Big Data: Impact, Benefits, Risk and Governance
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1 Big Data: Impact, Benefits, Risk and Governance Urs Fischer, CPA (Swiss), CRISC, CISA, CIA Fischer IT GRC Consulting & Training
2 Urs Fischer
3 Agenda 1. Introduction 2. Impact on the Enterprise 3. Business Benefits 4. Risks and Concerns 5. Strategies for Addressing Risk 6. Governance
4 Introduction Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
5 Definition Big data refers to data sets that are too large or too fast-changing to be analysed using traditional relational or multidimensional database techniques or commonly used software tools to capture, manage and process the data at a reasonable elapsed time. Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
6 Mind Reading
7 Data Volunteered Data Created and explicitly shared by individuals e.g., social network profiles Observed Data Captured by recording the actions of individuals e.g., location data when using cell phone Inferred Data Data about individuals based on analysis of volunteered or observed information e.g., credit scores Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
8 Impacts on the Enterprise Governance Planning Utilisation Assurance Privacy
9 Privacy a hoax? Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
10 Objective Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
11 Business Benefits Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
12 Product Development Market Development Operational Efficiency Positive Impact of Big Data Analytics Customer Experience and Loyality Market Demand Predictions
13 Insights from Big Data Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
14 Four-Tier Plan 1. Take time to strategise 2. Think analytically 3. Ask for what is needed 4. Invest to improve
15 Questions Where should we store the data? How are we going to protect the data? How are we going to utilise the data safely and lawfully?
16 Risk and Concerns Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
17 Security & Privacy Private or custodial information such as credit card numbers, personally identifiable information such as Social Security numbers, and personal health information Strategic information such as intellectual property, business plans and product designs Information such as key performance indicators, sales figures, financial metrics and production metrics used to make critical decisions
18 Points of Tension Privacy Global Governance Personal Data Ownership Transparency Value Distribution
19 Minimize Potential of Damage Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
20 Strategies for Addressing Risk Determine what internal resources and capacities are available to digest existing information. Determine what tools are needed to enhance the information acquisition and digestion process. Address how information will be used to achieve both tactical and strategic goals, if the determination is made that new and/or different information is needed. Develop or obtain training programs for the team. Determine whether a data scientist is needed. Establish realistic expectations and create a tactical plan.
21 Quality Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
22 End-To-End Governance Source: COBIT 5, ISACA 2012
23 Proper Data Governance Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
24 Data Governance Programs Source: Big Data Impacts & Benefits ;ISACA White Paper, March 2013
25 Fundamental Questions Do we fully recognize the responsibilities associated with handling big data? How does big data change the traditional concept of information as a corporate asset? What are the emerging requirements around privacy? How do the big data technologies relate to our current IT infrastructure?
26 Conclusion The enterprise culture, which either fights or embraces innovation, requires a big data leader who understands his/her role in innovation or enterprise direction. In addition, the leader must: Manage expectations Reward behaviours rather than results Shield data scientists from the detailed scrutiny of management and investors Manage projects Communicate well to span the enterprise channels
27 Fragen / Diskussion
28 Urs Fischer, CPA (Swiss), CRISC, CISA, CIA
29 Urs Fischer CPA (Swiss) by origin, CRISC, CISA & CIA 5 year external auditor Switch to IT Audit In IT Audit for 13 years incl. Head of IT Audit Head IT Governance & Risk Mgmt Since 2011 independent IT GRC Consultant and Trainer Co-Author of CobiT4 and now participant of the development of COBIT5 Co-Developer of CobiT Control Practices Co-Developer of ISACA s IT Control Objectives for Cloud Computing Board member of ISACA CH Chapter for about 8 years Member of the CobiT Steering Committee for 3 years Member and Chair of ISACA s EuroCACS Conference Programme Committee for 6 years Chair of ITGI s 'Risk IT' Task Force Chair of ISACA s CRISC Task Force Member of ISACA Audit Committee (since Chairman) Member of ISACA s Guidance and Practice Committee Member of ISACA s Credentialing Board Chair of ISACA s CRISC Committee 2012 Member of ISACA/ITGI s Nomination Committee 2010 Receiver of the John W. Lainhart IV Common Body of Knowledge Award
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