Midwest IMS RUG 09_2013 - Data Governance for IMS.pdf

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Midwest IMS RUG 09_2013 - Data Governance for IMS.pdf

  1. 1. © 2013 IBM Corporation ® IMS IMS and Data Governance Overview
  2. 2. © 2013 IBM Corporation2 IMS IMS and Data Governance Why discuss data governance? What is data governance? How does IMS implement data governance? What are the today’s challenges?
  3. 3. © 2013 IBM Corporation IMS What happens when you’re NOT in control of your business data… 3 Heathcare – “Dozens of women were told wrongly that their smear test had revealed a separate infection after a hospital error, an independent inquiry has found…. Confusion arose because the hospital decided to use a code number to signify “no infections”, not realizing that it was already in use at the health authority where it meant “multiple infections”…. Retail – “Hackers have stolen 4.2 million credit and debit card details from a US supermarket chain by swiping the data during payment authorization transmissions in stores..” Banking – “A major US bank has lost computer data tapes containing personal information on up to 1.2 million federal employees, including some members of the U.S. Senate…. The lost data includes Social Security numbers and account information that could make customers of a federal government charge card program vulnerable to identity theft….” Banking – “A rogue trader accused of the world’s biggest banking fraud was on the run last night after fake accounts with losses of £3.7 billion were uncovered…. The trader used his inside knowledge of the bank’s control procedures to hack into its computers and erase all traces of his alleged fraud. Mr Leeson said ”Rogue trading is probably a daily occurrence within the financial markets. What shocked me was the size. I never believed it would get to this degree of loss.” Public Sector – “Two computer discs holding the personal details of all families in the UK with a child under 16 have gone missing…. The Child Benefit data on then includes name, address, date of birth, National Insurance number and, where relevant, bank details of 25million people…” WASHINGTON – “The FINRA announced today it has censured and fined a financial services company $370,000 for making hundreds of late disclosure to FINRA’s Central Registration Depository (CRD) of information about its brokers, including customer complaints, regulatory actions and criminal disclosures. Investors, regulators and others rely heavily on the accuracy and completeness of the information in the CRD public reporting system – and, in turn, the integrity of that system depends on timely and accurate reporting by firms.”
  4. 4. © 2013 IBM Corporation IMS …. Resulting in a broad range of potentially life threatening consequences 4 Heathcare – Dozens of women were told wrongly that their smear test had revealed a separate infection after a hospital error, an independent inquiry has found…. Confusion arose because the hospital decided to use a code number to signify “no infections”, not realizing that it was already in use at the health authority where it meant “multiple infections”…. Retail – Hackers have stolen 4.2 million credit and debit card details from a US supermarket chain by swiping the data during payment authorization transmissions in stores.. Banking – A major US bank has lost computer data tapes containing personal information on up to 1.2 million federel employees, including some members of the U.S. Senate…. The lost data includes Social Security numbers and account information that could make customers of a federal government charge card program vulnerable to identity theft….” Banking – Rogue trader accused of the world’s biggest banking fraud was on the run last night after fake accounts with losses of £3.7 billion were uncovered…. The trader used his inside knowledge of the bank’s control procedures to hack into its computers and erase all traces of his alleged fraud. Mr Leeson said ”Rogue trading is probably a daily occurrence within the financial markets. What shocked me was the size. I never believed it would get to this degree of loss.” Public Sector – Two computer discs holding the personal details of all families in the UK with a child under 16 have gone missing…. The Child Benefit data on then includes name, address, date of birth, National Insurance number and, where relevant, bank details of 25million people…” WASHINGTON – The FINRA announced today it has censured and fined a financial services company $370,000 for making hundreds of late disclosure to FINRA’s Central Registration Depository (CRD) of information about its brokers, including customer complaints, regulatory actions and criminal disclosures. “Investors, regulators and others rely heavily on the accuracy and completeness of the information in the CRD public reporting system – and, in turn, the integrity of that system depends on timely and accurate reporting by firms.” s s s s s s Incorrect classification.. Life threatening consequences Ineffective Security.. Brand damage Financial loss Physical Data Loss.. Identity Theft Late Disclosures.. Inaccurate data Heavy Fines, Legal implications Physical unprotected Data Loss.. Fraud on a massive scale Poor Internal Controls.. Bankruptcy, Financial ruin, penalties Need to manage the information
  5. 5. © 2012 IBM Corporation IMS What is Data Governance and Information Governance? • Data: – Structured – Unstructured – Metadata – Video, Audio, Multi-Media – Print, Email, and Archived – Software Code – Patents, IP – Protocols, Message Streams • Information: – Data which has been processed and transformed in order to provide insight and answers to business questions Effective management of data quality needs initiatives which: • span the whole organisation – not just within the silos • get to the root of the problem – not just the symptoms • allocate clear, measurable responsibilities This is Data Governance Effective use of business information needs a framework which: • manages the underlying data assets effectively through Data Governance • matches the supply of information with its demand from the business • underpins the business requirements with a solid Information architecture Information Governance: ‘The specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival, and deletion of information. It includes the processes, roles, standards, and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.’ ~ Gartner Inc. This is Information Governance As a business, we need to use these terms consistently
  6. 6. © 2013 IBM Corporation IMS Data Governance Creates Order out of Data Chaos   Orchestrate people, process and technology toward a common goal  Promotes collaboration  Derive maximum value from information Data Governance is the exercise of decision rights toData Governance is the exercise of decision rights to optimize, secure and leverage data as an enterprise asset.optimize, secure and leverage data as an enterprise asset. Governing the creation, management and usage ofGoverning the creation, management and usage of enterprise data is not an option any longer. It is:enterprise data is not an option any longer. It is: Expected by your customers Demanded by the executives  Enforced by regulators/auditors  Leverage information as an enterprise asset to drive opportunities  Safeguards information  Ensure highest quality  Manage it throughout lifecycle
  7. 7. © 2012 IBM Corporation IMS IBM Information Governance approach A good Information Governance program supports compliance initiatives,A good Information Governance program supports compliance initiatives, reduces cost and minimizes risk to enable sustainable profitable growthreduces cost and minimizes risk to enable sustainable profitable growth Validated by the Information Governance Council Top global companies, business partners and industry experts http://www.infogovcommunity.com/ Applied with a Unified Process Requirements driven aligned with business goals to solve business problems Accelerates deployment with Council built Maturity Model A framework (disciplines, levels) as starting point and for prioritizing actions
  8. 8. © 2013 IBM Corporation IMS Information Governance Maturity Model Data Quality Management Information Life-Cycle Management Information Security and Privacy Core Disciplines Data Risk Management & Compliance Business Outcomes / Reporting Value Creation Data Architecture Classification & Metadata Audit Information Logging & Reporting Supporting Disciplines Organizational Structures & Awareness Enablers Policy Data Stewardship Requires Supports Business Intelligence & Advanced Analytics Enhances Requires
  9. 9. © 2012 IBM Corporation IMS IBM Information Governance approach
  10. 10. © 2013 IBM Corporation IMS Information Governance Maturity Model Data Quality Management Information Life-Cycle Management Information Security and Privacy Core Disciplines Data Risk Management & Compliance Business Outcomes / Reporting Value Creation Data Architecture Classification & Metadata Audit Information Logging & Reporting Supporting Disciplines Organizational Structures & Awareness Enablers Policy Data Stewardship Requires Supports Business Intelligence & Advanced Analytics Enhances Requires
  11. 11. © 2013 IBM Corporation11 IMS IMS – All You Need in One  A z/OS middleware that inherits all the strength of zEnterprise  A Messaging & Transaction Manager – Based on a messaging and queuing paradigm – High-volume, rapid response transaction management for application programs accessing IMS and/or DB2 databases, MQ queues – “Universal” Application Connectivity for SOA integration – Integrated with Business Rules & Business Events  A Database Manager – Central point of control and access for the IMS databases – A hierarchical database model • Used by companies needing high transaction rates • Provides database recoverability – Now provide a “Universal” Database Connectivity based on JDBC / DRDA • Lot of new features in that space! Stay tuned  A Batch Manager – Standalone z/OS batch support – Batch processing regions centrally managed by the IMS control region • Managing the batch-oriented programs — providing checkpoint/restart services
  12. 12. © 2013 IBM Corporation12 IMS Dynamics of an Information Ecosystem … with IMS in perspective Reduce the Cost of Data Trust & Protect InformationMachine Data Application Data Transaction Social Media Content Analytic Applications Mobile/Cloud Applications THE INFORMATION SUPPLY CHAIN Manage Integrate & Govern New Insights From Big Data Analyze Enterprise Applications Govern Quality Security & Privacy Lifecycle Standards
  13. 13. © 2013 IBM Corporation13 IMS z/OS Database Manager Positioning  Hierarchical – Operational Data – Very High performance – Real time mission critical work – Time sensitive response oriented – Complex data structures with many levels  Relational – Tabular data – Temporal data – Warehousing – Complex and/or ad hoc queries – Decision support 13 CUSTOMER BILL COMMAND ARTICLE PRODUCT CUSTOMERCUSTOMER BILLBILL COMMANDCOMMAND PRODUCTPRODUCT ARTICLE DB2 for z/OS Enhanced for business analytics IMS on z/OS Built for performance and recovery
  14. 14. © 2013 IBM Corporation14 IMS IMS 12 on zEC12 provides superlative Security, Compliance, Performance, Efficiency, and Industrial-Strength Transaction and Database management Revolutionize your IMS with zEC12!  Most secure system with 99.999% reliability  Optimized data serving with largest cache in the industry  Leadership in performance with z/OS using the 5.5 GHz 6 way processor chip  Ability to process terabytes of data quickly  Millions of transactions per day with sub second response times  Faster problem determination with IBM zAware for improved availability  Java exploitation of Transactional Execution for increased parallelism and scalability  A 31% improvement to PL/I-based CPU intensive applications based on NEW Enterprise PL/I for z/OS and Updated C/C++ compilers  Increased Performance through Flash Express of large pages via z/OS 1.13 Additional gains include:  XML hardware acceleration; streamline and secure valuable SOA applications with IBM WebSphere DataPower  Centrally monitored, controlled and automated operations across heterogeneous environments with IBM Tivoli Omegamon IMS 12 on zEC12 shows up to 30% improvement in transaction rate
  15. 15. © 2013 IBM Corporation15 IMS IMS DB in Perspective Native Quality of Services   High Capacity HALDB & DEDB High Availability IMS Data Sharing Performance without CPU extra cost 1/2 the MIPS and 1/2 the DASD of relational Application Development   Multi-language AD support COBOL, PLI, C, … JAVA XML Support Decomposed or Intact Java SQL support (JDBC) IMS Java Access from CICS and IMS applications, from Batch IMS since early days Open Access and Data Integration DRDA Universal Driver with IMS 11+ Open Database Data Management   Metadata Management IMS 12+ Catalog Advanced Space Management DFSMS family Health Check Pointer validation & repair Backup and Recovery Solutions IMS Tools Reorganization for improved performance IMS Tools Enterprise Data Governance   Compression and Encryption InfoSphere Guardium Tools Audit for every access InfoSphere Guardium Tools Data Masking InfoSphere OPTIM Family Creation of Test databases InfoSphere OPTIM Family Data Growth Management InfoSphere OPTIM Family Operational Business Analytics & Reporting COGNOS & SPSS Information Integration & Data Synchronization   Fast integration in Web 2.0 applications IMS Open database Data Federation InfoSphere Classic Federation Replication to IMS – Towards Active / Active solution InfoSphere IMS Replication Replication to Relational InfoSphere Classic Replication Server & Classic CDC Publication of DB Changes InfoSphere Classic Data Event Publisher
  16. 16. © 2013 IBM Corporation16 IMS IMS Explorer for Development – View Examples Much easier to understand the database structure SQL & result sets z/OS Perspective
  17. 17. © 2013 IBM Corporation17 IMS IMS Explorer for Development – View Examples Multiple Logically related databases Manufacturing – assembly parts arrival time to assembly line
  18. 18. © 2013 IBM Corporation18 IMS 18  Easily refresh & maintain right sized non-production environments, while reducing storage costs  Improve application quality and deploy new functionality more quickly  Speed understanding and project time through relationship discovery within and across data sources  Understand sensitive data to protect and secure it InfoSphere Optim solutions Managing data throughout its lifecycle in heterogeneous environments ProductionProduction TrainingTraining DevelopmentDevelopment TestTest ArchiveArchive •Subset •Mask •Compare •Refresh  Reduce hardware, storage & maintenance costs  Streamline application upgrades and improve application performance Data Growth Management Test Data Management Data Masking  Protect sensitive information from misuse & fraud  Prevent data breaches and associated fines RetireRetire Discover Understand Classify Discover  Safely retire legacy & redundant applications while retaining the data  Ensure application-independent access to archive data Application Retirement
  19. 19. © 2013 IBM Corporation19 IMS 19 Managing Test Data in Non-Production – OPTIM Test Data Management  Create right-sized test environments, providing support across multiple applications, databases and operating systems  Deploy new functionality quicker and with improved quality & customer satisfaction  Compare results during successive test runs to pinpoint defects and errors  On z/OS: Support for DB2, IMS, VSAM 100 GB Development 100 GB Test 100 GB100 GB Training 100 GB100 GB QA Production or Production Clone Subset 1 TB http://www-01.ibm.com/software/data/data-management/optim/core/test-data-management-solution-zos
  20. 20. © 2013 IBM Corporation20 IMS 20 Data Masking and Protection - OPTIM Data Masking Option  Reduce risk of exposure during data theft – Fines and lawsuits – Avoid the negative publicity – Customer loss – Loss of intellectual property Personal identifiable information (PII) is masked with realistic but fictional data for testing & development purposes. http://www-01.ibm.com/software/data/data-management/optim/core/data-privacy-solution-zos/  De-identify for privacy protection  Deploy multiple masking algorithms  Provide consistency across environments and iterations  No value to hackers  Enable off-shore testing  On z/OS: Support for DB2, IMS DB, VSAM
  21. 21. © 2013 IBM Corporation21 IMS InfoSphere Optim Data Masking Solution / Option Example 2Example 1 PersNbr FstNEvtOwn LstNEvtOwn 27645 Elliot Flynn 27645 Elliot Flynn Event TableEvent Table PersNbr FstNEvtOwn LstNEvtOwn 10002 Pablo Picasso 10002 Pablo Picasso Event TableEvent Table Personal Info TablePersonal Info Table PersNbr FirstName LastName 08054 Alice Bennett 19101 Carl Davis 27645 Elliot Flynn Personal Info TablePersonal Info Table PersNbr FirstName LastName 10000 Jeanne Renoir 10001 Claude Monet 10002 Pablo Picasso Data masking techniques include: String literal values Character substrings Random or sequential numbers Arithmetic expressions Concatenated expressions Date aging Lookup values Generic mask Referential integrity is maintained with key propagation Patient InformationPatient Information Patient No. SSN Name Address City State Zip 112233 123-45-6789 Amanda Winters 40 Bayberry Drive Elgin IL 60123 123456 333-22-4444 Erica Schafer 12 Murray Court Austin TX 78704 Data is masked with contextually correct data to preserve integrity of test data Satisfy Privacy regulations Reduce risk of data breaches Maintain value of test data
  22. 22. © 2013 IBM Corporation22 IMS Managing Data Growth in Production – OPTIM Data Growth  Segregate historical data to secure archive  Align performance to service level targets  Reclaim under utilized capacity  On z/OS: Support for DB2, IMS DB, VSAM Current Production Historical Selective Retrieval Archived Data/Metadata Reporting Data Historical Data Reference Data Selective Archive Universal Access to Application Data Application Application XML ODBC / JDBC
  23. 23. © 2013 IBM Corporation23 IMS InfoSphere Optim Application Retirement  Preserve application data in its business context  Retire out-of-date packaged applications as well as legacy custom applications  Shut down legacy system without a replacement Infrastructure before RetirementInfrastructure before Retirement Archived Data after ConsolidationArchived Data after Consolidation ` User Archive DataArchive Engine ` User ` User ` User DatabaseApplication Data ` User DatabaseApplication Data ` User DatabaseApplication Data
  24. 24. © 2013 IBM Corporation24 IMS Secure & Protect High Value Databases - Guardium Data Encryption http://www-01.ibm.com/software/data/guardium/  Provides: z/OS integrated software support for data encryption  Operating System S/W API Interface to Cryptographic Hardware − CEX2/3C/4C hardware feature  Enhanced Key Management for key creation and distribution − Public and private keys − Secure and clear keys − Master keys  Created keys are stored/accessed in the Cryptographic Key Data Set (CKDS) with unique key label − CKDS itself is secured via Security Access Facility
  25. 25. © 2013 IBM Corporation25 IMS Secure & Protect High Value Databases - Guardium Data Encryption  Non-invasive architecture  Clear and Secure Keys  Hardware enabled = Minimal performance impact  Supports DES, TDES & AES algorithms  Supports 56, 128 & 256 bit encryption  Installed at the IMS segment level  No Database or application changes http://www-01.ibm.com/software/data/guardium/ Clear text Cryptotext
  26. 26. © 2013 IBM Corporation26 IMS Secure & Protect High Value Databases - Guardium Real-Time Database Monitoring  Non-invasive architecture  Heterogeneous, cross-DBMS solution  Does not rely on native DBMS logs  Minimal performance impact  No DBMS or application changes  Activity logs cannot be erased by attackers or rogue DBAs  Automated compliance reporting, sign-offs & escalations (SOX, PCI, NIST, etc.)  Granular, real-time policies & auditing  Single point of monitoring across DBMSs DB2 & DB2/z http://www-01.ibm.com/software/data/guardium/ IMS VSAM
  27. 27. Copyrite IBM 2013 IMS Secure & Protect High Value Databases - Guardium Real-Time Database Monitoring Architecture
  28. 28. Copyrite IBM 2013 IMS Here is shown an IMS BMP job that ran for 2 minutes. A jobname of TSTCMDDC accessed database AUECCMDD. You can also see the UserID and the PSB being used by the job. Under IMS Context column the calls in sequence made to the database are seen. Secure & Protect High Value Databases - Guardium Real-Time Database Monitoring Sample report
  29. 29. Copyrite IBM 2013 IMS Secure & Protect High Value Databases - Guardium Real-Time Database Monitoring Sample report Here is shown an IMS BMP job that ran for 2 minutes. A jobname of TSTCMDDC accessed database AUECCMDD. You can also see the UserID and the PSB being used by the job. Under IMS Context column the calls in sequence made to the database are seen.
  30. 30. © 2013 IBM Corporation30 IMS Operational Business Analytics on IMS Data Cognos Reporting with IMS 12  Benefits: – Ad hoc reporting access – Report on data reflecting the most current state of the business – React faster to trusted data – Market-leading BI solution for IMS customers  Roadmap for customers – Cognos 10.2 & IMS V11: IMS 11 JDBC driver is NOT certified with Cognos 10.2. • Even if Open database architecture is available. – Cognos 10.2 & IMS V12 : IMS 12 JDBC driver with Catalog is certified with Cognos 10.2. • New functions that allow to get enhanced predicats exploited by Cognos • IMS catalog for z/OS centralized metadata management Cognos BI Report Authoring Publishe d Reports Cognos Framework Manager IMSConsumer Author JDBC Data Store Data Model IMS Universal JDBC
  31. 31. © 2013 IBM Corporation31 IMS Operational Business Analytics on IMS Data Cognos Reporting with IMS 12 Avail with Cognos 10.2
  32. 32. © 2013 IBM Corporation32 IMS DataPower Appliance  Why an Appliance for SOA? – Hardened, specialized hardware for helping to integrate, secure & accelerate SOA – Many functions integrated into a single device – Higher levels of security assurance certifications require hardware – Enables run-time SOA governance and policy enforcement – Higher performance with hardware acceleration – Addresses the divergent needs of different groups: • enterprise architects, network operations, security operations, identity management, web services developers – Simplified deployment and ongoing management – Proven Green / IT Efficiency Value • Appliance performs XML and Web services security processing as much as 72x faster than server-based systems • Impact: Same tasks accomplished with reduced system footprint and power consumption
  33. 33. © 2013 IBM Corporation33 IMS DataPower Appliance The WebSphere DataPower Integration Appliance is a purpose built hardware platform that delivers rapid data transformations for cloud and mobile applications, supports secured and scalable business integration, and provides an edge of network security gateway in a single drop-in appliance. Integration appliance Includes all features of the Security and Acceleration appliances
  34. 34. © 2013 IBM Corporation34 IMS DataPower Appliance  IMS Integration (XI50, XI50B, XI50z, XI52, XB60, XB62...) – Three interfaces to get to IMS: • IMS Connect Client » Access to IMS applications using a DataPower embedded IMSClientConnect handler to IMS Connect • Soap » Access to IMS web services via the IMS SOAP Gateway • MQ Client » Access to IMS applications using an MQ server on system z and the MQ Bridge for IMS
  35. 35. © 2013 IBM Corporation35 IMS Technologies are in Place for Mainframe Apps Extensibility WAS MQ CICS & IMS Connectors Data Warehouse XML Asset Mgmt SOA Business Processes Compliance Service Mgmt Customers are here today Technology is in place to go here next Hybrid Computing Workload Optimization Analytics ASM & Cobol & PLI & C Java Application Investment Protection zLinux & zBX Business Rules
  36. 36. © 2013 IBM Corporation36 IMS Big Data and IMS Databases  IMS integration with the BigInsights application connectors – Merge trusted OLTP data with the Big Data platform  Integrate IMS with the Big Data Machine Data Accelerator (MDA) – Correlate log records from off-platform application servers with IMS log records Traditional Approach Structured, analytical, logical New Approach Creative, holistic thought, intuition Data Warehouse Traditional Sources Structured Repeatable Linear Hadoop Streams New Sources Unstructured Exploratory Iterative Web Logs Social Data Text Data: emails Sensor data: images RFID Enterprise Integration IMSIMS OperationalOperational DataData Transaction Data Internal App Data Mainframe Data OLTP System Data
  37. 37. © 2013 IBM Corporation37 IMS An enterprise information hub on a single integrated platform Transaction Processing Systems (OLTP) Predictive Analytics Best in Analytics Industry recognized leader in Business Analytics and Data Warehousing solutions Best in Flexibility Best in OLTP & Transactional Solutions Industry recognized leader for mission critical transactional systems Business Analytics zEnterprise Recognized leader in workload management with proven security, availability and recoverability DB2 Analytics Accelerator for z/OS Powered by Netezza Recognized leader in cost- effective high speed deep analytics Data Mart Data Mart Consolidation Unprecedented mixed workload flexibility and virtualization providing the most options for cost effective consolidation Data Mart Data Mart Data Mart Ability to start with your most critical business issues, quickly realize business value, and evolve without re-architecting Best in Batch workload Efficient execution environment close to the data with first class I/O Technology Batch workload
  38. 38. Copyrite IBM 2013 IMS Why Assess Information Maturity  Information Maturity is typically assessed to provide a snapshot in time of an organisation's ability to manage information, as defined by the maturity model  This is most often used to benchmark and compare maturity • Across time within an organisation • Between organisations  With the aim to improve the ability to manage information over time • Reduce the time needed to access information • Reduce stored information complexity • Lower costs through an optimized infrastructure • Gain insight through analysis & discovery • Leverage information for business transformation • Gain control over master data • Manage risk and compliance via a single version of truth  This implies that an information maturity assessment should be an ongoing activity
  39. 39. IMS A Model for Information Maturity: An Evolution for our Clients BusinessValueof Information Information Management Maturity • Data: All relevant internal and external information seamless and shared. Additional sources easily added • Integration: Virtualized Information Services • Applications: Dynamic Application Assembly • Infrastructure: Dynamically, re-configurable; Sense & Respond • Flexible, adaptive business environments across enterprise and extraprise • Enablement of strategic business innovation • Optimization of Business performance and operations • Strategic insight • Data: Seamless & shared; Information separated from process; Full integration of structured and unstructured • Integration: Information Available as a Service • Applications: Process Integration via Services; in line bus apps • Infrastructure: Resilient SOA; Technology Neutral • Role-based, work environments commonplace • Fully embedded capabilities within workflow, processes & systems • Information-enabled Process innovation • Enhanced Business Process & Operations Management • Foresight, predictive analytics • Data: Standards based, structured & some unstructured • Integration: Integration of silos; Virtualization of Information • Applications: Services-based • Infrastructure: Component/Emerging SOA, Platform Specific • Introduction of contextual, role-based, work environments • Enhanced levels of automation • Enhancement of existing processes and applications • Integrated business performance management • Single version of truth • Insight thru analytics, real-time • Data: Structured content; organized • Integration: Some integration; silos still remain • Applications: Component-based applications • Infrastructure: Layered Architecture, Platform Specific • Basic search, query, reporting and analytics • Some automation • Disparate work environments • Limited enterprise visibility • Multiple versions of the truth • Data: Structured content, static • Integration: Disjointed, Siloed, non-integrated solutions • Applications: Stand alone modules; application-dependent • Infrastructure: Monolithic, Platform Specific • Basic reporting & spreadsheet- based • Manual, ad hoc dependence • Information overload • No version of truth • Hindsight based Information as a Competitive Differentiator Information to Enable Innovation Information as a Strategic Asset Information to Manage the Business Data to Run the Business 1 2 3 4 5
  40. 40. © 2012 IBM Corporation IMS 40 Data Governance Workshop Key Steps Conduct Interviews of Key IT/Business Leaders and DG Council Assess Data Governance Maturity and Target Capabilities Develop a Roadmap for Delivering Capabilities Develop Recommendations Next Steps Identify Gap to Future State (18 months) © 2011 IBM Corporation 16 Information Maturity Assessment – Gap Summary 1. Organizational Structures and Awareness 2. Data Stewardship 3. Policy 4. Value Creation 5. Data Risk Management & Compliance 6. Information Security & Privacy 7. Data Architecture 8. Data Quality Management 9. Classification & Metadata 10. Information Life-Cycle Management Optimizing Level 5 11. Audit Information Logging & Reporting Maturity Category Quantitatively ManagedDefinedManagedInitial Level 4Level 3Level 2Level 1 Scope of Services Assess current state Determine future state (in 12- 18 months) Identify required capabilities and initiatives Capability Gap © 2011 IBM Corporation 22 2011 2012 ….. Implementation Roadmap 1. Organizational Structures and Awareness 2. Data Stewardship 3. Policy 4. Value Creation 5. Data Risk Management & Compliance 6.Information Security & Privacy July OSA1: Communication and DG Ownership OSA2: DGC undertaking critical projects OSA3: Establish COE & Execution committee OSA4: Data Stewards across Biz/IT areas DS1: Stewards clearly identified/defined DS2: Pilot program across departments DS3: Data Stewards Accountability POL1: Policy prioritization POL2: Flushing Policy Details POL3: Policies communication, enforcement and compliance VC1: Develop DG Scorecard VC2: Selective LOB projects using DG VC3: Selective cross-LOB projects using DG Assessment for baseline and establish Data Centric Security Reference Architecture Vulnerability Assessment Data Discovery (structured) Activity Monitoring of current privileged user access to systems Verify that Level 4 has started by comparing governance success with assessment findings for people and process. Adjust Privileged Access Rights ‘Sensitive’ Data Policy Document Controls in placemappedto requirements for data security and compliance * Risk Assessment for current Controls Data Centric Security Architecture Automated Activity Monitoring Establish and Mandate De-Identification program for non-production systems (Test, QA, Dev) Align perimeter & Identity controls with Activity Monitoring Baseline Vulnerability Assessment Pre Assessment Internal Survey © 2011 IBM Corporation 14 Pre-Workshop Survey Results - Executive Summary © 2011 IBM Corporation 21 Next Steps 1. Communication of Workshop assessment results 2. Validate Data Governance Plan and Objectives  Alignment of current business and IT initiatives with IBM workshop assessment  Prioritize Data Governance initiatives and integrate with planned project sequence; for short term and long term 3. Create Discover Roadmap; with prioritized initiatives 4. Implement a Data Governance Project Management Office  Obtain Executive sponsorship  Define structure, responsibilities, and identify core team  Define quality metrics and reporting 5. Conduct Detailed workshop / Execution of prioritized initiatives. E.g. Data Quality, Classification and Metadata Management  Adopt Metadata Driven Data Governance in IT  Acquire Metadata Management, Analysis, and Quality Tools  Analyze current data quality  Implement Process Improvement for Data Quality 6. Define the metrics to identify how the business realizes returns on investment in the collection, production, and use of data. 7. Identify areas where additional consulting would accelerate timeline. © 2011 IBM Corporation 8 Key Observations and Opportunities  Efficiency  Data Integrity Policy, Standards, Data definition1  Monitored Data Quality (early Risk ID)  Quantified Risk Metrics – Data Quality, Business Impact4  Data and analytics optimization for the business  Higher ROI / faster payback Value Creation process ( Enterprise and LOB)3 OpportunityObservation R E F  Cost avoidance  Risk mitigation Unstructured content7  Risk mitigation & complianceInternal data access and sensitive data location/control 6  Ownership  Efficiency  Data Quality Organizational Effectiveness and Data Accountability (Stewardship) 5  Communication  SME availability  Level of influence Organizational Awareness and Enterprise Solutions 2
  41. 41. © 2013 IBM Corporation Information Governance – Company’s Assessment results Data Quality Management/ Discovery Information Life-Cycle Management Information Security and Privacy Core Disciplines Data Risk Management & Compliance Business Outcomes / Reporting Value Creation Data Architecture Classification & Metadata Audit Information Logging & Reporting Supporting Disciplines Organizational Structures & Awareness Enabler s Policy Data Stewardship Require s Support s Enhanc e
  42. 42. © 2013 IBM Corporation Information Governance Maturity Assessment current and target mapping Assessed current state Planned future state Prioritized* Domains with Recommended Action Plan Prioritization has been made by Workshop participants based on : • Highest gaps between current and to-be positions • Evaluation of acceptance capability / Feasability by the Organization
  43. 43. © 2013 IBM Corporation43 IMS IMS and Data Governance Palisades, New York: May 14-15, 2013 Chicago: May 21-22, 2013 São Paulo, BR: June 3, 2013 Costa Mesa, CA: June 4-5, 2013 Boeblingen, DE : June 5, 2013 Taipei, Taiwan: June 2013 United Kingdom: June 2013 Charlotte, NC: June 25-26 2013
  44. 44. © 2013 IBM Corporation44 IMS IMS and Data Governance Data governance Regulation compliance Avoiding media embarrassment Competitive edge IMS Enterprise Suite V2.2 Explorer Infosphere Optim for Test Data Management Infosphere Optim for data and application retirement Infosphere Guardium for data protection Encryption of IMS data S-Tap monitors Data Maturity assessment workshop Information Governance Wildfire Workshops
  45. 45. Data Governance for System z Workshop (DGSYSZ) San Francisco, CA October 14-15, 2013 This workshop like all Wildfire Workshops is offered at no-fee to qualified customers. IBM Advanced Technical Skills Wildfire Workshop With the complexity of today’s information ecosystems, organizations must improve the level of trust users have in information, ensure consistency of data, and establish safeguards over information. When information is trusted, business can optimize outcomes. Join us for one and a half days at the IBM Data Governance for System z Workshop. Meet with experts to understand business and IT implications of Data Governance, Real Time Analytics, and Operational Data Warehousing, and learn how the IBM System z platform can help you meet, simplify, and reduce the cost of meeting your data governance requirements. Workshop Topics: • Drivers of Information Governance • Data & Information Governance, What are They? • Enablers of Enterprise Data Governance Strategy − Policy − Data Stewardship − Organizational Structure & Awareness • Pillars of Data Governance − Data Quality Management − Information Life Cycle − Security, Privacy, & Compliance − Master Data Management • Enterprise Data Governance on System z • Data Architecture on System z • Role of DB2 for z/OS & IMS in Data Governance • Operational Analytics & Real Time Analytics on System z • Data Governance Assessment Audience: Attendance of this workshop is recommended for Chief Technology Officers, Architects, Data Stewards, IT Management, Owners of Business Analytics, Data Warehouse Owners, Line of Business Application Owners, and DBA Management, and Test & Development Management. Enrollment: To enroll please work with your IBM sales representative and enroll together by visiting the following website: https://www.ibm.com/servers/eserver/zseries/education/topgun/ enrollment/esfldedu.nsf/0/0D284179789982B5852578B8004C 07B4?EditDocument For more information on enrollment or for other Wildfire administration questions, contact Judy Vadnais-Keute at judyv@us.ibm.com , and for more information on this Data Governance
  46. 46. © 2012 IBM Corporation IMS 5/22/13 IBM Smart Analytics System 9600

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