erepublic hawaii dgs 14 presentation -big data and analytics_michael stevens

8/10/2019 ERepublic Hawaii DGS 14 Presentation -Big Data and Analytics_Michael Stevens

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2013 IBM Corporation

Transforming Governmentwith Big Data & AnalyticsHawaii Digital Government SummitDecember 16, 2014

Michael D Stevens Government Solutions Manager

IBM Big Data & Analytics


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2014 IBM Corporation2

1. What are analytics? Why are they important?

2. What is Big Data? How can it improve analytics?

3. A Big Data & Analytics Platform

4. Whos using it?


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Big Data & Analytics is Transforming Government


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Different Types of Business Analytics

What actionshould I take?

Decisionmanagement

Why did ithappen?

Reporting,analysis, content

analytics

What couldhappen?

Predictiveanalytics

and modeling

What ishappening?

Discovery andexploration

Descriptive

Diagnostic

Predictive

Prescriptive

What didI learn,

whats best?

Cognitive

Be more right,

more often.


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Descriptive Analytics

What ishappening?


Where are we today?

Arrests, Budget, Potholes

Exploring Metrics and KPIs against targets


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Diagnostic Analytics

Why did it

happen?Reporting,Analysis

Root cause of event,Trend analysis, What if scenarios; text analytics



Predictive Analytics

What could

happen?Predictive Analyticsand

modeling

Build models, use past history to

determine what might happen given

specific scenarios and contributing factorsPredict occurrences of eventsStated as probabilities



Prescriptive Analytics

What action

should I take?Decisionmanagement

Deliver high-volume, optimized decisions to

both systems and front-line workers



Cognitive Analytics

What didI learn,

whats best?Cognitive


Decisionmanagement

Why did ithappen?

Reporting,analysis, content

analytics

What couldhappen?

Predictiveanalytics

and modeling

What ishappening?


Learning and improving over time

Natural Language



What is Big Data?


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By 2017 there will be more than 1 trillionconnected objects and devices on the planet

generating data.

80% of all data is unstructured and growing15 times the rate of structured data

There are 2.5 billion gigabytes of datagenerated every day

Over 500 billion tweets aresent every day (Twitter)

Data Its growing at massive scale and is the key toimproving analytics


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Data at Scale Data in Many Forms Data in Motion Data Uncertainty

olume riety elocity er city

Big Data is All Data


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Challenge in Government:

Data is Diverse, Structured, Unstructured and Growing

Finance

CrimeClaims Tax Intelligence

Environmental TrafficEmergency Logistics

Social Programs

Social MediaGeospatialImagery VideoSensors

Non-Traditional

DataSources

LargeVarietyof

Data


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Paradigm shifts enabled by big data & analytics

TRADITIONAL APPROACH

Analyze small subsets

of information

Analyzedinformation

Allavailable

information


Carefully cleanse information

beforeany analysis

Small amount ofcarefully organized

information

Hypothesis Question

DataAnswer


Start with hypothesis andtest against selected data

Repository InsightAnalysisData


Analyze data afterits been processedand landed in a warehouse or mart


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BIG DATA & ANALYTICS APPROACH


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What do these shifts enable us to do?

Predict and decide the best action

Cognitive computing

Intuitive analytics for everyone

Analytics as and when you need it

embedded in everything

Real-timeLearn to sense and predict using

all types of information

BIG DATA & ANALYTICS APPROACH

What wil lhappen and what should you do


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How Decision-Making is Changing

Decisions from Intuition Instinct Hunches Based on experience

Automated Decision-Making Knowledge, policies and practices

embodied in business rules Decisions made efficiently and

consistently

Objective

Quali ty and value of decision s

Predictive Decision-MakingAccurate predictions based onhistoric patternsLeverage all available dataFlexible, evidence-based decisions

Robust in volatile environmentsmodels re-generated from latestdata to reflects changing fashions,trends, etc.


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A Word About Predictive Analytics


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Its Tough to make predictions, especially about the future

-- Yogi Berra


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What is Predictive Analytics?

Predictive Analytics helps

connect data to effective action

by drawing reliable conclusions

about current conditions and

future events

Gareth Herschel, Research Director, Gartner

Group

Techniques:

Statistics

Game Theory

Data Mining


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Predictive Analytics in Our Daily Lives

Credit Score

Netflix

Pandora

Google

Amazon

Traffic

Portfolio Mgt.

Health Care

Fraud Detection

Underwriting

Risk Management

Customer Retention


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Preemptive GovernmentA New York Story

Problem: family died in a fire in a building that had

been illegally subdivided; 10s of thousands of complaints

Strategy: Assessing Fire Risk through Predictive Analytics.

Identify most dangerous of illegally subdivided housing units

Metrics:

Owners in financial distress

Multiple illegal-conversion complaints

Multiple family dwellings built before 1938 (code revision)

Low income/high-immigrant/low-employment neighborhoods

Data: agency reports, real-estate filings, finance & tax information

Findings: dwellings with all four risk categories 40 times more likely

to have a fire

Targeted 225 of hightest risk buildings

Moral: targeting all conversions captures many properties, but fails tofocus on those at most risk


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A Platform for Big Data & Analytics


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Landing,Explorationand Archivedata zone

Operationaldata zone

Real-time Data Processing& Analytics

Transaction andapplication data

Machine,sensor data

Enterprisecontent

Image,geospatial, video

Social data

Third-party data

Information Integration & Governance

DeepAnalyticsdata zone

EDW anddata mart

zone

A New Architecture to Manage Big Data

Data at rest and

data in motion

Structured and

unstructured

Inside and outside

the enterprise


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and improve analytics


Systems Security

On premise, Cloud, As a service

Storage

New/Enhanced

ApplicationsAll Data


Decisionmanagement

Landing,Exploration

andArchivedata zone

EDWand data

martzone

Operational data

zone

Real-time Data Processing &Analytics

What ishappening?


Why did ithappen?

Reporting andanalysis

What couldhappen?Predictive

analytics andmodeling

Deep

Analyticsdatazone

What didI learn,

whats best?

Cognitive


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Systems Security


Storage

New/Enhanced



Decisionmanagement


EDWanddatamartzone

Operationaldatazone


What ishappening?


Why did ithappen?




DeepAnalyti

csdatazone

What didI learn,

whats best?

Cognitive

Why did ithappen?

Reportingand analysis

Deep

Analytics

data

zoneOperational

data zone

and improve analytics


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A new architecture is required


Systems Security


Storage

New/Enhanced



Decisionmanagement


EDWanddatamartzone

Operationaldatazone


What ishappening?


Why did ithappen?




DeepAnalyti

csdatazone

What didI learn,

whats best?

Cognitive

Landing,

Exploration

and Archive

data zone

What ishappening?Discovery

andexploration


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A new architecture is required


Systems Security


Storage

New/Enhanced



Decisionmanagement


EDWanddatamartzone

Operationaldatazone


What ishappening?


Why did ithappen?




DeepAnalyti

csdatazone

What didI learn,

whats best?

Cognitive

What actionshould Itake?

Decisionmanagement

Real-time Data Processing &

Analytics


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New / Enhanced

Applications

All Data

Claims

Tax & Income

Threat & Crime

Case Worker

Social Media

Sensor

Images &Video

Outcome-basedProgram Mgt.

Real-timeFraud Detection

Real-time Threat

& Crime Detection

Audit & TaxCompliance

Patrol Deployment

Budget & FinanceOptimization

Big Data & Analytics Platform

Big Data & Analytics Strategy, Integration & Managed Services

Big Data & Analytics Infrastructure

What ishappening?


Why did ithappen?


What couldhappen?

Predictiveanalytics and

modeling

What didI learn,whatsbest?

Cognitive


Decisionmanagement



EDW anddata mart

zone


Real-time Data Processing & Analytics


Risk Determinatio

Case Management



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New / Enhanced

Applications

All Data

Claims

Tax & Income

Threat & Crime

Case Worker

Social Media

Sensor

Images &Video

Outcome-basedProgram Mgt.

Real-timeFraud Detection

Real-time Threat

& Crime Detection

Audit & TaxCompliance

Patrol Deployment

Budget & FinanceOptimization


Big Data & Analytics Strategy, Integration & Managed Services

Big Data & Analytics Infrastructure

What ishappening?


Why did ithappen?


What couldhappen?

Predictiveanalytics and

modeling

What didI learn,whatsbest?

Cognitive


Decisionmanagement



EDW anddata mart

zone


Real-time Data Processing & Analytics


Risk Determinatio

Case Management

Technologies in a Big Data & Analytics Platform

Data Integration

Master Data Management

Entity Analytics

Data Security & Privacy

Hadoop

Data Warehouse Appliance

Streaming PlatformBig Data Navigation

Predictive Analyics

Business Analytics

Case Management

Decision Management


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How are Government Agencies using Big Data &

Analytics?


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A state health agency optimizes use of tax dollars by using

pattern analysis to crack down on Medicaid fraud

99% reductionin potentially fraudulent claims,

from USD19.2 million to

USD138,000

Business Challenge: Rising Medicaid costs and a growing

sense that too many inappropriate payments are being made

The Smarter Solution: Powerful analytical models flagclaims and providers that dont follow the typical patterns

exhibited by their peer groups. By finding obscure

connections among doctors, pharmacists, labs and medical

supply companies, the solution also helps uncover extended

fraud networks.

USD49 millionrecovered through 22 criminalconvictions and 18 civil

settlements

USD200 millionin questionable claims

identified within first 12 months


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Medway Youth Trust Identifies At-risk Youth

Business Challenge: Fragmented, incomplete data from a

variety of state and local agencies hindered the goal of finding

permanency for at-risk youths.

The Smarter Solution: Sophisticated modeling and predictive

analytics on high volumes of text and data enablecaseworkers can uncover hidden patterns and relationships

and that might otherwise go unnoticed and use the insight to

determine just the right combination of services for each child

> 50% success rate with intervention cases by

accurate and early identification

250% improvementin accuracy of identification of

those at risk

Accurately predictwhether individual youths have a

high (>60%) of needing help in

the future


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City Event Monitoring

Background and resource

information displayed geospatiallyto quickly respond to incidents

Social media analytics to proactively

identify and monitor potential

incidents

Intelligent Video Analytics to identify

and correlate incidents


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TechAmerica Big Data Report Findings

1. Understand the Art of the Possible2. Identify 2-4 key business or mission requirements that develop

underpinning use cases that would create value for both the agency

and the public.

3.Take inventory of your data assets. Explore the data available both

within the agency enterprise and across the government ecosystemwithin the context of use cases.

4.Assess your current capabilities and architecture against what is

required to support your goals

5.Explore which data assets can be made open and available to the

public to help spur innovation outside the agency.


http://www.techamericafoundation.org/bigdata
http://www.techamericafoundation.org/bigdatahttp://www.techamericafoundation.org/bigdata


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Links & Contact Information

IBM Watson Video

http://www.youtube.com/watch?v=_Xcmh1LQB9I

IBM Big Data & Analytics Hub

http://www.ibmbigdatahub.com/

Michael D. Stevens

Government Solutions

IBM Big Data & Analytics

Ph: 720.395.3951

[email protected]

Twitter @stevens_m_d

Ibm.com/bigdata
http://www.youtube.com/watch?v=_Xcmh1LQB9Ihttp://www-01.ibm.com/software/data/bigdata/mailto:[email protected]://www.ibm.com/bigdatahttp://www.ibm.com/bigdatahttp://www.ibm.com/bigdatamailto:[email protected]://www-01.ibm.com/software/data/bigdata/http://www.youtube.com/watch?v=_Xcmh1LQB9I


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2014 IBM C ti

Thank You

erepublic hawaii dgs 14 presentation -big data and analytics_michael stevens

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