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How to achieve accurate data for the Web World PowerPoint Presentation
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How to achieve accurate data for the Web World
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  1. How to achieve accurate data for the Web World Michael Rochford Sales Manager mrochford@transoft.com 07801 634176 The Modernization Experts

  2. Agenda • Quick into to Transoft • Strategies for Web and Mobile applications • Why is data so important • Data Quality/Matching/De-duplication • Data Migration • Change Data Management • Data Governance • Summary

  3. Transoft Solutions

  4. Transoft Champions June 2011 Transoft Named “Champion” in Info-Tech Research Group’s Legacy Software Modernization Vendor Landscape

  5. Traditional Legacy • Large Systems • Batch Processing • OLTP • Big IT Departments • Long Development Times • Centralised Systems • Controlled users • Green Screen • PC’s emulation • Departmental applications

  6. The modern age

  7. And it’s accelerating 38% of CEOs label social media a high priority 57% of businesses plan to hike their social media spend in 2012 • 50% of men and 75% of women access the internet from their phones Carphone Warehouse • 32% of Valentine’s gifts are purchased on-line - ebillme Although the UK economy is stagnant, the on-line economy is expected to grow by 10% per annum - Boston Consulting • Over 10 billion apps have been downloaded to Android devices - ZDnet 2011 • Android make up 50% of the Smartphone market - Mobiledia • 76% of British homes are connected to the internet - Ofcom • One in four Starbucks payments in the US are via mobile devices - Mobile Syrup • More than a third of Domino’s pizzas are ordered online - Internet Retailing

  8. Data Cleanse • Data Migration So how do you take traditional applications to this new world?

  9. Why is Data so important “The farther backward you can look, the farther forward you are likely to see” -- Winston Churchill • Without accurate data businesses cannot make informed decisions regarding the future • Customer Service • Compliance • Single version of the truth

  10. Agenda • Quick into to Transoft • Strategies for Web and Mobile applications • Why is data so important • Data Quality/Matching/De-duplication • Data Migration • Change Data Management • Data Governance • Summary

  11. Data Quality, Matching De-duplication Legal • Increased Revenue Financial • Reduced Costs • Enhanced Compliance • Single Version of Truth • Improved Efficiency and Productivity Service Operational • Improved Reporting • Enhanced Customer Service • Better Decision Making

  12. Data Cleanse and De-duplicate • Cleansed in source or staging database • Iterative, rules based process • No one size fits all • Built to fit source requirements

  13. Data enrichment • Correct Address • Match with external databases • Further improvement • Increased value • Improved service • Individual Information • Contact Preferences • LocationInformation • OrganisationInformation

  14. Example 1 Problem: 3 existing Order Processing systems duplicated customer data 5 Million records Solution: 2.9 million records standardised, cleansed, merged and de-duplicated Benefits: • Efficient operations – 2.9 million records in new CUSTOMER database • Improved customer service - Single customer view - basis of new CRM system • Cost saving - Bring marketing in-house saving £000s • Increase revenue – implemented new customer loyalty card

  15. Example 2 Problem: Duplicated Locations, Organisations and Individuals Solution: • Standardise Organisation name, Individual title and Address • Validate UK Addresses • Identify duplicate Organisations, Individuals and Locations • Remove duplicates or set status to inactive 1 Canada Square, LONDON, E14 5LB One Canada Square, LONDON One Canada Square, London One Canada Square, London One Canada Square, Canary Wharf, London 1 Canada Square One Canada Square, London E14 5AL One Canada Square One Canada Square, Canary Wharf, London One Canada Square Benefits: • Improved customer service • Increase membership

  16. Agenda • Quick into to Transoft • Strategies for Web and Mobile applications • Why is data so important • Data Quality/Matching/De-duplication • Data Migration • Change Data Management • Data Governance • Summary

  17. Data Migration – Separate Applications • Project definition/scoping • Data analysis • Project plan • Data cleansing rules • Data migration rules • Testing • Go-live

  18. Project Definition • Stakeholders • Who owns the project? • Who owns the data? • Identify all Data Stores (Source and Target) • Data Discovery

  19. Data analysis – Data Discovery • Where is it? • Platform, applications • How is it stored? • What access can we get to it? LEGACY

  20. Project Plan • Task overview • Resources • Project plan • Product selection • Costs • Timescales

  21. Data Migration Rules • Match required Source data to Target data • Automated, accurate, repeatable and maintainable • Run in sequence • Data transformation to improve quality or meet requirements of Target

  22. Testing • Will require multiple passes • Audit trails • Logs and Alerts • Error handling • Check timing

  23. Go-live • Co-ordinated with Application go-live • Phased • Data Subset • Table subset • Application Integration • Data Synchronisation

  24. Agenda • Quick into to Transoft • Strategies for Web and Mobile applications • Why is data so important • Data Quality/Matching/De-duplication • Data Migration • Change Data Management • Data Governance • Summary

  25. Change Data Management • Batch migration • Re-migrate data or update dataset migrated periodically • Suitable for static datasets • Where up-to-date info isn’t essential Existing Database New Database • Real-time synchronisation • Capture Insert/Update/Delete events and apply these to other dataset • Ideal for dynamic data • Should be bi-directional

  26. Data Governance • Application issues • Input validation • Post code checks • Capitalisation • Human Factors • Caps Lock key (Roberts, rOBERTS) • Typos (Peterson, Pieterson) • Abbreviations (Ln, Ave, St, Rd) • Obsolete Data • Moved, gone away • Deceased

  27. Agenda • Quick into to Transoft • Strategies for Web and Mobile applications • Why is data so important • Data Quality/Matching/De-duplication • Data Migration • Change Data Management • Data Governance • Summary

  28. Summary • A web strategy needs to be backed by a data strategy • Data Cleansing and/or Migration needs to be planned as a project in its own right • Use an Automated, Rules-based product • Apply all the usual Project Management steps • Find a partner who has both the tools and experience • Test, Test, Test ……

  29. Questions