Frontier

Examining

the

March 26, 2014#gltrain

Welcome

Steve ResslerFounder & PresidentGovLoop

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The Data Revolution

“As we sit on the cusp of remarkable innovations, we must remember that this time, modern innovations are powered by data.”

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

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.

GovLoop Survey Data

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?

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.

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

Convergence of Technology

You can’t talk about big data without thinking about cloud and mobile.

3 Big Data Case Studies

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.

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.

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.

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

Big Data’s Core Challenge

How do we find the needle in the haystack…when the haystack keeps

getting exponentially bigger?

Our Big Data Best Practices

1: Executive Leadership

2: Business Before Treasure

3: Know Thyself: Define Use Cases

4: Leverage Existing Resources & Augment

5: Integrate Legacy Systems

6: Partner With Industry

7: Focus on Governance and Data Quality

8: Have a Deep Bench - Train

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?

Before we wrap up…

Today, public service offers a unique

opportunity

Photo license: by Pa1nt, FlickR Creative Commons