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1 Using Big Data Analytics to Improve Government Performance Arun Chandrasekaran Gartner is a registered trademark of Gartner, Inc. or its affiliates. This publication may not be reproduced or distributed in any form without Gartner's prior written permission. If you are authorized to access this publication, your use of it is subject to the Usage Guidelines for Gartner Services posted on gartner.com. The information contained in this publication has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information and shall have no liability for errors, omissions or inadequacies in such information. This publication consists of the opinions of Gartner's research organization and should not be construed as statements of fact. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner's Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see "Guiding Principles on Independence and Objectivity."

2 The Nexus of Forces Is Driving Innovation in Government Extreme Networking Rampant Access Rich Context, Deep Insights Global Class Delivery

3 Government Information Is a Public Asset Are you getting the most business value from your data?

4 Key Issues 1. How does big data enhance analytic capabilities in government? 2. What decisions and steps are needed to gain value from big data analytics? 3. What are public sector use cases for big data analytics?

5 Strategic Planning Assumptions By 2015, more than 30% of analytic projects will deliver insights based on structured and unstructured data. Correlating, analyzing, presenting, and embedding insights from structured and unstructured information together enables government agencies to better personalize the constituent experience and identify opportunities for efficiencies, innovation, and even new business models.

6 Key Issues 1. How does big data enhance analytic capabilities in government? 2. What decisions and steps are needed to gain value from big data analytics? 3. What are public sector use cases for big data analytics?

7 Government CIOs Have More Sources of Information to Do More With Descriptive Analytics What happened? What should happen? Enterprise "Dark Data" Documents Operational Social IT/OT Open Open Data Text Transactional Data Audio Search Engine Social Image Commercial Diagnostic Analytics Why did it happen? What will happen? Prescriptive Analytics Video Public Mobile Predictive Analytics

8 Linking, Mining, and Sharing Data Expand Information Management Practices How In-line; Real Time Whose Social Government Offline; Batch Structured; "Simple" Explanatory; Historical What Unstructured; Linked Open Data More sources Social Data More relationships Predictive; Outcomes Why Shared Data Linked Data More stakeholders More context

9 Big Data Capabilities Capture the Business Value Big Data Capabilities Correlations and patterns from disparate, linked data sources yield the greatest insights and transformative opportunities Transactions Geographic Economic Contracts Sentiment Sensor Reports Monitoring Demographic Weather Mobile Network Industry Ability to Store and Process Unstructured Data Ability to Link Data of Various Types Ability to Affordably Perform Comprehensive Analysis Constituent Insights and Engagement Program and Outcomes Management Operations and New Services Risk Management and Public Safety Fraud Detection Primary Use Cases

10 Question Where Do Big Data Analytics Fit? Public Safety: Unknown Multidimensional Analysis Big Data Analytics Situation Analysis Crime Detection and Prevention Tax and Revenue: Fraud Detection Financial Management Transportation: Dynamic Road Charging Known Predefined Reports Statistical Analysis Fleet Management Policy Making: Citizen Sentiment Analysis Real-time Impact Analysis Well-defined Varied Data Structure

11 Key Issues 1. How does big data enhance analytic capabilities in government? 2. What decisions and steps are needed to gain value from big data analytics? 3. What are public sector use cases for big data analytics?

12 Acknowledge Big Data Analytics Initiatives Are Unique Technical Challenges and Opportunities Business Challenges and Opportunities

13 Typical Drivers for a Big Data Analytics Initiative Business Drivers: Cost-reduction opportunities Improved outcomes Changing priorities or use cases New business models Unused dark data Compliance (executive order or legislative action) Technology Drivers: Combination of structured and unstructured data Performance issues with enterprise data warehouses Traditional technology does not scale Technology cost reduction Program grant requirements Convergence of Business and IT

14 Business: Shared Analytics and Business Intelligence Infrastructure Road Map 1 Establish Strategy and Program Governance 2 Create a Business Intelligence Competency Center 3 Implement Information Governance 5 4 Create a Performance Management Framework Stand Up the Shared Analytics/BI Infrastructure 6 Analytics Deployment

15 IT: A Process Framework for Big Data as It Applies to the Logical Data Warehouse Big data is not new to users and IT is catching up. Users have long been combining linked data with BI analytics form partnerships with power users. Measure Implement Frame Problem Learning Library Execute and Interpret Design Analysis Gather Data Frame it! and throw out "not so" big data projects Design business and analytics hypothesis Gather data observe the contacts Execute prove, disprove, and refine Implement for business change Measure all aspects

16 IT: "Analytics" Data Warehouses Big Data Analytics Project Outline Big Data Analytics Project Steps Key Participants Key Objectives Frame Problem Design Analysis Gather Data Business leader, IT leader, EA, domain expert, project manager, chief data officer (CDO) EA, business analyst, machine learning expert, data mining engineer, data scientist and more Software engineer, network engineer, data architect, statistician, EA, and so on Is problem a big data problem? Gain mutual agreement on problem Formulate hypotheses Focus data exploration tasks Work with data sources Determine relevant data Execute and Interpret Implement Measure Machine learning expert, statistician, data miner, EA, data scientist and more Software engineer, network engineer, data analysts, and so on Financial partner, data analyst, business analyst, EA, and so on Technical skills to execute solutions Business skills to interpret outcomes Act upon big data insights Technical skills to implement BDA BDA production environment User training Business skills to implement change Create meaningful metrics Identify BDA success and failures

17 Key Issues 1. How does big data enhance analytic capabilities in government? 2. What decisions and steps are needed to gain value from big data analytics? 3. What are public sector use cases for big data analytics?

18 Big Data Analytics Initiatives in Government: Too Few and Far Between Key Law Enforcement Food Safety Fraud Detection Health Care Key National Security

19 Police Predict Predator's Position Opportunity - Increase the speed of Swedish police investigations Data and Analytics - Communication behaviour from phone calls in combination with crime statistics, weather, day-ofweek and city events - Analysed data from over 500,000 interrogations, evidence and background info using QlikView Results Reduced nine months of manual analysis to three minutes of automated analytics Helped locate a serial killer in the city of Malmö by calculating the time and location of the next shooting 6.7M krone reallocated from administration to law enforcement 18

20 NOAA s Ark of Weather Data Opportunity - Travel safety - Community preparation for weather related events Data and Analytics - 30 petabytes of data per year from 3.5 billion daily observations via satellites, ships, aircraft, buoys and other sensors - Sophisticated high-resolution predictive modeling Results - Generates millions of weather-related products per day including weather warnings and guidance for public and private sectors - Saves lives and expense via severe weather alerts National Oceanic and Atmospheric Administration 19

21 Using Predictive Analytics in Foster Care Case Management Social Services Healthcare School

22 Protecting Public Services With Context: Enhanced Fraud Detection Agency and Government Systems User and Entity Profiles Collective Network Analysis Transaction Profile

23 Recommendations Do not postpone the implementation of big data analytics, but develop an information management strategy first. Identify big questions relevant to big data. Understand big data technology capabilities and manage organizational impacts. Validate your big data assumptions in a proof of concept.

24 Recommended Gartner Research Invest in Information and Analytics to Benefit From Big Data Douglas Laney, Frank Buytendijk (G ) Toolkit: Big Data Business Opportunities From Over 100 Use Cases Frank Buytendijk, Lisa Kart, and others (G ) Information Governance in the Age of Big Data Svetlana Sicular (G ) Decision Point for Practical Big Data Use Cases Svetlana Sicular (G ) Predicts 2013: Business Intelligence and Analytics Need to Scale Up to Support Explosive Growth in Data Sources Daniel Yuen, Rita Sallam, and others (G ) For more information, stop by Gartner Research Zone.

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