IBM InfoSphere MDM v11 Overview - Aomar BARIZ

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  • Finally, I wanted to end our discussion on what is master data and master data management by summarizing a few key trends that may influence your thinking and has influenced IBM’s product direction. 1 – MDM requires information governance to be successful. 2 – Organizations are linking process and data strategies with BPM and MDM. 3 – Implementations are maturing from single domain to multi-domain.
  • Masters all domains in a single solution: IBM is unifying best-of-breed technologies that were built to address specific needs of different domains or different technical approaches to MDM. IBM will make this combined technology available to our customers as a single solution to address all their MDM needs across the whole enterprise. Govern Inside & Out: IBM is building in governance capabilities within the MDM technology that are unique to master data, but IBM is also integrating our MDM to work seamlessly with related governance technologies in IBM’s overall InfoSphere governance solution. Designed for Big Data: IBM’s MDM has always been the market leader when dealing with volume and scale. While we continue to push the boundary on volume & scalability, we are also building our MDM to handle the increasing VARIETY of information that is a hallmark of the Big Data trend. Accelerate Time-to-value: As MDM becomes a ‘mainstream’ technology, we continue to look for ways to simplify our software, reducing the time and cost necessary for clients to implement MDM and start getting value from MDM. This comes not just through simplifying the core MDM software itself, but also through providing pre-configured MDM solutions that target specific business problems or are designed for specific applications. (Advanced Catalog Management for Commerce is a great example). Embrace New Era of Computing: New computing platforms are becoming more and more important, both emerging platforms such as ‘converged systems’ (like IBM’s Pure Application systems) as well as already-emerged platforms of mobile computing. IBM MDM is designed to take advantage of these new computing platforms in ways that are valuable for our clients. Rich MDM Ecosystem: Lastly, we realize that the success of our MDM business is not just a function of the software itself, but a function of having a rich and healthy ecosystem of domain experts, business partners, implementation specialists, and thought leaders both inside IBM and outside IBM.
  • Masters all domains in a single solution: IBM is unifying best-of-breed technologies that were built to address specific needs of different domains or different technical approaches to MDM. IBM will make this combined technology available to our customers as a single solution to address all their MDM needs across the whole enterprise. Govern Inside & Out: IBM is building in governance capabilities within the MDM technology that are unique to master data, but IBM is also integrating our MDM to work seamlessly with related governance technologies in IBM’s overall InfoSphere governance solution. Designed for Big Data: IBM’s MDM has always been the market leader when dealing with volume and scale. While we continue to push the boundary on volume & scalability, we are also building our MDM to handle the increasing VARIETY of information that is a hallmark of the Big Data trend. Accelerate Time-to-value: As MDM becomes a ‘mainstream’ technology, we continue to look for ways to simplify our software, reducing the time and cost necessary for clients to implement MDM and start getting value from MDM. This comes not just through simplifying the core MDM software itself, but also through providing pre-configured MDM solutions that target specific business problems or are designed for specific applications. (Advanced Catalog Management for Commerce is a great example). Embrace New Era of Computing: New computing platforms are becoming more and more important, both emerging platforms such as ‘converged systems’ (like IBM’s Pure Application systems) as well as already-emerged platforms of mobile computing. IBM MDM is designed to take advantage of these new computing platforms in ways that are valuable for our clients. Rich MDM Ecosystem: Lastly, we realize that the success of our MDM business is not just a function of the software itself, but a function of having a rich and healthy ecosystem of domain experts, business partners, implementation specialists, and thought leaders both inside IBM and outside IBM.
  • PURPOSE: Identify how this offering will be validated with customer and business partner needs SOURCE: Marketing/Release Lead/Green Thread Lead/ Product Owner (Agile)/Business Development (for Business Partners) CHANGE HISTORY: Originally introduced in June 2008 as a “pilot”. Pilot designation removed in Version 5.4 (July 2009) Dec 09: Added specific reference to Business Partners Provide a list of the customers and/or business partners the Offering Team/Green Thread Team is working with, or plans to work with to ensure that this offering meets their needs. Also describe how the offering team plans to solicit input from the customer/business partner, the customer checkpoints, and the plan for incorporating customer feedback into the offering release processes. The project team documents its plans for Early Programs via the SWG Quality Plan template, Customer Early Program Feedback Summary Tab.
  • Probabilistic Search – re-use the sophisticated matching capabilities for searching as well Application Toolkit - create sophisticated master data UIs or embed MDM capabilities in end user UIs, including BPM RDM - Provides the governance, process, security and audit control for managing reference data as an enterprise standard, resulting in fewer errors, reduced business risk and cost savings Building on the unified packaging introduced with IBM InfoSphere Master Data Management V10.0, V10.1 contains significant enhancements that include: Master Data Governance Master Data Policy Administration – Define and create master data policies to ensure trusted data quality for consumers of master data Master Data Policy Monitoring – Provides reports and dashboards to track the uniqueness and completeness of the golden record and measures the consistency between the data sources and the golden record Master Data Policy Enforcement – Ensures noncompliant data is remediated, critical data changes are reviewed and approved, and master data is appropriately matched, linked, and collapsed Business Process Management (BPM) integration capabilities and sample workflows – Straightforward mechanisms to create processes (workflows) that govern data steward-oriented and other tasks. Master Data Management Enhanced probabilistic matching and searching – Probabilistic capabilities are expanded to include probabilistic search for the InfoSphere MDM Server technology and use of the latest probabilistic matching engine. Advanced Rules Management – Enables business users to leverage a single interface for product creation, rules authoring, and rules association through an integrated solution with WebSphere ODM. Helps drive product personalization, advanced bundling and configuration, complex offers, and more. Advanced Catalog Management - An accelerated solution with an out of the box data model, business process workflows, and integration components tailored for WebSphere Commerce. Includes advanced capabilities for managing eCommerce catalogs supported by WebSphere Commerce Additional support for delimited file formats for Adaptive Services Interface – After introducing of the Adaptive Services Interface in v10.0 its support for XML message formats has been augmented with support for delimited file and messaging formats, thereby further expanding the number of integration points that can be supported and removing the need to “code” the required interfaces. Enhancements to the InfoSphere Master Data Management Application Toolkit – With additional widgets, the Application Toolkit can be used to create sophisticated master data UIs or to embed MDM capabilities in end user UIs, e.g. in CRM or Call Center applications.
  • Service patterns are defined in the core bundles. These patterns include definitions for business objects, lookup tables, business proxies, etc. These same patterns are then employed by customers who extend the core features of MDM with their own customizations Central framework is agnostic regarding the where a service provisioned. There is a pattern of look-ups that is employed to get the correct bundle for any given service Use of OSGi to allow for a deployment of InfoSphere MDM that is more modular/granular Separation of core InfoSphere MDM code (the IBM code) and the extensions (the customer’s code) as components (or “bundles”) Ability for customers to create multiple bundles such that separate development teams can work more independently Patching can occur more localized; IBM patches against the core code bundle; the customer’s patches against the extension bundle(s) 2 scenarios: Customer would have to take ibm EAR out of box into workbench, then take own code and redeploy everything – net new EAR for every upgrade and all patches Every customer said this is painful Organize development teams better and segregate extensions/customizations – can have different bundles, separate code over bundles Examples – cardinal health – have multiple teams, by domain, customer data use cases; product data use cases – can now more easily work independently where appropriate, when working cross domain still work together – (data model changes go cross – really only one data model) – Use of OSGi to allow for a deployment of InfoSphere MDM that is more modular/granular Separation of core InfoSphere MDM code (the IBM code) and the extensions (the customer’s code) as components (or “bundles”) Ability for customers to create multiple bundles such that separate development teams can work more independently Patching can occur more localized; IBM patches against the core code bundle; the customer’s patches against the extension bundle(s) Customer would have to take ibm EAR out of box into workbench, then take own code and redeploy everything – net new EAR for every upgrade and all patches Every customer said this is painful Organize development teams better and segregate extensions/customizations – can have different bundles, separate code over bundles Examples – cardinal health – have multiple teams, by domain, customer data use cases; product data use cases – can now more easily work independently where appropriate, when working cross domain still work together – (data model changes go cross – really only one data model) –
  • Examples of Hybrid scenarios Prospect/customer use case Source/consuming systems Mainframe can only contribute info, can’t consume updates – technology is too expensive to create that integration back – not worth it CRM – can consume M&A - I just bought a company that has X systems, bring their info into virtual side for comparison, but can’t persist yet because you may not own data yet or post acquisition but systems aren’t ready to consume Cigna – customer service – moving from account/policy centric to customer perspective - feed customer service portal Dell – started with identifying individuals cause they didn’t know who they were, duplication, important when I interact to know where they are: identification of individual = first step in journey; over time, want much richer customer profiles, adding info such as privacy preferences (can we call you, email), demographic view to broader view – account management view – know if you are assigned to that account - – getting to full set of attributes is not easy – needs people to agree, get through IT structure Allstate – Wells Fargo – Matching tech is why IBM bought initiate - New customer – start quick (identify specific use case, get people to agree, approach different LOBs to say you still own data but I’ll take your data and give other areas the best view of the data), as LOBs become comfortable with data overtime, I can now grow over time – low risk – journey – flexibility to do either/both when appropriate – can make journey if needed – - Go with IBM because you aren’t locked into certain architecture – make it easy for you to change your IT based on your business requirements vs. other way around Hybrid prospect/customer – thin/think; some systems can consume, some can only provide – Mainframe can only contribute info, can’t consume updates – technology is too expensive to create that integration back – not worth it CRM – can consume M&A - I just bought a company that has X systems, bring their info into virtual side for comparison, but can’t persist yet because you may not own data yet or post acquisition but systems aren’t ready to consume How we are different from INFA – we have done it more; experience, reference V11 Harmonized Terminology Engine Co-Residence MDM Server and Initiate MDS engines within same WAS deployment Simplified deployment and management (based on OSGi) Unified MDS/MDMS Workbench for configuration and customization Unified MDS/MDMS installer Integration with IBM Support Assistant Data Collector for both MDM SE/AE Modularity - Use of OSGi to allow for a deployment of InfoSphere MDM that is more modular/granular Separation of core InfoSphere MDM code (the IBM code) and the extensions (the customer’s code) as components (or “bundles”) Ability for customers to create multiple bundles such that separate development teams can work more independently Patching can occur more localized; IBM patches against the core code bundle; the customer’s patches against the extension bundle(s) Enforce versioning of third party code components
  • Examples of Hybrid scenarios Prospect/customer use case Source/consuming systems Mainframe can only contribute info, can’t consume updates – technology is too expensive to create that integration back – not worth it CRM – can consume M&A - I just bought a company that has X systems, bring their info into virtual side for comparison, but can’t persist yet because you may not own data yet or post acquisition but systems aren’t ready to consume Cigna – customer service – moving from account/policy centric to customer perspective - feed customer service portal Dell – started with identifying individuals cause they didn’t know who they were, duplication, important when I interact to know where they are: identification of individual = first step in journey; over time, want much richer customer profiles, adding info such as privacy preferences (can we call you, email), demographic view to broader view – account management view – know if you are assigned to that account - – getting to full set of attributes is not easy – needs people to agree, get through IT structure Allstate – Wells Fargo – Matching tech is why IBM bought initiate - New customer – start quick (identify specific use case, get people to agree, approach different LOBs to say you still own data but I’ll take your data and give other areas the best view of the data), as LOBs become comfortable with data overtime, I can now grow over time – low risk – journey – flexibility to do either/both when appropriate – can make journey if needed – - Go with IBM because you aren’t locked into certain architecture – make it easy for you to change your IT based on your business requirements vs. other way around Hybrid prospect/customer – thin/think; some systems can consume, some can only provide – Mainframe can only contribute info, can’t consume updates – technology is too expensive to create that integration back – not worth it CRM – can consume M&A - I just bought a company that has X systems, bring their info into virtual side for comparison, but can’t persist yet because you may not own data yet or post acquisition but systems aren’t ready to consume How we are different from INFA – we have done it more; experience, reference V11 Harmonized Terminology Engine Co-Residence MDM Server and Initiate MDS engines within same WAS deployment Simplified deployment and management (based on OSGi) Unified MDS/MDMS Workbench for configuration and customization Unified MDS/MDMS installer Integration with IBM Support Assistant Data Collector for both MDM SE/AE Modularity - Use of OSGi to allow for a deployment of InfoSphere MDM that is more modular/granular Separation of core InfoSphere MDM code (the IBM code) and the extensions (the customer’s code) as components (or “bundles”) Ability for customers to create multiple bundles such that separate development teams can work more independently Patching can occur more localized; IBM patches against the core code bundle; the customer’s patches against the extension bundle(s) Enforce versioning of third party code components
  • Level 1 – social media profile in MDM (today ’ s capability) – SM contact points, preference profile, …. What else? Level 2 – integration with Big Data to aggregate SM into MDM facts – intent to purchase, sentiment towards X, ….. V11 – the landing point for new insights is MDM, so they can operationalize the insights from Big Data
  • Our product management, engineering, marketing, CTPs, etc, etc teams have all been working together to help to better understand the big data market. We ’ve done surveys, met with analysts and studied their findings, we’ve met in person with customers and prospects (over 300 meetings) and are confident that we found market “sweet spots” for big data. These 5 use cases are our sweet spots. These will resonate with the majority of prospects that you meet with. In the coming slides we’ll cover each of these in detail, we’ll walk through the need, the value and a customer example.
  • Turn MDM Repository into an out of the box Text Analysis tool Automatically discover linkages between text and relevant MDM entities. Enhance detection of relationships between entities Enhance entity resolution from the evidence hidden within the documents. Enrich knowledge base by adding additional information to MDM records Data model agnostic – can be for any domain – ENTERPRISE EDITION ONLY Traditional internal data sources – integrate into consolidated view to downstream systems Potential information about customers lost out in unstructured, xls, reports, email, social blogs – might be in ECM, used to be unavailable to MDM With EUTC, able to take info about customers and use it to exploit Go to one location to see information from traditional and non traditional sources related to this person See connections – Text analysis tool – what emails, what information in unstructured is linked to customers, degree of certainty that it is linked to this entity, relationship link to sources Now I know more about this customer, conversations - tech support – know customer, name, (demographics), know email conversations – know experience, so the next tech support person is more prepared for interaction If negative, can say, I understand you had problems last time you reached out, is that what you are calling today or did it get resolved If positive, can say, did this fix work Public safety – structured data across multiple sources across the world, no connection around address so not able to say there is a link, If have 2 names, 2 addresses in email, typical text analytics will not find links between attributes, combine MDM as part of entity resolution – create an entity from attributes Analysts – given links made by EUTC, enter lead info, I want to know everything about jennifer reed from all my sources, results come up, query, click on entities, see relationships/connection between structured and unstructured – INVESTIGATIVE TOOL Link but don’t automatically resolve – don’t want to update master record from unstructured sources, but want to have link. Unstructured is not as trusted so shouldn’t update master record. User could update master record based on info found in unstructured doc PMe offers attribute level scoring for us to be able to get granularity on how close information in document relates to information in hub - if rare, more sure – if commonly occurs – then not likely a link -- need granularity of proprability to know likely that this is a link – because unstructured is less trusted Identity Insight only does similarity score but can’t say it is a common address or common name (high occurrence/appears a lot in repository) – doesn’t know probability that it occurs –
  • Public safety – structured data across multiple sources across the world, no connection around address so not able to say there is a link, If have 2 names, 2 addresses in email, typical text analytics will not find links between attributes, combine MDM as part of entity resolution – create an entity from attributes Analysts – given links made by EUTC, enter lead info, I want to know everything about jennifer reed from all my sources, results come up, query, click on entities, see relationships/connection between structured and unstructured – INVESTIGATIVE TOOL Link but don’t automatically resolve – don’t want to update master record from unstructured sources, but want to have link. Unstructured is not as trusted so shouldn’t update master record. User could update master record based on info found in unstructured doc
  • Augment traditional product information with dynamically derived product traits based on web and social media feedback Can use this additional information to update marketing, offers, address technical issues, change product specs, change packaging etc. This is an example where the master record could be updated/enhanced with insight from unstrcutured text.
  • IBM combines proven MDM technologies with new innovations from IBM Research to enable healthcare organizations to find and perform analytics on groups of patients who are similar in terms of their clinical information. Key Functions HL7 integration with Healthcare specific Natural Language Processing Text analytics based on healthcare vocabularies, including SNOMED, LOINC, RxNorm Health record de-identification Patient similarity service against a longitudinal patient record Clinical trials cohort selection application UI Key Benefits Ease of use for researchers Quick time to value Better and broader results from the unique advanced analytics approach Built on gold-standard MDM/EMPI technology
  • IBM IOD 2012 07/15/13 Drury Design Dynamics
  • Translation – different language UIs to support country implementations (big in europe) Easier install – had to install 2 things prior, now just install 1 thing Security enhancements, attribute level security – greater control over data ownership Global search – search for reference data across sets – want to find a ISO code, search for that name using global search; or if looking for country code = US – find all sets where code is present Slide 18 -= screen shot Manage changes Advanced hierarchies Integration with IIS
  • IBM InfoSphere MDM v11 Overview - Aomar BARIZ

    1. 1. © 2013 IBM Corporation Information Management 1 What’s New in IBM InfoSphere Master Data Management v11
    2. 2. © 2013 IBM Corporation Information Management Please Note: 2
    3. 3. © 2013 IBM Corporation Information Management 33 Remember, We Rock. MDM for Customer Data MDM for Product Data Gartner estimates that IBM is the market share leader, followed by Oracle, Informatica, SAP and Tibco #2 11.2% #1 40.3% IBM #1 20.1%
    4. 4. © 2013 IBM Corporation Information Management 4 MDM Market Trends – Analyst Perspective Implementations are maturing from single domain to multi-domain MDM cited as the #1 information related project that requires Information Governance to be successful …visionary BPM and MDM teams turn to process data management, which acknowledges the inherent connection between business process improvement and data quality. Some vendors may claim to be able to model and support a variety of data domains in a single technology product, but they often lack aspects of functionality, such as collaborative workflow, and experience in dealing with the needs of the different functional groups and business processes that leverage particular master data domains. Organizations are linking process and data strategies with BPM and MDM MDM requires Information Governance to be successful MDM and Big Data strategies should be intertwined To create competitive advantage, organizations will need to leverage sources of big data, especially social networks, in combination with their MDM strategy.
    5. 5. © 2013 IBM Corporation Information Management 5 Opportunities in an Information Supply Chain Reduce the Cost of Data 1. Replace Oracle Database 2. Enhance the Value of Your Data Management System 3. Archive Data to Reduce Cost 4. Increase Efficiency of Application Development & Testing 5. Data Warehouse Augmentation Trust and Protect Information 1. Trusted Information for Big Data and Data Warehousing 2. Act on a Trusted View 3. Consolidate and Retire Applications 4. Protect & Secure Enterprise Data to Ensure Compliance New Insights From Big Data 1. Rapid Warehouse Deployment for Deep Analytics 2. Real-Time Warehouse for Operational Analytics 3. Exploit New Data Sources
    6. 6. © 2013 IBM Corporation Information Management InfoSphere MDM Strategy Single Solution Designed for Big Data Accelerate Time-to- Value Govern Inside & Out Embrace New Era of Computing
    7. 7. © 2013 IBM Corporation Information Management InfoSphere MDM Strategy Designed for Big Data • Scale into the billions of records • Combine structured master data with insights from unstructured data • Integrate with IBM’s capabilities for exploring and visualizing big data Accelerate Time-to-Value • Simplify implementation process • Pre-built accelerators • Easily adjust MDM implementation ‘style’ • Built into broader IBM solution offerings New Era of Computing • MDM ‘patterns’ for IBM Pure Application System • Expose master data easily to mobile platforms • Exploit mobile-device generated data as part of master data (e.g. geolocation) Govern Inside & Out • Built-in governance capabilities unique to MDM • Integrated to IBM InfoSphere • Support both ‘passive’ and ‘active’ governance of master data • Support OOTB governance policies + client-unique policies
    8. 8. © 2013 IBM Corporation Information Management 8 Transforming InfoSphere MDM into a unified MDM solution 2010 Initiate MDS MDM Server MDMS for PIM • Separate products targeted to different MDM use cases • Best of breed acquisitions 2011-2012 • Single MDM offering • Common matching engine • Advanced Catalog Management for attachment to WebSphere Commerce 2013 Operational Server Virtual & Physical Modules V9 V10 V11 InfoSphere MDM InfoSphere MDM Initiate MDS MDM Server Collaboration Server Collaboration Server • Unified virtual and physical technology into single server capable of supporting multiple MDM use cases • Hybrid MDM • Modularity
    9. 9. © 2013 IBM Corporation Information Management 9 v11 further differentiates IBM from the competition by supporting complex initiatives and utilizing big data Business requirements for MDM clients necessitate hybrid implementation styles  Customers can adjust MDM architectural style as business matures with MDM, and will migrate from simpler use cases to more advanced (hybrid) ones Clients want to master new types of data  New use scenarios around customer engagement with product and location information are driving need to incorporate unstructured and other non-traditional data MDM is often part of a larger initiative  MDM may be positioned as a foundational component for a business solution or larger information governance project Standard Edition and Advanced Edition now on the same technical platform  Support for “hybrid” use cases (crossing MDM architectural styles) – Key competitive advantage  Straightforward up-sell path/opportunity (easier for sellers and buyers) Extension for unstructured text correlation and expanded patient hub data model to include clinical attributes  Ties into Big Data Messaging Cross IM and SWG Integration • Support attachment to Information Server projects • Support attachment to WebSphere Commerce projects
    10. 10. © 2013 IBM Corporation Information Management 10 InfoSphere MDM V11 New Features & Functionality  Virtual, physical and hybrid MDM styles in a single instance  Modular implementations and upgrades  Collaborative authoring UI enhancements  Data quality via integration with InfoSphere Information Server  Enhanced hierarchy support for reference data  Dashboard for collaborative authoring workflow  Task KPIs to monitor master data quality  Augment master data with unstructured text  Expanded patient hub to include clinical attributes AccelerateAccelerate Time to ValueTime to Value AccelerateAccelerate Time to ValueTime to Value Designed forDesigned for Big DataBig Data Designed forDesigned for Big DataBig Data GovernanceGovernance Inside & OutInside & Out GovernanceGovernance Inside & OutInside & Out
    11. 11. © 2013 IBM Corporation Information Management 11 Accelerate Time to Value
    12. 12. © 2013 IBM Corporation Information Management Unification of MDM Virtual & Physical Multi-style, multi-domain MDM in a single operational hub – Single database instance and schema – Engine co-residence (WAS container) – Simplified deployment and management (based on OSGi) – Unified MDS/MDMS workbench for configuration and customization – Unified MDS/MDMS installer – Integration with IBM Support Assistant Data Collector 12
    13. 13. © 2013 IBM Corporation Information Management 13 InfoSphere MDM v11 - Modularity “We are planning to upgrade to 10.1. The part I don't like is the recreation of all customizations in each new release.” - Master Data Management Architect, Caterpillar “We are planning to upgrade to 10.1. The part I don't like is the recreation of all customizations in each new release.” - Master Data Management Architect, Caterpillar MDM v11 Custom Extension v2 MDM vNext Custom Extension v2 Modularity in MDM v11 • OSGi modular framework • Separation of core InfoSphere MDM code from custom extensions • Localized patching Simplified upgrades through OSGi
    14. 14. © 2013 IBM Corporation Information Management A Visual Indication of Simplicity 14 Before v11 V11 & Beyond
    15. 15. © 2013 IBM Corporation Information Management 15 Business Use Cases Benefit from Hybrid MDM Prospect Hub Customer Hub Thin amount of prospect attributes – Registry Approach Thin amount of prospect attributes – Registry Approach Persist large number of customer attributes Centralized Approach Persist large number of customer attributes Centralized Approach InfoSphere MDM Maintain and move prospect and customer information seamlessly in a single solution; persist information Hybrid Approach Maintain and move prospect and customer information seamlessly in a single solution; persist information Hybrid Approach
    16. 16. © 2013 IBM Corporation Information Management 16 Business Use Cases Benefit from Hybrid MDM Immediately Post Acquisition Business Processes Integrated Thin amount of prospect attributes – Registry Approach Thin amount of prospect attributes – Registry Approach Persist large number of customer attributes Centralized Approach Persist large number of customer attributes Centralized Approach InfoSphere MDM Maintain and move prospect and customer information seamlessly in a single solution; persist information Hybrid Approach Maintain and move prospect and customer information seamlessly in a single solution; persist information Hybrid Approach
    17. 17. © 2013 IBM Corporation Information Management What’s New in v11.0 Collaborative Edition Governance Dashboard Home page Customizable Labels and Icons Single-edit Customization Multi-edit Enhancements Related Items Tab Shared Search Templates ACM for WebSphere Commerce Phase 2 Information Server for Data Quality Supporting Stack Updates
    18. 18. © 2013 IBM Corporation Information Management Collaborative Edition – Current Home Page
    19. 19. © 2013 IBM Corporation Information Management New Governance Dashboard All numbers are links to view the specific category of entries. Ex. 6 “Urgent” entries in DBWorkflow1 Summary pane with graphical view of assigned entries Workflow summary with priorities and categories of assigned entries: Current – blue Urgent – yellow Critical - red
    20. 20. © 2013 IBM Corporation Information Management 20 Designed for Big Data
    21. 21. © 2013 IBM Corporation Information Management MDM and Big Data Must Work Together Master Data Management Core Big Data Technologies MDM creates context for big data. MDM system provides trusted information and operationalizes insights from big data Big data creates context for MDM. Big data provides new insights from social media and other sources for customer profile
    22. 22. © 2013 IBM Corporation Information Management 22 Big Data Exploration Find, visualize, understand all big data to improve decision making Enhanced 360o View of the Customer Extend existing customer views (MDM, CRM, etc) by incorporating additional internal and external information sources Operations Analysis Analyze a variety of machine data for improved business results Data Warehouse Augmentation Integrate big data and data warehouse capabilities to increase operational efficiency Security/Intelligence Extension Lower risk, detect fraud and monitor cyber security in real-time The 5 Key Use Cases
    23. 23. © 2013 IBM Corporation Information Management 23 InfoSphere MDM – Correlating Unstructured Data CRM ERP Orders Structured Data Unstructured Data  Name  Address  Phone number  Purchase history  Customer sentiment  Contact history  Issue resolution status InfoSphere MDM • Discover linkages between text and relevant master data entities • Link to additional information • Investigative tool for text analysis • Complete, accurate and timely views Benefits • Enhanced customer service • Quicker, more accurate issue resolution • Increased upsell/cross opportunity
    24. 24. © 2013 IBM Corporation Information Management InfoSphere MDM for Patient – Advanced Edition • Expanded model and services for data collection, storage and access to a longitudinal patient record • Patient Demographics, Contact Info, IDs • Immunizations, Allergies, Vital Stats • Visit Info, Exam Data, Procedures • Medications. Measurements, Outcomes • Family History, Studies • Diagnosis, Symptoms, Treatments • Uses WebSphere Message Broker Healthcare connectivity pack for real time HL7 data collection into MDM • Anonymized and secure storage of clinical data for patient data security compliance InfoSphere MDM for Patient –Advanced Edition EMRs Lab/ Radiology Systems Pharmacy HIE Data Warehouse Case Management Patient Population Selection
    25. 25. © 2013 IBM Corporation Information Management 28 Governance Inside & Out
    26. 26. © 2013 IBM Corporation Information Management  Business Processes require trusted data  Trusted data requires data governance  IBM providing capabilities to facilitate construction and adoption of these applications – MDM Application Toolkit (MDAT) - Improved – Master Data Policy Monitoring (MDPM) – Improved – Master Data Policy Remediation (MDPR) - Improved – Master Data Governance Dashboard (MDG) - New Master Data Governance in MDM 11 Enforce Monitor Identify Remediate policy rules through Master Data Policy Remediation the effectiveness of your rules through Master Data Policy Monitoring quality issues through Master Data Policy Monitoring and the MDG console data quality issues through Master Data Policy Remediation and the MDG console Monitor Identify Remediate Enforce Data Quality
    27. 27. © 2013 IBM Corporation Information Management MDM & BPM Widgets
    28. 28. © 2013 IBM Corporation Information Management Integration with Information Server – enhanced and new in v11 InfoSphere MDM Individual Product Account Organization Reference Reference Data Management InfoSphere QualityStage InfoSphere Information Analyzer InfoSphere Metadata Workbench InfoSphere Data Click InfoSphere Business Glossary Information Server Definitions for reference data sets Export wizard for data lineage IA sample for MDM Address standardization Defined pattern
    29. 29. © 2013 IBM Corporation Information Management 32 MDM and Information Server Bundling Versions of MDM Release Date IIS bundling Restrictions MDM v11.0 ** (All Editions) June 2013 (expected) Yes, you can position this in a Q2 deal after 6/4 announcement Information Server for Data Quality Edition 9.1 (Information Analyzer, IA Workbench, InfoSphere Discovery, QualityStage, Blueprint Director, Metadata Workbench, and Information Services Director) Can only be used to support MDM program as defined in the license Included*: • 480 PVUs • 2 Authorized Users • 5 unique data sources for InfoSphere Discovery * More entitlements can be purchased separately
    30. 30. © 2013 IBM Corporation Information Management Integration Flow – MDM & Data Quality 33 Sources Applications Databases xls, xml, Flat Files Data Warehouses z Systems CRM Data Warehouses eBusiness ERP Consuming Applications Data Validation Standardize & Cleanse Match & Link Monitor & evaluate IBM Infosphere Information Analyzer IBM Infosphere Information Analyzer IBM Infosphere Quality StageIBM Infosphere Quality Stage IBM Infosphere Master Data Management IBM Infosphere Master Data Management Discover and Cross source analysis IBM Infosphere DiscoveryIBM Infosphere Discovery
    31. 31. © 2013 IBM Corporation Information Management © 2013 IBM Corporation35 RDM Capability: Advanced Hierarchies  Make hierarchies first class entities including lifecycle and versioning  Visualize level based hierarchies  Complex hierarchies – Mixed level based and tree based  Export of advanced hierarchies
    32. 32. © 2013 IBM Corporation Information Management 36 Summary & Resources
    33. 33. © 2013 IBM Corporation Information Management The MDM Optimization Program bridges the gap between setting an MDM vision and identifying the technologies best suited to drive successful implementations and continuous results IBM Master Data Management Optimization Program Program Overview  A no cost, business assessment of you current MDM strategy by IBM Product Managers  An efficient quality assurance program for MDM solutions  Gap analysis of resource and skill sets and ways to address  Recommendations and best practices based on current and future environment  Approach to achieve continuous validation of business case and value proposition  Strategic roadmap and solution architecture Contact Larry Dubov ldubov@us.ibm.com or Henk Alblas halblas@ca.ibm.com for more information
    34. 34. © 2013 IBM Corporation Information Management 3838 Why IBM InfoSphere Master Data Management? Complete  All domains, styles, use cases, industries  Master data governance  Pre-built, extensible and customizable data models and services Flexible  Virtual, physical and hybrid styles in a single solution  Collaborative workflow  Reference data management  Entity resolution Proven  #1 market share  800 + customers  Lowest risk, Quickest time to value  Global reach  Scalability, performance Accessible  Designed for big data  Cloud and mobile options  Integration across InfoSphere solutions  Optimized for real time InfoSphere Master Data Management Improves operational and analytical systems
    35. 35. © 2013 IBM Corporation Information Management Cross Sell and Up Sell Campaigns © 201 39 Sell more MDM (records, domains, editions) to existing MDM customers Sell MDM capabilities to existing IM customers Sell MDM capabilities to existing SWG customers Creating a Customer Hub for Enterprise Marketing (Unica) •Created target customer list in Banking, Retail, Telco - 45 customers in NA •Collateral to execute is ready - VITO letter, internal cheat sheet, flyer, deck Next steps.: •FLMs/Sellers send identified customers the VITO letter by COB 5/10 •Follow up with a call in week of 5/13 •Maintain cadence of phone calls to prospect with the target of setting up meeting with the prospect by the end of this month. RDM for Information Server will be rolled out next Creating a Customer Hub for Enterprise Marketing (Unica) •Created target customer list in Banking, Retail, Telco - 45 customers in NA •Collateral to execute is ready - VITO letter, internal cheat sheet, flyer, deck Next steps.: •FLMs/Sellers send identified customers the VITO letter by COB 5/10 •Follow up with a call in week of 5/13 •Maintain cadence of phone calls to prospect with the target of setting up meeting with the prospect by the end of this month. RDM for Information Server will be rolled out next
    36. 36. © 2013 IBM Corporation Information Management Execution Details  Designated IM FLMs will drive teams – Leverage existing ~3000 DataStage customers and ~1000 PDA customers as market – Focus on last 3 years and IBM core accounts – Narrow to accounts with net new MDM opportunity and high potential for being a reference  IM Reps to execute multi-touch campaign designed to land prospect F2F meetings - Content is developed and ready to go - MDM SWAT team will support F2F meetings and technical sales as necessary - Goal that IM Reps drive sales cycle - MDM SWAT will help set the stage for the future MDM enterprise up-sell  Monthly contest with prizes to teams producing the most leads and ultimately the most revenue 40 This is our best shot to drive short-term 2013 MDM revenue without requiring specialized MDM or heavy Tech Sales skills
    37. 37. © 2013 IBM Corporation Information Management 41 InfoSphere Master Data Management - Resources  Trusted View Resources – Act on a Trusted View Sales Play – Informatica Competitive Portal  InfoSphere MDM Resources – MDM Sales Kit – InfoSphere MDM Reference Data Management Hub (GA Q3 2012) – MDM CTP Sales Kit (Technical) – MDM Client References – MDM Blitz Kits & Prospecting Letters – Reference Data Management - Community – Advanced Catalog Management - Community – MDM Pricing Information – MDM Resources by Industry  Technical Documentation – Pre-GA internal server: http://vanguard.svl.ibm.com:9103/help/index.jsp – Post-GA: http://pic.dhe.ibm.com/infocenter/mdm/v11r0/index.jsp – 10.1: http://pic.dhe.ibm.com/infocenter/mdm/v10r1/index.jsp Bookmark These Links!
    38. 38. © 2013 IBM Corporation Information Management Additional Sessions Title Presenter Date V11 Standard Edition & Advanced Edition Henk Alblas Eric Trenk Tuesday, May 14th v11 Collaborative Edition Harsha Kapre Wednesday, May 15th Reference Data Management Erik O'Neill Thursday, May 16th Unified Engine Considerations Henk Alblas Eric Trenk Priya Krishnan Friday, May 17th MDM and Information Server Priya Krishnan Rakesh Shah Monday, May 20th Data Governance with BPM Trey Anderson Larry Dubov Tuesday, May 21th Extension for Unstructured Text Correlation (EUTC( Jennifer Reed Wednesday, May 22nd Healthcare v11 Enhancements Deanna Nole Dean Burton Joaquim Neto Thursday, May 23rd Master Data Policy Monitoring Enhancements Larry Dubov Priya Krishnan Friday, May 24th 42 Source: If applicable, describe source origin All times 10 am EST
    39. 39. © 2013 IBM Corporation Information Management 43 Thank You

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