Enterprise Information Architecture using Data Mining<br />Reshmi Chakraborty<br />
Digital information proliferation<br />Healthcare Sector<br />Utility Sector<br />An integrated solution framework<br />Ou...
Digital Information Growth and need for a scalable data mining solution<br />3<br /><ul><li>In 1986, 14% of earth’s data w...
In 2000, 25% of all information was in digital media form.
By 2007, 94% of all information storage capacity was digital, totaling 276 exabytes. 
Computing storage capacity is growing at around 58% per year.
This is increasing infrastructure requirements, complexity and straining IT resources.
Achieving analytics with traditional data mining strategies is becoming slow and/or beyond the financial means of many org...
Consumers “shopping” for their healthcare needs.
Resulting information proliferation and need for data mining
Managed-Care Organizations (MCO) has become a merger and acquisition industry
Each MCO has large amounts of digital prescription claims (often redundant).
MCOs working to use these information to improve and retain customer loyalty.
They need a Clinical Master Patient Index and an efficient data mining strategy to remain profitable.</li></ul>4<br />
Demand response in Utility sector <br />5<br /><ul><li>The fundamental problem is rising utility expense.
Lack of capability to monitor and control consumptions.
Need to study past data and need algorithms to extrapolate past data into possible future conjectures.
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Enterprise Information Architecture Using Data Mining

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  • http://smartdatacollective.com/yellowfin/35139/
  • U.S. healthcare spend is projected to be around $4.0 trillion by 2015 while OOP expense will grow by 9% only – source www.Cms.Hhs.GovConsumer ImpactUS consumers are increasingly bearing a larger burden of their healthcare costs due to tiered cost-sharing formulas of managed care organizations (MCO).More than 2/3rd of the MCOs are registered in preferred provider organization (PPO) programs allowing consumers to “shop” for their healthcare needs.This has created a consumer focused healthcare market.Resulting information proliferation and need for data miningIn a consumer centric market, MCO has become a merger and acquisition industry with consolidation expected to continue as MCOs seek to expand their consumer base.Given this concentrated dynamics in MCO industry, Prescription Benefit Managers (PBMs) can easily gain access to large amounts of digital claims from the MCOs. In order to make this collaborative business model workable and secured, it is absolutely imperative that an efficient data mining strategy is implemented and all information exchange across various organizations comply to a given electronic message protocol (CDIC/HL7) and privacy regulations such as HIPAA.
  • Enterprise Information Architecture Using Data Mining

    1. 1. Enterprise Information Architecture using Data Mining<br />Reshmi Chakraborty<br />
    2. 2. Digital information proliferation<br />Healthcare Sector<br />Utility Sector<br />An integrated solution framework<br />Our proposal & future research areas<br />
    3. 3. Digital Information Growth and need for a scalable data mining solution<br />3<br /><ul><li>In 1986, 14% of earth’s data was stored on vinyl records.
    4. 4. In 2000, 25% of all information was in digital media form.
    5. 5. By 2007, 94% of all information storage capacity was digital, totaling 276 exabytes. 
    6. 6. Computing storage capacity is growing at around 58% per year.
    7. 7. This is increasing infrastructure requirements, complexity and straining IT resources.
    8. 8. Achieving analytics with traditional data mining strategies is becoming slow and/or beyond the financial means of many organizations.</li></li></ul><li>Healthcare – state of the union<br /><ul><li>Spending is projected to be around $4.0 trillion by 2015 while OOP expense will grow by 9% only
    9. 9. Consumers “shopping” for their healthcare needs.
    10. 10. Resulting information proliferation and need for data mining
    11. 11. Managed-Care Organizations (MCO) has become a merger and acquisition industry
    12. 12. Each MCO has large amounts of digital prescription claims (often redundant).
    13. 13. MCOs working to use these information to improve and retain customer loyalty.
    14. 14. They need a Clinical Master Patient Index and an efficient data mining strategy to remain profitable.</li></ul>4<br />
    15. 15. Demand response in Utility sector <br />5<br /><ul><li>The fundamental problem is rising utility expense.
    16. 16. Lack of capability to monitor and control consumptions.
    17. 17. Need to study past data and need algorithms to extrapolate past data into possible future conjectures.
    18. 18. Need a smarter infrastructure, an integration of electrical infrastructure and information infrastructure </li></li></ul><li>A tentative solution approach<br />The integrated data mining solution (apart from industry specific algorithms) need to cater the following:<br /><ul><li>Retain customer loyalty through Portals and Mash-ups
    19. 19. Master Data Management System
    20. 20. A Clinical Master Data Management System
    21. 21. A Meter data management system based on power-line-communication (PLC) architecture.
    22. 22. Actionable analytics based on data mining algorithms.
    23. 23. Unified identity and access management system
    24. 24. Secured content management system.
    25. 25. Canonical data model for all electronic information exchange.
    26. 26. Service Oriented Architecture as part of the enterprise wide information strategy. </li></ul>To scale this architecture up, implement this solution in SaaS/BPO/ Cloud (EC2/Azure/Google) model<br />6<br />
    27. 27. Basic Data Mining Process<br />7<br />ETL*<br />Pre process<br />Select mining logic<br />Presentation logic<br />Operational Data Store<br />Data Mart<br />Star schema based dimension cubes<br />Data mining algorithms<br />* Extract, Transform and Load<br />ETL*<br />Pre process<br />Select mining logic<br />Analytics<br />Operational Data <br />(ODS)<br />Data Mart<br />Star schema based dimension cubes<br />Data mining algorithms<br />* Extract, Transform and Load<br />
    28. 28. Healthcare version<br />8<br />
    29. 29. Utility sector version<br />9<br /><ul><li>The solution consists of installation of smart meters in individual apartments and controlling them from one single location.
    30. 30. The solution is intended to operate in a service cloud model where different customer energy profiles can be managed from the same information cloud.
    31. 31. Customer information security will be maintained at two different levels.
    32. 32. First, the information to and from smart meters will be communicated using web service-security framework and each customer will have their own security algorithm.
    33. 33. Second, at the database level, the data will be stored in partitioned tables.
    34. 34. Smart meters, RF links (zigbee protocol will be used to communicate data out of smart meters into redundant data collection units) and data collection units will be off-the-shelf products. </li></li></ul><li>Is this a viable approach?<br />10<br />iPhone based consumer centric healthcare App – adoption trend<br />A smart grid enabled demand response system<br />
    35. 35. Lets look at a SWOT analysis<br />11<br />W<br />Strengths<br /><ul><li> Scalable – can be sold in subscription model.
    36. 36. Standardized – follows industry standard communication protocols</li></ul>Weaknesses<br /><ul><li> Additional industry specific components needed which may increase cost.
    37. 37. Security and data privacy is still a major concern.</li></ul>Opportunities<br /><ul><li>Strategic alliances, partnerships with cloud providers like Amazon/Google.
    38. 38. Can be built entirely using open source technologies.</li></ul>Threats<br /><ul><li> User hesitation.
    39. 39. Could be conidered as “Old wine in new bottle”.</li></ul>S<br />T<br />O<br />
    40. 40. Our approach to implement an integrated information framework<br />12<br />Three step business-technology strategy development process<br />Learn- Investigate- Stimulate- Tabulate - Enumerate - Net<br />
    41. 41. Prometheus is our proposed utility sector solution<br />13<br />
    42. 42. Future areas of research<br />14<br />Following are the future areas of research that we are going to focus in the process of developing our solutions and attempting to commercialize them:<br /><ul><li> The techniques will be useful pending change in information storage techniques – i.e. it becomes a hybrid of relational and semantic storage model.
    43. 43. Developing the solution in open source mode.
    44. 44. Making the structure flexible so that the end consumer has the capability of choosing from a set of data mining algorithms and compare results.
    45. 45. Identifying the target set of customers and testing the prototype model in viral networking environment.</li></li></ul><li>In summary:<br />Information proliferation is costly from people, process and technology perspective.<br />Business decision is a function of information and intelligence.<br />Combining one and two above, we find that an integrated hosted data mining framework can improve the top line of an organization.<br />15<br />
    46. 46. 16<br />
    47. 47. Thank you<br />

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