Smarter Analytics: Big Data and Predictive Governance
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The document discusses how big data, social media, systemic models, and governance can be used for predictive governance. It describes how analyzing large amounts of diverse data from various sources can help anticipate crises and their impacts. By monitoring data in real-time from sensors, images, reports, and meetings, predictive models can be generated to simulate potential outcomes and help decision makers plan accordingly. When combined with data governance practices to validate data quality, these tools allow issues to be addressed proactively before they become larger problems.
Smarter Analytics: Big Data and Predictive Governance
- 1. Predictive Governance Big Data, Social Media, Systemic Models, and Governance Steven Adler IBM Information Governance Solutions © 2010 IBM Corporation
- 2. Predictive Governance 1. Crises – Always a surprise 2. Big Data – We Anticipate the Future 3. Systems – We understand how things work 4. Predictive Governance – We take control © 2010 IBM Corporation
- 3. When the Financial Crisis hit in October 2008 ...why were its causes and effects a surprise? © 2010 IBM Corporation
- 4. When Greece couldn't make its debt payments in 2009 ...Why didn't we foresee the impact on interest rates? © 2010 IBM Corporation
- 5. When 57% of American Farmland is ruined by Drought... ...How will that effect the global economy? © 2010 IBM Corporation
- 6. Making Predictions is Difficult... ...When we aren't paying attention to what's happening © 2010 IBM Corporation
- 7. Even when we are paying attention ...there is a lag between event and information © 2010 IBM Corporation
- 8. But there are ways To know what's happening right now, and combine it with historical experience. To detect evidence of dysfunction, And monitor its development. To predict the likelihood of crises, And anticipate its direct and tertiary consequences. ...And we have to do it now © 2010 IBM Corporation
- 9. Because the world is too important ...To just keep muddling along © 2010 IBM Corporation
- 10. Big Data = Volume, Variety and Velocity Extracting insight from an immense volume, variety and velocity of data, in context, beyond what was previously possible. Variety: Manage the complexity of multiple relational and unstructured data types and schemas Velocity: Streaming data and large volume data movement Volume: Scale from terabytes to zettabytes 10 © 2010 IBM Corporation 10
- 11. Example: A Massive Earthquake in Australia... Gold Mine Perth Will have a ripple effect across South East Asia © 2010 IBM Corporation 11
- 12. In the old days, markets priced the effects... But Today, you use Big Data to monitor the impact © 2010 IBM Corporation 12
- 13. Combining Satellite Images We can know: where every ship is in port and en route What they carry, and their destination Speed and Course Maintenance Record and Personnel Buyers and Sellers Logistical Supply Chain Industrial Dependencies Markets and Makers ...with logistics data © 2010 IBM Corporation 13
- 14. Using Local Reporting of damage Smartphone Images Uploaded with geotags Image recognition of Damaged facilities Compared to port data on Goods volume per day ...and historical data we can assess economic impact © 2010 IBM Corporation 14
- 15. Meanwhile Employees scour media reports Each report is a lead that a search engine uses to find more of the same. Employees comment on the reports adding experience and interpretation. In real time, you build rich understanding of what's happening. ...and post articles that are indexed and researched © 2010 IBM Corporation 15
- 16. They attend meetings and conferences Their metadata allows you to Perform federated search On the meeting or conference They attended and index the larger Contextual information to magnify Their experience and provide Richer context. ...and send photos, ideas, and updates © 2010 IBM Corporation 16
- 17. Your Data Governance Ontology Using the same Big Data Solutions, you tag data as it Is analyzed, research its lineage Verify its provenance, and assign Obligations to its onward use. ...allows you to validate Data Quality in Real Time © 2010 IBM Corporation 17
- 18. With verified data, you generate systemic models ...to simulate potential outcomes and make new plans © 2010 IBM Corporation 18
- 19. This vision combines data from human and computer ...Sensors with Big Data Actuators © 2010 IBM Corporation 19
- 20. Every day we are confronted with crises big and small ...that we want to master with information © 2010 IBM Corporation 20
- 21. Big Data is the way to master our information 1. Business and IT Identify information sources available. 2. IT Delivers Platform that enables creative exploration of all available data and content. + 4. New insights drive integration with traditional technology. 3. Business explores data and relationships creating and testing hypotheses. ...and turn challenges into opportunities © 2010 IBM Corporation
- 22. Big Data allows us to analyze anything and... You can tell where your information came from - when it was last updated - how many people touched and altered it - what it means and how you should use it - when you should trust it - whether it is fact or dangerous fiction - what it means and what it is related to - to create ecosystems of information ...add rich layers of context and meaning © 2010 IBM Corporation 22
- 23. IBM Vision for Big Data Integration A Streams p Computing p li Internet Scale c Computing a ti o Content Discovery n F r Analytics a m Public/Private e Cloud w o r k © 2010 IBM Corporation 23
- 24. Big data is a hot topic because technology makes it possible to analyze ALL available data Cost effectively manage and analyze all available data, in its native form – unstructured, structured, streaming Website Social Media Billing ERP Network Switches CRM RFID © 2010 IBM Corporation
- 25. Vestas optimizes capital investments Capabilities: Hadoop System Data Warehousing • Model the weather to optimize placement of turbines, maximizing power generation and longevity. • 3 weeks to 3hrs. Reduce time required to identify placement of turbine from weeks to hours. • 2.5 PB of structured and semi- structured data. Growing to 16PB 2015 25
- 26. Beacon Institute Detects Environmental Changes to Water Resources in Real-time Capabilities Utilized: Stream Computing • Collecting and processing multiple streams of physical, chemical, and biological data from sensors deployed in Hudson Bay • Sensor data is analyzed against larger meteorological data and aggregated • Real-time environmental data delivered in standard format to scientists, engineers, policy makers, and educators Significant benefits: “More effective • Better understanding of dynamic interactions within local river and estuaries response to • Fosters increased collaboration by making real- chemical, world data available to outside systems, researchers, policy makers physical, • Helps resource management respond more effectively to changes to local water resources biological changes” 26
- 27. TerraEchos Turns to IBM Big Data for Low Latency Surveillance Data Analysis Capabilities Utilized: Stream Computing • Deployed security surveillance system to detect, classify, locate, and track potential threats at highly sensitive national lab • Stream computing collects and analyzes acoustic data from fiber-optic sensor arrays • Analyzed acoustic data fed into TerraEchos intelligence platform for threat detection, classification, prediction & communication Significant benefits: • Enables Terraechos solution to analyze and classify streaming acoustic data in real-time • Provides lab & security staff with holistic view of “Identifies and potential threats & non-issues • Enables a faster and more intelligent response to classifies potential any threat security threats – 27 miles away”
- 28. KTH Swedish Royal Institute of Technology Reducing Traffic Congestion Capabilities Utilized: Stream Computing • Deployed real-time Smarter Traffic system to predict and improve traffic flow. • Analyzes streaming real-time data gathered from cameras at entry/exit to city, GPS data from taxis and trucks, and weather information. • Predicts best time and method to travel such as when to leave to catch a flight at the airport Significant benefits: • Enables ability to analyze and predict traffic faster and more accurately than ever before • Provides new insight into mechanisms that affect a complex traffic system • Smarter, more efficient, and more environmentally friendly traffic 28
- 29. Proctor & Gamble increases employee productivity thru improved enterprise search Capabilities Utilized: IBM Vivisimo Velocity Need • Robust search and discovery system to help employees more effectively & efficiently leverage company data & content in more than 30 strategic repositories • Help employees find content they need, people they should talk to, and places to look for relevant info. Benefits • Reduced employee time spent searching for info, increased time to make productive connections, and enable action
- 30. Closing Remarks 1. Big Data will integrate all information types 2. Federated Search and Indexing 3. Automated Research and Discovery 4. Live Data Verification and Classification 5. Systemic Models and Simulations 6. All of this is available today © 2010 IBM Corporation