
Founder & President
GovLoop
- Tweets: #gltrain
- Slides, Video archive & other resources will be emailed to
you later this week.
- Check out the GovLoop VIP
programhttp://www.govloop.com/TrainingVIPs
- Be sure to fill out the evaluation to obtain your 3 CPE’s at
the end of the event.
3. The Data Revolution
“As we sit on the cusp of remarkable
innovations, we must remember that
this time, modern innovations are
powered by data.”
4. Our Goals - GovLoop Research
• Our research: empower and educate
• Our basic formula:
– Survey of GovLoop Audience
– Case study from state, local and federal government
– Best practices, challenges
– Cheat sheet
• Our mission: Help you do your job better
5. What You’ll Find in the Report
• A local government spotlight
showing how the city of Louisville,
KY., has leveraged data to improve
services
• A federal government case study
highlighting the Army’s Enterprise
Management Decision Support
program.
• Industry insights on the current
big data landscape.
• 8 Strategies and best practices for
smart big data adoption and
analysis.
• GovLoop’s big data cheat sheet.
7. Defining Big Data
“Big Data refers to the massive amounts
of data that collect over time that are difficult to
analyze and handle using common database
management tools.” – PC Magazine
The Method for an Integrated
Knowledge Environment open-source
project. The MIKE project argues that
big data is not a function of the size of
a data set but its complexity.
Consequently, it is the high degree of
permutations and interactions within a
data set that defines big data.
The National Institute of Standards
and Technology. NIST argues that big
data is data which “exceed(s) the
capacity or capability of current or
conventional methods and systems.”
In other words, the notion of “big” is
relative to the current standard of
computation.
Definitions from: The Big Data Conundrum: How to Define It?
8. A Working Definition
“Big data is a term describing the storage
and analysis of large and or complex data
sets using a series of techniques
including, but not limited to: NoSQL,
MapReduce and machine learning.”
See full study: Undefined By Data: A Survey of Big Data Definitions
- Jonathan Stuart Ward and Adam Barker, School of Computer
Science, University of St. Andrews, UK.
9. Do we care?
• Leveraging data in new ways to meet
mission need.
• Unlocking new insights by synthesizing
data across your department
• Collaborating and sharing resources
12. Social Welfare
• The oldest case is the Famine Early Warning Systems
Network (FEWS NET) developed by U.S. Agency for
International Development in 1986.
• The $25 million dollar program helps optimize the
distribution of up to $1.5 billion dollars per year in USAID
Food for Peace assistance.
13. Smarter Healthcare
• Predicting the likelihood of hospitalization or death
within 90 days, the Patient Care Assessment System
(PCAS) calculates the Care Assessment Needs (CAN)
Score.
• This score allows the Veterans Health Administration
(VHA) to focus care teams and proactively care for
their patients.
• The system collects 120 unique elements for 5.25
million patients and is supported by an 80-terabyte
corporate data warehouse.
14. Biometric Intelligence
• Since 2003, US armed forces have collected biometric
information from non-US citizens in Iraq and Afghanistan.
• It identifies enemy combatants and permits access into
controlled areas.
• The system, known as The Automated Biometric
Identification System (ABIS), stores 4.4 million unique
identities and has identified over 3,000 enemy
combatants, added 190,000 identities to the watch list,
and protected the welfare of the United States and its
allies.
15. Big Data’s Challenges – From the
Survey
• Data governance
• Data locked in legacy systems
• Unclear mission and goals
• Lack of support
• Lack of clarity on metrics
16. Big Data’s Core Challenge
How do we find the needle in the
haystack…when the haystack keeps
getting exponentially bigger?
26. Where to begin?
• What problem are we trying to solve?
• How do we engage the right people?
• How do we break down silos?
• What kinds of data do we need?
• What do I need to be able to do with the data?
• Who needs access and when?
• Can I leverage existing technology my agency has?
• What does success look like?
27. Before we wrap up…
Today, public service
offers a unique
opportunity
Photo license: by Pa1nt, FlickR Creative Commons