© 2014 IBM Corporation
Using the Information Server Toolset to deliver end to
end traceability
Tommie Hallin
Rob Cooper
In...
© 2014 IBM Corporation
Introduction
Tommie Hallin, Senior Information Architect – IBM GBS, BAO
Rob Cooper, Senior Informat...
© 2014 IBM Corporation33
End to end traceability – in the context for this presentation
FRONT LINE
APPLICATIONS
OLAP
DATA ...
© 2014 IBM Corporation
Understanding how to create value from data has been the focus of IBM’s
analytics studies for 5 yea...
© 2014 IBM Corporation5
Analytics correlates to performance
Source: Analytics: The New Path to Value, a joint MIT Sloan Ma...
© 2014 IBM Corporation
Top Performers are more sophisticated in handling information
6 Source: Analytics: The New Path to ...
© 2014 IBM Corporation
Transformed organizations master three competencies to drive
sustainable competitive advantage
7
So...
© 2014 IBM Corporation
Manage The Data
Managing the Information Landscape
Source
s Business
Initiativeslegacy
apps
dbs
xls...
© 2014 IBM Corporation
Transformed organizations need resist the urge to perfect the data
9
Source: The New Intelligent En...
© 2011 IBM Corporation10
Understand The Data
Profiling using Information Analyzer
Cleanse
Master
Monitor
Monitor the quali...
© 2014 IBM Corporation
Data and Integration Modeling
Common understanding of the design
Database development requires a
“b...
© 2014 IBM Corporation
Act On The Data
Trust and traceability enables action
12
Information Integration: ETL,
Data Quality...
© 2014 IBM Corporation
– Key Business End Users
– Program Manager / Project Lead
– Governance Stewart (SME)
– Security & P...
© 2014 IBM Corporation
Trust in data – there is still a long way to go
Two thirds of the leaders express confidence in dat...
© 2014 IBM Corporation
Three characteristics that distinguish Transformed organizations most
15
Source: The New Intelligen...
© 2014 IBM Corporation
Over to Rob
16
© 2014 IBM Corporation
Simplify Integration Increase trust and
confidence in information
Increase compliance to
standards
...
© 2014 IBM Corporation
Information Server Metadata Components
Metadata Management
Analyze / Understand
Data Lineage
Impact...
© 2014 IBM Corporation
Information Server
Common
Metadata Repository
InfoSphere
Data Architect
(Data Model)
Inormation Ana...
© 2014 IBM Corporation
InfoSphere Data Architect (Manage & Understand)
Data Models
– Sources (Regular / Migration)
– Targe...
© 2014 IBM Corporation
InfoSphere Business Glossary (Manage & Understand)
Common Terminology
Connect business with IT
Asso...
© 2014 IBM Corporation
InfoSphere Information Analyzer (Understand)
Data Profiling tool
– Understand the source data
– Reg...
© 2014 IBM Corporation
InfoSphere FastTrack (Manage & Understand)
Source to Target Mapping Specifications
Metadata availab...
© 2014 IBM Corporation
InfoSphere Metadata Asset Manager (Manage)
Managed Metadata Import
– Metadata Bridges
– InfoSphere ...
© 2014 IBM Corporation
InfoSphere DataStage (Manage)
DataStage consists of three different components
– Administrator
– De...
© 2014 IBM Corporation
InfoSphere Metadata Workbench (Manage, Understand & Act)
Manage and Understand
– Implemented Data R...
© 2014 IBM Corporation
InfoSphere Operations Console (Understand & Act)
Operations Console
– Job runtime activity
– Logs
–...
© 2014 IBM Corporation
Summary
Information Server can provide a single repository for your BI solution
Design and implemen...
© 2014 IBM Corporation
End to End Traceability enables...
Trust and Understanding in solutions
Provides confidence to deci...
© 2014 IBM Corporation30
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Using the information server toolset to deliver end to end traceability

  1. 1. © 2014 IBM Corporation Using the Information Server Toolset to deliver end to end traceability Tommie Hallin Rob Cooper Information Server User Group 2014 1
  2. 2. © 2014 IBM Corporation Introduction Tommie Hallin, Senior Information Architect – IBM GBS, BAO Rob Cooper, Senior Information Managment Consultant Abstract Using the Information Server Toolset to deliver end to end traceability Tommie and Rob have used the Information Server Toolset on a number of analytics and data warehousing projects to deliver end to end traceability. The presentation focuses on describing Why, What and How end to end traceability is important and share experiences and best practices from projects and from many years of consulting. 2
  3. 3. © 2014 IBM Corporation33 End to end traceability – in the context for this presentation FRONT LINE APPLICATIONS OLAP DATA INTEGRATION / DATA QUALITY / ETL SOURCE SYSTEMS, DATA MARTS, MASTER DATA DATA WAREHOUSE Analytics Data Integration Data Warehouse
  4. 4. © 2014 IBM Corporation Understanding how to create value from data has been the focus of IBM’s analytics studies for 5 years http://www-935.ibm.com/services/us/gbs/thoughtleadership/ 4 Analytics: The new path to value Operationalizing analytics in sophisticated organizations Analytics: The widening divide Mastering analytic competencies Analytics: The real world use of big data Fundamentals of big data Analytics: A blueprint for value Extracting value from data and analytics 2010 2011 2012 2013 The intelligent enterprise and Breaking away with BAO 2009 Defining analytics as a strategic asset 2014 The emerging role of the chief data officer The intersection of big data and innovation Power of analytics to transform business outcomes
  5. 5. © 2014 IBM Corporation5 Analytics correlates to performance Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright © Massachusetts Institute of Technology 2010. Top Performers are more likely to use an analytic approach over intuition* Organizations that lead in analytics outperform those who are just beginning to adopt analytics *within business processes 5.4x3x
  6. 6. © 2014 IBM Corporation Top Performers are more sophisticated in handling information 6 Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study (c) Massachusetts Institute of Technology 36% 28% 34% 21% 9% 3% 4% 2% Capture information Aggregate information Analyze information Disseminate information and insights 4x more likely 9x more likely 8.5x more likely 10x more likely Activity rated very well Transformed organizations Aspirational organizations Chart reflects percentage of respondents who rated their organizations’ ability to perform these tasks as “very well”
  7. 7. © 2014 IBM Corporation Transformed organizations master three competencies to drive sustainable competitive advantage 7 Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011.
  8. 8. © 2014 IBM Corporation Manage The Data Managing the Information Landscape Source s Business Initiativeslegacy apps dbs xls, xml, flat warehouse external custom BI Analytics Data Discovery Predictive Business Analysts Executives Enterprise Architects Data Analysts Subject Matter Experts Data Warehouse Manager Developer DBA System Architect Data Steward Optimization UnderstandUnderstand ActActManage
  9. 9. © 2014 IBM Corporation Transformed organizations need resist the urge to perfect the data 9 Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011.
  10. 10. © 2011 IBM Corporation10 Understand The Data Profiling using Information Analyzer Cleanse Master Monitor Monitor the quality of your data in any place (database / in a data flow) and across systems Understand Assess the quality of your data Manage ActActUnderstand
  11. 11. © 2014 IBM Corporation Data and Integration Modeling Common understanding of the design Database development requires a “blueprint” or model of business requirements Data integration designer and developer need that “blueprint” to ensure that requirements (i.e., sources, transformations, and targets) have been clearly communicated in a common, consistent manner Model Type Data Integration Conceptual Model Logical Model Physical Model Implementation Development InfoSphere Data Architect Tools Conceptual Data Model Conceptual Data Integration Model Logical Data Model Database Data Stage Projects The Modeling Paradigm Physical Data Model Logical Data Integration Model Physical Data Integration Model Data Stage Designer Blueprint Director
  12. 12. © 2014 IBM Corporation Act On The Data Trust and traceability enables action 12 Information Integration: ETL, Data Quality, Data Profiling Source Systems, Data Marts, Silos Front Line / BI Applications / Predictive Analytics Data Lineage, Impact Analysis, Operational Monitoring UnderstandUnderstandManageManage Information Governance, Business Definitions Act
  13. 13. © 2014 IBM Corporation – Key Business End Users – Program Manager / Project Lead – Governance Stewart (SME) – Security & Privacy Teams – Operations – Developers – Modelers / Architects – QA / Testing Teams – Data Analyst BI Reports and Dashboards Source Systems Data Warehouse ETL Developer Data Modeler BI Developer Accuracy in Reporting Deliver Information Efficiently Measures and Metrics Complex Data at the Speed of Business Data Analyst Business User Common Understanding 13 Common shared metadata Aligning different actions for efficient delivery
  14. 14. © 2014 IBM Corporation Trust in data – there is still a long way to go Two thirds of the leaders express confidence in data 14 Transformed organizations that has confidence in the quality of data and analytics Source: Analytics: A blueprint for value – Converting big data and analytics into results, IBM Institute for Business Value © 2013 IBM Trust in data
  15. 15. © 2014 IBM Corporation Three characteristics that distinguish Transformed organizations most 15 Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011. Percentage indicates Transformed respondents who rated themselves as highly effective at each key characteristic
  16. 16. © 2014 IBM Corporation Over to Rob 16
  17. 17. © 2014 IBM Corporation Simplify Integration Increase trust and confidence in information Increase compliance to standards Facilitate change management & reuseDesign Operational DevelopersSubject Matter Experts Data Analysts Business Users Architects DBAs Unified Metadata Management What does Information Server help to achieve?
  18. 18. © 2014 IBM Corporation Information Server Metadata Components Metadata Management Analyze / Understand Data Lineage Impact Analysis Object Merge Import/Export Create / Manage Read/Write Metadata Server Information Analyzer Information Services Director Metadata Asset Manager DataStage FastTrackBusiness Glossary & BGA MetaBridges CognosInfoSphere Data Architect Metadata Workbench Third Party Tools
  19. 19. © 2014 IBM Corporation Information Server Common Metadata Repository InfoSphere Data Architect (Data Model) Inormation Analyzer (IA) Source Data Profiling (tool) Cognos Framework Manager (tool) EDW /DM Repository Business Glossary (part of the Information Server Common Metadata Repository) DataStage ETL (tool) Manage and Execute DDL BI Data Linage Meta Data (Reports and FM Packages) Export Target Data Model Export Data Models Validate Discover and adjust source metadata Uses and Creates Fast Track Mappings (tool) Export DDL / XML Deploy and Execute Scripts Use Source and Target meta data To create mappings CVS / ClearCase Reopository Metadata workflow and Tools Overview Overall aim with the Metadata workflow is to: - Ensure that the Cognos reports are linked to Business Definitions, Data Model and the Data Integration design , i.e. to enable design traceability and lookup of definitions - Ensure an improvement of change management analysis, i.e. to perform impact analysis Information Server Data Stage Metadata Repository IA Metadata Repository (Source Table Definitions) Updates Source Model Generate Meta Data to Data Stage Automatic publish of ETL/ Data Lineage Meta Data Cognos Content Store (Metadata Repository) FM Packages Cognos Report Studio (tool) Reports Version Control Version Control Import Source Models Version Control BA DM BI Version Handeling BA DM DBA ETL BI DBA ETL Version Control DBA BI ETL BI ETL ETL ETL ETL BI BI Source Databases (Regular and Migration) Read Terms from Business Gloassary DBA InfoSphere Metadata Asset Manager
  20. 20. © 2014 IBM Corporation InfoSphere Data Architect (Manage & Understand) Data Models – Sources (Regular / Migration) – Targets (EDW / DM) Management – Logical Data Models – Physical Data Models – Attribute Groups – Generate DDL – Reverse Engineer Governance – Business Terminology – Naming Models – Domain Models Integration – InfoSphere Metadata Asset Manger (IMAM) – Business Glossary Challenges – Data Type inconsistencies with Oracle – Reverse Engineering source models – Implemented Data Resources – Date / Timestamp – Integer
  21. 21. © 2014 IBM Corporation InfoSphere Business Glossary (Manage & Understand) Common Terminology Connect business with IT Associate terminology with assets Data Rules – Definitions – Visibility – Understanding Greater visibility increases understanding and trust in the underlying solutions, the data and information they provide Governance – Stewardship – Architects, Analysts, Business Integration – Import from files – IDA – Metadata Workbench – Information Server assets – Cognos – BG Workflow – Business Glossary Anywhere Challenges – Category structure – Business Organisation Governance Business Lineage BG Anywhere Taxonomy Business Terms
  22. 22. © 2014 IBM Corporation InfoSphere Information Analyzer (Understand) Data Profiling tool – Understand the source data – Regular ETL Sources – Migration ETL Sources Integration – Input for the mapping specifications – Define and validate business rules (Data Rules) – Publish Data Rules for use in DataStage Standard Analysis – Column Analysis – Primary Key Analysis – Foreign Key Analysis – Cross-Domain Analysis Overview of results in Data Quality Console Challenges – Consolidate and document findings / conclusions for Mapping generation – Limitations of analysis – Some drill through limitations – SQL Analyze Structure, Content, Quality + Relationships of Data
  23. 23. © 2014 IBM Corporation InfoSphere FastTrack (Manage & Understand) Source to Target Mapping Specifications Metadata available from the IS Metadata Repository Connection between Business and IT Mapping (design) also stored in the IS Metadata Repository Audit Integration – Metadata Repository – Metadata Workbench Challenges – Efficency – MS Excel Flexible Reporting Auto-generates DataStage jobs Specification Flexible Reporting
  24. 24. © 2014 IBM Corporation InfoSphere Metadata Asset Manager (Manage) Managed Metadata Import – Metadata Bridges – InfoSphere Data Architect – Cognos – Staging area for comprehensive impact analysis Metadata Management – Administration of Metadata Repository – Manage • Duplicate and disconnected Metadata • Relationships (LDM / PDM / Implemented Data Resources) Integration – Metadata Repository – IDA – Cognos – Other 3rd Party tools (BO, ERwin) Challenges – LDM / PDM relationships – Remove models for certain changes – Metadata Interchange Server (Client or Server)
  25. 25. © 2014 IBM Corporation InfoSphere DataStage (Manage) DataStage consists of three different components – Administrator – Designer – Director Develop and Run ETL Environment Variables Integration – Published Data Rules from IA – Table Definitions – Metadata from Metadata Repository originally defined in IDA and imported via IMAM – Operations Console – Data Quality Console Challenges – Application of development standards and guidelines to ensure End To End Data Lineage – Use of the correct metadata from Metadata Repository – Metadata management issues • Date / Time • Integer Hundreds of Built-in Transformation Functions Visually Designed Logic Transform, Aggregate Data in Batch or Real Time
  26. 26. © 2014 IBM Corporation InfoSphere Metadata Workbench (Manage, Understand & Act) Manage and Understand – Implemented Data Resources – DataStage Jobs – FastTrack Mappings – Cognos Data Models and Reports – Extended Data Sources / Extended Mappings – Lineage Services Who – Metadata Administrators – Architects, Analysts Custom Queries – Adherence to standards – Validation of Data Lineage Information governance – End to End traceability of solutions – Data Model Implementation – Cognos BI – Understand complex environments – Visibility and understanding – Data Rules Data Lineage – Impact Analysis – Faster time to market Challenges – Data Lineage (some performance tuning) – Browser! (Firefox, Chrome, IE) Design + Operational + Extended lineage
  27. 27. © 2014 IBM Corporation InfoSphere Operations Console (Understand & Act) Operations Console – Job runtime activity – Logs – System Resources (CPU, Memory) – Identify jobs that have Failed or Finished with Warnings – Automated integration with DataStage – Execute jobs / sequences – Analyse trends Operations Database – ETL Audit Information – available to Jobs Challenges – SLA / OLA measurement Information Server Administrator Information project team (developers. analysts, administrators, architects, etc.)
  28. 28. © 2014 IBM Corporation Summary Information Server can provide a single repository for your BI solution Design and implementation enables End to End Lineage and Traceability Trust and confidence in data and information Organisation and Governance – BICC – Data Quality Forums – Architecture Forums Impact Analysis – new and existing solutions – Faster time to market Teams using the same tools with the same information, talking the same language – Architects / Analysts / Application Management / Business – Consistent communication between business and IT Run time analysis – Operations console – Identify and resolve issues in operations 28 IBM Confidential
  29. 29. © 2014 IBM Corporation End to End Traceability enables... Trust and Understanding in solutions Provides confidence to decision makers, enabling the business to act! Or just wing it… 29 IBM Confidential
  30. 30. © 2014 IBM Corporation30
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