1. Barriers to Information Instructor: Pankaj Mehra Teaching Assistant: Raghav Gautam Lec. 3 April 6, 2010 ISM 158

2. Reading Assignment (for April 6) Review Chapters 2 & 3 (Overcoming the failures and Three opportunity areas) from CapGemini’s The Information Opportunity report (2008) Think about: –What are some dimensions of information quality? –How can lack of trust be an issue in making better use of information? –What sort of policies, procedures and mechanisms would enable information sharing among business silos toward a single view of customer?

3. Compare and Contrast Application-centric view (ca. 2007) Information-centric view (ca. 2009) PeopleProcess Inform ation Techno logy From SOA Practitioner’s Guide pt. 2SOA Practitioner’s Guide

4. Barriers to exploiting information

5. What is Information Quality A measure of how well information satisfies the needs of its consumers Suitable definition of IQ measures requires agreement betw. business & IT Achieving good IQ requires not only bottom-up investment in systems but also top-down investment in policies and procedures

6. IQ dimensions & metrics To judge this, … Accuracy Completeness Reliability Availability Timeliness / freshness Consistency Uniqueness Measure/model this Precision of answers Recall of answers Probability of error/failure Uptime and downtime Latency Constraints Redundancy

7. 7 Systems Integration and Data Quality Technology: Maturity Model by Gartner’s Newman Prolific use of custom code Lack of general- purpose tools Too many technologies Lack of strategic deployment Custom Code ETL EII Cleansing Profiling Metadata EAI Custom code remained Some vendor consolidation around related tools Common cleansing services Custom Code EAI Cleansing Profiling Metadata ETL EII Custom code minimized Comprehensive integration tools Metadata centricity Strategic approach EAI ETLEII Cleansing Profiling Metadata Custom Code Metadata No custom code Converged information infrastructure Service-orientation Strategic deployments Transform Deliver Govern Access 2007!

8. Case Studies

9. Courtesy: Information Quality Workgroup, Mark Temple-Raston

11. Service Canada Information Quality Review and Activities IQ Working Group Andrew John Bystrzycki Information Architecture Services ATS, IITB, Service Canada March 22, 2007

12. 12 Service Canada: who we are  Service Canada (the service wing of HRSDC) has the largest Government of Canada service delivery network, with coverage and capacity across Canada  Serving 32 million Canadians per year over 500 points of service  Delivers key national programs, including Employment Insurance, Canada Pension Plan and Old Age Security  Paying more than $70 Billion in benefits to Canadians annually  Employing over 22,000 staff  History of our IM/IT environment:  Service Canada was formed from many mergers of many programs resulting in heterogeneous operational IM/IT environments and numerous fragmented systems and databases impacting information quality  Data / Information:  Information stays operationally alive for many years throughout the client’s lifecycle events: birth, school, work, sickness, disability, maternity/paternity, volunteer, unemployed, homeless, retired, low-income pensioner, death  Numerous initiatives are underway to improve IT readiness, processes, Information Management in general and Information Quality in particular

13. 13 Information Quality Issues  Inconsistent data quality assessment processes  Issues of conformity in terminology, metadata, naming, formats, etc.  Issues of inconsistency in data values  Some concerns about data correctness  Data dictionary divide between legacy systems and new databases  Issues of missing or incomplete data  Issues in data validation  Issues in data synchronization  Issues in data integration or consolidation

14. 14 Service Canada Information Quality Vision  IQ Vision:  Improve the quality of client and benefit information to enable information synchronization and consolidation and to demonstrate accountability, transparency, effectiveness and efficiency in service delivery  IQ Goal and the Business Imperative:  Improvement in information quality and consolidation will enable us to become part of international trend towards one-stop process to government services  IQ is essential for the service delivery side as well as for the policy side

15. 15 Service Canada IQ Initiatives  Government of Canada Data Stewardship Initiative:  A partnership between Treasury Board of Canada Secretariat, Canada Revenue Agency, Service Canada and other dept’s for the formulation of a Data Stewardship methodology  As part of its major transformation project, Service Canada will be implementing some portions of the methodology which include information quality  Data Stewardship is defined as the act or process of ensuring that corporate data is managed as an asset, according to accepted practices through its lifecycle. As a necessary component of IM, data stewardship helps achieve inter-operability, improve data quality, and increase both data sharing and semantic understanding.  Data Quality Processes: Data lifecycle management Data capture, validity and integrity Data audit  IQ Factors: Data Quality readiness Assessment: The extent to which processes for ensuring data / information are accurate, consistent, complete and current IQ Problem Handling: The status of data / information quality incident reporting, analysis, problem handling and resolution Costing of IQ: The use of IM financial management to establish the true cost of non-quality data within the enterprise IQ Improvement Actions: The processes in place to leverage best practices and adopt and promote a culture of continuous improvement

16. 16 Service Canada IQ Initiatives (Cont’d)  Service Canada One Client View:  The One Client View initiative is a multi-year initiative that will enable timely access to the complete set of client information that is required for the delivery of seamless citizen-centered service to Canadians citizens and businesses. One major component of OCV is accurate, timely, non-redundant and secure information.  Service Canada Integrity and Operational Risk Management Project:  An initiative to establish a national risk management program for proactive, risk based service delivery. This initiative is based on analyzing existing data, assessing the data quality and pointing out the challenges and opportunities for improving data quality at two levels: 1) at the origin of data and 2) at the data mart level using ECTL - Extract, Cleanse, Transform and Load  Other Service Canada IM current and future initiatives  Corporate Client Data Model  Corporate data dictionary using the CASE tool the Oracle Designer  Corporate data management process for using standard structure and data content for code/reference tables  Corporate naming conventions for OLTP, Data Warehouse and Data Mart systems  Address validation software like Street Perfect  Corporate strategy for ECM – Enterprise Content Management (future initiative)

17. In the next lecture … Meet MDM, a key element of enterprise information management

18. Questions?

19. NEWS PRESENTATION (SIGN UP NOW!)