This document provides a summary of a Talend webinar on leveraging open source for data quality. The webinar agenda includes introductions to Talend, data cleansing with Talend, and an explanation of why data cleansing is important for data integration. Talend offers open source and commercial data quality and integration products to help users discover, assess, and improve data quality through profiling, cleansing, and management across the data lifecycle.

1. Leverage Open Source for Data Quality

3. If time is too short to address all questions, you will receive an answer via emailIf you are having connection problems, please use also the Q&A panel

4. Agenda Talend Introduction Data Cleansing with Talend Data Cleansing Why data cleansing? The importance of data cleansing in data integration

5. Agenda Talend Introduction Data Cleansing with Talend Data Cleansing Why data cleansing? The importance of data cleansing in data integration

6. © Talend 2010 5 Corporate Overview Leading provider of open source data management software Venture-backed Worldwide operations and users London (Maidenhead) Business Tech Support Nuremberg Business Tech Support Tokyo Business Tech Support Beijing R&D Tech Support San Francisco (Los Altos) Corporate Orange County (Irvine) Business R&D Tech Support New York (Tarrytown) Business Tech Support Paris (Suresnes) Corporate Business R&D Tech Support Milan (Curno) Business Tech Support UtrechtBusiness 5 © Talend 2010

8. 450,000 users

9. 1,500 customers1 download of Talend Open Studio per minute 100 new customers per month

11. Technical & business criteria

12. Direct entry as Visionary

13. Only open source vendorAlso mentioned in Gartner’s Data Quality & Master Data Management research, and by other analyst firms (Forrester, IDC, Bloor Research, etc.)

14. © Talend 2010 8 Company History IntegrationSuite RTx MDMEnterprise Edition Open Studiov1.0 Products Open Profiler Integration Suite MPx MDMCommunity Edition Data Quality IntegrationSuite Talend Open Studio Beta 1 2002 2006 2007 2008 2009 2010 2005 Operations Operations R&D Company creation Third round of financing: existing investors & Balderton Capital Launched US operations First round of financing: AGF Private Equity & Galileo Partners MDM acquisition Closed second round of financing Closed fourth round of financing © Talend 2010

15. © Talend 2010 9 Open Source History 2002 1970 1984 1998 2000 2003 2006 2009 Open source is created Free access to code Free Software Foundation (Richard Stallman) Launching GPL and GNU Open source solutions emerge Apache… Software companies come out MySQL, JBoss, SugarCRM… More and more mature key players stand out JBoss, SugarCRM , Jaspersoft, Talend… Economic crisis favors enterprise-ready open source players Open Source Initiative is created Implementing a policy meeting economical and technical realities

16. © Talend 2010 10 Market Positioning MDM Data Quality Reference data management Data profiling & data cleansing Data Integration Analytics (ETL) Operational Integration Data replication & synchronization, data migration & capture, application upgrade, etc. Extract, Transform & Load for decision support systems

19. Repository Manager

23. Agenda Talend Introduction Data Cleansing with Talend Data Cleansing Why data cleansing? The importance of data cleansing in data integration

25. Data lacks granularity to fulfill the requirements of the applications

30. Statistics

32. Understand data characteristics

33. Identify potential problems before beginning data projects

34. Reduce time and resources needed to find problematic data

35. Allow business analysts to have more control of maintenance and data managementData Quality

38. Eliminate or recycle erroneous records

39. Correct bad data

40. Interfaces with:

41. Name, address, & phone validation databases

42. Synonym tables and lookup data

43. External data cleansing routines

44. Types of processing: Filtering / Correction / EnrichmentData Quality

46. Data profiling

47. Measure and track level of quality

48. Preserve historical records for measuring improvement or degradation

49. Data cleansing

50. Eliminate data inconsistencies, duplicates, etc.

51. Produce augmented/enriched data

52. Standardizes data

53. Complete data quality lifecycle managementNatively integrated with Data Integration Implement a "Data Quality Firewall" in data integration processes Data Quality

54. Agenda Talend Introduction Data Cleansing with Talend Data Cleansing Why data cleansing? The importance of data cleansing in data integration

57. Watch anotherWebinar on Demand : http://nxy.in/hkidj

58. Watch our Live Webinars : http://nxy.in/pjeph© Talend 2010 21