Big Data e BI voltados a estratégias em governo e definição de políticas e serviços públicos

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1 Big Data e BI voltados a estratégias em governo e definição de políticas e serviços públicos Claudio Chauke Executive Partner claudio.chauke@gartner.com 23 Gartner, Inc. and/or its affiliates. All rights reserved. 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."

4 Key Issues. Smart and Digital Government! 2. How does big data enhance analytic capabilities in government? 3. What decisions and steps are needed to gain value from big data analytics? 4. What are public sector use cases for big data analytics? 24 Gartner, Inc. and/or its affiliates. All rights reserved.

5 The Nexus of Forces Is Driving Innovation in Government Extreme Networking Rampant Access Rich Context, Deep Insights Global Class Delivery 24 Gartner, Inc. and/or its affiliates. All rights reserved.

7 Four Phases of Technology in Government: Toward Smart and Digital Joined-up Government: Life events Back-office re-engineering Open Government: Transparency, participation, collaboration Community engagement Smart Government: Sustainability Affordability Crossing boundaries Digital Government E-government: Online services Multiple websites Gartner, Inc. and/or its affiliates. All rights reserved.

8 Top Strategic Technology Trends for Smart Government Top Government Technology Trends Social Mobile Information Cloud. Personal Mobile Workplace ü ü 2. Mobile Citizen Engagement ü ü 3. Big Data and Actionable Analytics ü ü 4. Cost-effective Open Data ü ü 5. Citizen-managed Data ü ü ü ü 6. Hybrid IT and Cloud ü ü 7. Internet of Things ü ü ü 8. Cross-domain Interoperability ü ü 9. BPM for Case Management ü ü.gamification for Engagement ü ü 24 Gartner, Inc. and/or its affiliates. All rights reserved.

9 Actionable Analytics From Big Data: More Than More I C Descriptive: What happened? What is happening? Diagnostic: Why did it happen? What key relationships? Predictive: What will happen? What if? How risky? Prescriptive: What should happen? How can I optimize? Perishability Validation Classification Technology Velocity Fidelity Linking Contracts Pervasive Use Volume Public Safety: Situation Analysis Crime Detection and Prevention Tax and Revenue: Fraud Detection Financial Management Transportation: Dynamic Road Charging Fleet Management Policymaking: Citizen Sentiment Analysis Real-time Impact Analysis Variety 24 Gartner, Inc. and/or its affiliates. All rights reserved. Complexity

10 Cross-domain Interoperability: Scalable by Design Focus on the right information, the right patterns, and the right characteristics for information sharing. I C Source: National Information Exchange Model (NIEM) 24 Gartner, Inc. and/or its affiliates. All rights reserved.

12 Strategic Planning Assumptions By 25, more than 3% 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 Gartner, Inc. and/or its affiliates. All rights reserved.

13 Government Agencies Have More Sources of Information to Do More With Descriptive Analytics Enterprise "Dark Data" What happened? Documents What should happen? 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 24 Gartner, Inc. and/or its affiliates. All rights reserved.

14 Linking, Mining, and Sharing Data Expand Information Management Practices Whose How In-line; Real Time Open Data Social Data Shared Data Linked Data More sources More relationships More stakeholders More context Social Government Offline; Batch Structured; "Simple" Explanatory; Historical What Unstructured; Linked 24 Gartner, Inc. and/or its affiliates. All rights reserved. Predictive; Outcomes Why

15 Big Data Capabilities Capture the Business Value 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 Big Data Capabilities 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 24 Gartner, Inc. and/or its affiliates. All rights reserved.

16 Where Do Big Data Analytics Fit? Public Safety: Question Unknown Known Multidimensional Analysis Predefined Reports Big Data Analytics Statistical Analysis Situation Analysis Crime Detection and Prevention Tax and Revenue: Fraud Detection Financial Management Transportation: Dynamic Road Charging Fleet Management Policy Making: Citizen Sentiment Analysis Real-time Impact Analysis Well-defined Varied Data Structure 24 Gartner, Inc. and/or its affiliates. All rights reserved.

19 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 24 Gartner, Inc. and/or its affiliates. All rights reserved.

20 Business: Shared Analytics and Business Intelligence Infrastructure Road Map Establish Strategy and Program Governance Create a Business Intelligence Competency Center Implement Information Governance Create a Performance Management Framework Stand Up the Shared Analytics/BI Infrastructure 6 Analytics Deployment 24 Gartner, Inc. and/or its affiliates. All rights reserved.

21 The Information-Driven Enterprise: 4 Pillars for Successful Business Analytics It s important to leverage what we already have in terms of data, 24 Gartner, Inc. and/or its affiliates. All rights reserved. people, process and tools. 2

23 Business: Shared Analytics/Business Intelligence User Profiles User Profile Operational Analyst/Line Workers Business Analyst/Unit Lead Quantitative Analyst/Quality Assurance Analyst Manager Executive Potential Future Capacity Supports worker planning, activities, and decision making Supports routine reporting needs Uses reports to inform operational processes Enhances capacity for complex analyses focused on program and/or service delivery targeting, planning, and other forward looking activities Aligns within agency/program and across continuum of HHS programs and services (as appropriate or needed) Focuses on highly complex analysis within agencies/ programs/vendors and across the continuum of HHS programs and services Greater flexibility and less labor intensive capacity to conduct analysis Provides management decision-maker BI support for program and policy development, allocation of resources, outcome/ impact evaluation, and anticipating and responding to changing needs and mandates Provides senior leadership with BI support for budget, program, and policy planning and responsiveness to federal and state mandates and reporting requirements Enhances capabilities to assess outcome/impact and trend analysis (anticipatory management) by program area and across all HHS programs and services Potential Future Analytical Approaches Fixed Reports Parameterized Reports Alerts, Ticklers Operational Dashboard Ad Hoc Query Multi-dimensional Analysis Statistical Analysis Advanced Analytics and Data Mining Advanced Visualization Capabilities Modeling "What If" Scenarios Program Dashboards Fixed Reports Parameterized Reports Multi-dimensional Analysis Requesting Modeling "What If" Scenarios Program and HHS Enterprise Dashboards Fixed Reports Parameterized Reports Results of Multi-dimensional Analysis and Modeling 24 Gartner, Inc. and/or its affiliates. All rights reserved.

24 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. Frame Problem Frame it! and throw out "not so" big data projects Measure Design Analysis Design business and analytics hypothesis Learning Library Gather data observe the contacts Execute prove, disprove, and refine Implement Execute and Interpret Gather Data Implement for business change Measure all aspects 24 Gartner, Inc. and/or its affiliates. All rights reserved.

25 IT: "Analytics" Data Warehouses Big Data Analytics Project Outline Big Data Analytics Project Steps Key Participants Key Objectives Frame Problem Business leader, IT leader, EA, domain expert, project manager, chief data officer (CDO) Design Analysis EA, business analyst, machine learning expert, data mining engineer, data scientist and more Gather Data Software engineer, network engineer, data architect, statistician, EA, and so on Execute and Interpret Machine learning expert, statistician, data miner, EA, data scientist and more Implement Software engineer, network engineer, data analysts, 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 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 Measure Financial partner, data analyst, business analyst, EA, and so on Create meaningful metrics Identify BDA success and failures 24 Gartner, Inc. and/or its affiliates. All rights reserved.

27 Big Data Analytics Initiatives in Government: Few and Far Between Key Law Enforcement Food Safety Fraud Detection Key Health Care National Security 24 Gartner, Inc. and/or its affiliates. All rights reserved.

29 Protecting Public Services With Context: Enhanced Fraud Detection Agency and Government Systems User and Entity Profiles Collective Network Analysis 24 Gartner, Inc. and/or its affiliates. All rights reserved. Transaction Profile

30 Recommendations ü Do not postpone the implementation of big data analytics, but develop an information management strategy first. ü Identify big questions relevant to big data. ü Understand big data technology capabilities and manage organizational impacts. ü Validate your big data assumptions in a proof of concept. 24 Gartner, Inc. and/or its affiliates. All rights reserved.

31 Recommended Gartner Research è Digital Government Is Both Different From E-Government and More of the Same Andrea Di Maio (G25258) è How the Nexus of Forces Will Impact Government Andrea Di Maio (G2376) è Invest in Information and Analytics to Benefit From Big Data Douglas Laney, Frank Buytendijk (G252) è Toolkit: Big Data Business Opportunities From Over Use Cases Frank Buytendijk, Lisa Kart, and others (G2522) è Information Governance in the Age of Big Data Svetlana Sicular (G257) For more information, stop by Gartner Research Zone. 24 Gartner, Inc. and/or its affiliates. All rights reserved.

32 Recommended Gartner Research è Decision Point for Practical Big Data Use Cases Svetlana Sicular (G239633) è Predicts 23: Business Intelligence and Analytics Need to Scale Up to Support Explosive Growth in Data Sources Daniel Yuen, Rita Sallam, and others (G227565) For more information, stop by Gartner Research Zone. 24 Gartner, Inc. and/or its affiliates. All rights reserved.

33 Big Data e BI voltados a estratégias em governo e definição de políticas e serviços públicos Claudio Chauke Executive Partner claudio.chauke@gartner.com 23 Gartner, Inc. and/or its affiliates. All rights reserved. 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."