EMC ANZ Momentum User Group 2011- Business Track- Big Data Analytics

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Big Data Analytics
Big Challenges but Even Bigger Rewards
Dalibor Ivkovic & Kee Siong Ng

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EMC ANZ Momentum User Group 2011- Business Track- Big Data Analytics

  1. 1. Big Data Analytics Big Challenges but Even Bigger Rewards Dalibor Ivkovic & Kee Siong Ng© Copyright 2011 EMC Corporation. All rights reserved. 1
  2. 2. • The business case for Big Data + ECM – Problems and opportunities• Solution vision – Greenplum and Documentum – Structured and unstructured data – The data-finds-data approach – Solution architecture© Copyright 2011 EMC Corporation. All rights reserved. 2
  3. 3. Big (unstructured) data challenges Key issues for business The new approach • Digital data growth & • Discoverability: Improve discoverability through a data finds complexity is data approach Overload outstripping current • Automation: Increase the level and sophistication of automated tooling and data analytics and management approaches • Overload & • Act early: Change from cart-before-the–horse (how do I find my Loss of deficiencies in approach are causing answer in the haystack) to horse-before-the-cart (assess new information against other enterprise information assets at the insight loss of insight across point of entry). large data collections • The value of • Define: Define key information relationships in advance (not after information assets is the fact) Loss of degraded through • Directories: build enterprise directories to correlate key data, relationships widespread events and use cases duplication, & quality redundancy and silo- ing© Copyright 2011 EMC Corporation. All rights reserved. 3
  4. 4. Repairing the information value chain High utility Diminishing utility Archival value High A. ‘Normal’ value curve Value C. Desired state The value gap.. & addressing it Low with the Big Data + ECM approach (= Rewards) B. Field experience Time ...duplication... same/similar dataNegative in multiple systems ...errors & data quality issues (= Challenges) © Copyright 2011 EMC Corporation. All rights reserved. 4
  5. 5. Big Data + ECM Strategic Insight Analytics (not enough) Share & Reuse (not enough) ECM Capture & Store (too much) 10% structured data 90% unstructured data© Copyright 2011 EMC Corporation. All rights reserved. 5
  6. 6. The EMC Solution Stack4 Collaborative Act EMC Documentum xCP ? Analyze3 Real Time EMC Greenplum + Hadoop2 Structured & Unstructured1 Petabyte Scale Store EMC Isilon + Atmos© Copyright 2011 EMC Corporation. All rights reserved. 6
  7. 7. What is Greenplum?A massively parallel analytical Hadoop, Python, Perl, R, SQLdata warehousing system supporting MapReduceboth SQL and MapReduce processing Master Masteron Big Data Customers include Segment Segment Segment Segment … Segment © Copyright 2011 EMC Corporation. All rights reserved. 7
  8. 8. Role of analytics in content mgmt Context Outcome / Business Process Value Analytics Data Finds Data System n Information Supporting Systems System B System A© Copyright 2011 EMC Corporation. All rights reserved. 8
  9. 9. Banking scenario5 yr customer-bank relationship Business Outcomes Loan Processes Origination Business Product Fraud Recommend. Churn 2007 - 2010 2011 2015 New Loan - open a credit card a/c Events Change Better Application - spouse opens a/c Bank? Income - complaint - fraud Risk Customer Product use cases Assessment Big Data Churn Recommendations + ECM What else do we know What are her interactions What has changed about this person? with the bank? over time?© Copyright 2011 EMC Corporation. All rights reserved. 9
  10. 10. Loan application© Copyright 2011 EMC Corporation. All rights reserved. 10
  11. 11. Data finds data – Point of capture Name: Joel Ibrahim DOB: 22/5/1957 Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456© Copyright 2011 EMC Corporation. All rights reserved. 11
  12. 12. Data finds data – Point of capture Name: Joel Ibrahim DOB: 22/5/1957 Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456 Name: Joe Ibrahim DOB: 22/5/1957 Tel: (02) 8633 8412 Addr: 50 Indra St, NSW 2133© Copyright 2011 EMC Corporation. All rights reserved. 12
  13. 13. Data finds data – Point of capture Name: Joel Ibrahim DOB: 22/5/1957 Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456 Name: Joe Ibrahim DOB: 22/5/1957 Tel: (02) 8633 8412 Addr: 50 Indra St, NSW 2133 Name: J. D. Ibraham Acct: Superannuation Tel: 0412 047 456© Copyright 2011 EMC Corporation. All rights reserved. 13
  14. 14. Data finds data – Point of capture Name: Joel Ibrahim DOB: 22/5/1957 Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456 Name: Joe Ibrahim DOB: 22/5/1957 Tel: (02) 8633 8412 Addr: 50 Indra St, NSW 2133 Name: J. D. Ibraham Acct: Superannuation Tel: 0412 047 456 Name: Joel Ibrahim DOB: 22/5/1957 Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456© Copyright 2011 EMC Corporation. All rights reserved. 14
  15. 15. Data finds data – Credit assessment Name: Joel Ibrahim DOB: 22/5/1957 Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456© Copyright 2011 EMC Corporation. All rights reserved. 15
  16. 16. Data finds data – Credit assessment Name: Joel Ibrahim dependent DOB: 22/5/1957 director Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456 joint acct shared mortgage Name: M. Ibrahim DOB: 23/6/1960 Tel: 0433 044 888© Copyright 2011 EMC Corporation. All rights reserved. 16
  17. 17. Data finds data – Credit assessment Name: Joel Ibrahim dependent DOB: 22/5/1957 director Addr: 55 Picasa St, NSW 2032 Tel: 0412 047 456 director joint acct shared mortgage joint acct BANKRUPT Name: M. Ibrahim DOB: 23/6/1960 Tel: 0433 044 888© Copyright 2011 EMC Corporation. All rights reserved. 17
  18. 18. Ongoing customer management “Unless you have 100% customer satisfaction… you must improve.” Horst Schulz “A dissatisfied customer would tell between 7-10 people while a satisfied customer would recommend a company to 3-4 of their friends”. PIMS© Copyright 2011 EMC Corporation. All rights reserved. 18
  19. 19. Data finds data – Customer management feedback Refinance Courtesy call© Copyright 2011 EMC Corporation. All rights reserved. 19
  20. 20. Key insights• Data finds data – Discoverability i.e. finding relationships between data in near-real time • Directory i.e. a map of relationships between entities = a locator service. The degree to which previous information can be located & correlated with the new data.*• Principles – Act early i.e. at point of ingesting new data – Build understanding of relationships between data – Enable users to act on these understandings * Data Finds Data, Jeff Jonas and Lisa Sokol, from Beautiful Data, The Stories Behind Elegant Data Solutions, 2009© Copyright 2011 EMC Corporation. All rights reserved. 20
  21. 21. Other examples of data finds data Loan origination Customer relationship management (banking) Contracts • Improve correlation between significant lifecycle events (variation, renewal, dispute, expiry) & provision of data to stakeholders (contractor, supplier, legal, finance, PMO) Fraud detection One understanding of the customer Risk assessment Personalisation (machine learning)© Copyright 2011 EMC Corporation. All rights reserved. 21
  22. 22. Solution visionBig Data + ECM Parallel Architecture Analytics Directory CRM Master – customer details Partition - Correlation - Text analytics Master – accounts - Data mining - Messaging Banking - Machine learning Partition ... Master – documents & records ECM Constructed Context Act on understanding© Copyright 2011 EMC Corporation. All rights reserved. 22
  23. 23. Recap Challenges Insights Solution vision Rewards  Discoverability  Improve value of Overload  Act early Parallel Architecture information assets Analytics Directories (i.e. value gap)  Understanding of  Become more Loss of relationships - Correlation proactive -Text analytics insight between data -Data mining - Messaging  Better quality of - Machine learning ... service  Enable users to act  Improve estimation on these Constructed Context of risk Loss of  Reduce waste & understandings relationships cost & quality© Copyright 2011 EMC Corporation. All rights reserved. 23
  24. 24. THANK YOU© Copyright 2011 EMC Corporation. All rights reserved. 24

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