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Lançamento ERwin 08/02


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Lançamento ERwin 08/02

  1. 1. CA ERwinData ModelingVisualize the Power of Your DataOn Premise or in the CloudDonna BurbankVP, Product Marketing
  2. 2. Who am I?— More than more than 15 years of experience in the areas of data management, metadata management, and enterprise architecture. − Currently VP of Product Marketing for CA’s data modeling solutions. − Brand Strategy and Product Management roles at Computer Associates and Embarcadero Technologies − Senior consultant for PLATINUM technology’s information management consulting division in both the U.S. and Europe. − Worked with dozens of Fortune 500 companies worldwide in the U.S., Europe, Asia, and Africa and speaks regularly at industry conferences. − Co-author of several books including: • Data Modeling for the Business • Data Modeling Made Simple with CA ERwin Data Modeler r8
  3. 3. Where I Live(Photo taken on Saturday)3 February 8, 2012
  4. 4. Who Are You? Survey—How would you describe your role? A. Data Architect, Data Modeler, or Analyst B. Businessperson or Business Analyst C. DBA or Technical IT D. A combination of the above E. Other
  5. 5. Are you Using CA ERwin? Survey—Are you using CA ERwin currently? A. Yes!  B. No.  C. I’m not sure
  6. 6. What Version of ERwin? Survey—What version of ERwin are you using? A. 8.x B. 7.x C. 4.x D. 3.x or earlier E. I’m not using ERwin, which is very sad. 
  7. 7. Agenda 1 The Challenge: Managing Data Complexity 2 The CA ERwin Solution: Visualize the Power of Your Data 3 How a High-Level (Conceptual) Model Can Help 4 4 ase Study: Major Oil Company What’s New in the CA ERwin Product Family7 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  8. 8. The ChallengeManaging Data Complexity
  9. 9. The Challenge: Managing Data Complexity “Too Much Data, Too Little Time”More Data & Platforms to Support Most organizations have more than one database platform—it’s hard to be an expert in all The number of databases is growing, with more & more applications to support Many organizations are trying to integrate multiple systems – as a result of mergers andacquisitions, or for data warehousing or master data management projects The decision of what data to move to the Cloud is an important considerationFewer Staff and Resources Organizations are cutting back on IT staff, making it difficult to manage these growingdatabases Skill sets for individual databases are very specialized. It is unrealistic (and expensive) tohave multiple experts for all platforms 9 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  10. 10. The Business Challenge: Data Drives the Business – Make sure it’s Correct In today’s information age, data drives key business decisions. Executives ask questions such as:  How many customers do I have?  What is total revenue by region for last fiscal year?  Which products drove the most revenue this quarter? Behind the answers to those questions lies a data model.  Documenting the source and structure of data  What database(s) store customer information  How are these databases structure to store customer information  Defining key business terms  What is a product? e.g. Finished goods only? Raw materials?  Regulating business rules  Can a customer have more than one account? 10 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  11. 11. Information in ContextThere’s more to data than meets the eye A customer is I’d like a report someone who wants to buy showing all of A customer is our product. someone who A person’s not a our customers owns our customer if they don’t product. have an active maintenance account. Sales Business My customers Executive Accounting are internal employees. Which customer Support database do you Engineer want me to pull this from? We have 25. HR And, by the way, the Sybase databases all store Oracle customer information in a DB2 DBA different format. “CUST_NM” on DB2, “cust_last_nm” on Informix Oracle, etc. It’s a mess. SQL TeradataServer Data MS SAP Architect SQL Azure
  12. 12. The CA ERwin SolutionVisualize the Power of Your DataOn-Premise or in the Cloud
  13. 13. CA ERwin Data Modeler  Know what data you have: Create a visual inventory of source and target systems – Reverse Engineering  Know what your data means: Communicate key business requirements between business and IT stakeholders  Ensure that your data is consistent: Build consistent database structures - Forward Engineering CA ERwin® Data Modeler DB2 Oracle MySQL Sybase Oracle SQL Server SQL Sybase TeradataServer DB2 SQL SQL MySQL Teradata Azure Azure
  14. 14. CA ERwin Data Modeling
  15. 15. CA ERwin® Data Modeling At the Center of Your Data Management Initiatives Cloud or SaaS BI + Data ManagementMaster Data Management Business Intelligence + (MDM) Data Warehousing Data Data GovernanceManagement ERP Integration Application Developme Data Quality
  16. 16. CA ERwin Data ModelerProduct Editions
  17. 17. Why High-Level (Conceptual) Data ModelingIs Important
  18. 18. The Challenge—You’ve been tasked to assist in the creation of a Business Intelligence (BI) project—Trying to obtain a single view of ‘customer’—Technical and political challenges exist − Numerous systems have been built already—different platforms and databases − Parties cannot agree on a single definition of what a ‘customer’ is—Solution: Need to build a High-Level Data Model
  19. 19. What is a High-Level Data Model?—A high-level data model (HDM) uses simple graphical images to describe core concepts and principles of an organization and what they mean—The main audience of a HDM is businesspeople—An HDM is used to facilitate communication—It needs to be high-level enough to be intuitive, but still capture the rules and definitions needed to create database systems.
  20. 20. “A Picture is Worth a Thousand Words”Examples of High-Level Data Models
  21. 21. “A Picture is Worth a Thousand Words”Examples of High-Level Data Models Product Location Customer Region Order Raw Material Ingredient
  22. 22. “A Picture is Worth a Thousand Words”Examples of High-Level Data Models
  23. 23. “A Picture is Worth a Thousand Words”Examples of High-Level Data Models
  24. 24. “A Picture is Worth a Thousand Words”Examples of High-Level Data Models
  25. 25. “A Picture is Worth a Thousand Words”Examples of High-Level Data Models
  26. 26. Levels of Data Models
  27. 27. Levels of Data Models—Models can be built − Top-Down − Bottom-Up − Using a Hybrid Approach
  28. 28. How is this Different from a Logical Model? VHDM HDM LDMDefines the scope, audience, context for Defines key business concepts and their Represents core business rules and datainformation definitions relationships at a detailed levelMain purpose is for communication and Main purpose is for communication and Provides enough detail for subsequentagreement of scope and context agreement of definitions and business first cut physical design logicRelationships optional. If shown, Many-to-Many relationships OK Many-to-Many relationships resolvedrepresent hierarchy.Cardinality not shown Cardinality shown Cardinality shownNo attributes shown Attributes are optional. If shown, can be Attributes required and all attributes are composite attributes to convey business atomic. Primary and foreign keys meaning. defined.Not normalized (Relational models) Not normalized (Relational models) Fully normalized (Relational models)Subject names should represent high- Concept names should use business Entity names may be more abstractlevel data subjects or functional areas of terminologythe businessSubjects link to 1-M HDMs Many concepts are supertypes, although Supertypes all broken out to include sub- subtypes may be shown for clarity types‘One pager’ Should be a ‘one pager’ May be larger than one pageBusiness-driven Cross-functional & more senior people Multiple smaller groups of specialists involved in HDM process with fewer IT. and IT folks involved in LDM process.Informal notation ‘Looser’ notation required – some format Formal notation required construct needed, but ultimate goal is to be understood by a business user< 20 objects < 100 objects > 100 objects
  29. 29. Building a High-Level Data Model—Let’s go back to our challenge, to achieve a ‘single version of the truth’ for Customer information—We have 5 different systems with customer information in them: − 2 on Oracle − 1 on DB2 − 1 SAP system − 1 using MS SQL Server Oracle DB2 Oracle SQL SAP Server
  30. 30. Building a High-Level Data Model—We start with a very simple HDM, with just one object on it, called “Customer”.—We use an ER Model and show business definitions Too Simple??
  31. 31. Too simple?—Our team thought so, so went ahead and focused on the technical integration, including: − Reverse engineering a physical model from each system − Creating ETL scripts − Migrating the data into a single hub − Building a reporting system off of the data
  32. 32. Focusing on the Business—This implementation went “perfectly”, with no errors in the scripts, no data type inconsistencies, no delays in schedule, etc.—We built a complex BI reporting system to show our upper management the results.—We even sent out a welcome email to all of our customers, giving them a 50% off coupon, and thanking them for their support.
  33. 33. Focusing on the Business—Until we showed the report to the business sponsor: − We can’t have 2000 customers in this region! I know we only have around 400! − Why is Global Bank Company on this list? They are still evaluating our product! Sales was negotiating a 10% discount with them, and you just sent them a 50% coupon!?!? − You just spent all of that money in IT to build this report with bad data???
  34. 34. Back to the Drawing Board—After doing an extensive review of the six source systems, and talking with the system owners we discovered that: − The DB2 system was actually used by Sales to track their prospective “customers” − These “customers” didn’t match our definition—they didn’t own a product of ours!!
  35. 35. Oops!—We were mixing current customers, with prospects (non- customers). − We just sent a discount coupon to 1600 of the wrong people! − We gave upper management a report showing the wrong figure for our total number of customers! − We are now significantly over budget to have to go back and fix this!!—We started over, this time with a High-Level Data Model
  36. 36. Achieving Consensus We created a report of the various definitions of customer And verified with the various stakeholders that:  There were 2 (and only 2 definitions) of customer  Sales was OK with calling their “customer” a “prospect”
  37. 37. Resolving Differences—Our new high-level data model looked like this:
  38. 38. Identify Model Stakeholders— Make sure ALL relevant parties are involved in the design process Get buy-in!
  39. 39. Identify Model Stakeholders— Make sure ALL relevant parties are involved in the design process Get buy-in!
  40. 40. A HDM Facilitates Communication—A High-Level Data Model Facilitates Communication between Business and IT − Focus on your (business) audience • Intuitive display • Capture the business rules and definitions in your model − Simplicity does not mean lack of importance • A simple model can express important concepts • Ignoring the key business definitions can have negative affects − A model or tool is only part of the solution • Communication is key • Process and Best Practices are critical to achieve consensus and buy-in
  41. 41. Communication is the Main Goal of a High-Level Data Model—Wouldn’t it be helpful if we did this in daily life, too?—i.e. “Let’s go on a family vacation!” Person Concept Definition Father Vacation An opportunity to take the time to achieve new goals Mother Vacation Time to relax and read a book Jane Vacation A chance to get outside and exercise Bobby Vacation Time to be with friends Donna Vacation More time to build data models
  42. 42. Some Creative Ways to Facilitate Conversations withStakeholders— Food! − “Lunch and Learn” − Bring candy to meetings— Force? − “No bathroom breaks until we reach consensus!”— Active Listening − Understand why there is disagreement (e.g. “Ingredient” vs. Raw Material)— Fit into their schedule − Webinars − The “5 minute rule” for business execs – small, bite-sized models or questions.— Publish in an easily-accessible, intuitive format − Web-based publishing − Spreadsheet-style reporting
  43. 43. Identify Model Purpose— Key to success of any project is finding the right pain-point and solving it.— Make sure your model focuses on a particular pain point, i.e. migrating an application or understanding an area of the business Existing Proposed Business “Today an Account can “By next quarter, an only be owned by one Account can be owned by Customer.” more than one Customer.” Application “In the legacy Account “When we migrate to Management system, we SAP/R3, Account Holder call the customer an will be represented as Account Holder.” Object.”
  44. 44. Managing the Technical InfrastructureWhy do you need a modeling tool, and not a drawing tool?—Recall that we had multiple data sources on a variety of platforms: − 2 on Oracle − 1 on DB2 − 1 SAP system − 1 using MS SQL Server—How can CA ERwin help manage this? Oracle DB2 Oracle SQL SAP Server
  45. 45. Creating a Data Inventory— “Design Once, Reuse Many Times” across heterogeneous platforms— Design layers allow you to have a single high-level/logical model pointing to numerous physical model platforms. Oracle DB2 SQL Server
  46. 46. Design Layers Create both Business and Technical Designs Business Data DBA Sponsor Architect Physical Data Model Logical Data Model (Oracle) (Business Area 1)Conceptual Data Physical Data Model Model (SQL Server) Logical Data Model (Business Area 2) Physical Data Model (DB2)
  47. 47. A Data Model can be your Filter—A Data Model can add: − Focus – by Subject Area, by Platform, etc. − Visualization – Different Views for Different Audiences − Translation – to different DMBS AND to non DBMS formats such as UML, BI tools, Excel, XML, etc, etc. Data Model Oracle Oracle DB2 Developers Business Sponsors ETC! ETC! DB2 SQL 3NFServer IDMS SAP Data Architects DBAs
  48. 48. Create Different Displays for Different Audiences: BUSINESS—Business
  49. 49. Create Different Displays for DifferentAudiences: TECHNICAL
  50. 50. Generate Intuitive Reports for End UsersMany users want to see definitions, but not read a data model.
  51. 51. Use the Web to Share Information
  52. 52. Managing the Data Inventory witha Central Repository— A Central Model Store provides a single repository to store all of your data model assets— A collaborative environment for multiple modeling teams.— Metadata storage for: multiple models, multiple dbms platforms, multiple tools, multiple audiencesMultiple Multiple Multiple Tools MultipleModels DBMSs Audiences Oracle Teradata BI Tools DB2 SQL Developers Business Server Spreadsheets ETL Tools Sponsors Single Definition of 3NF “Customer” Central Model Store Data Architects DBAs
  53. 53. Understanding ERP Systems withCA ERwin Saphir Option Important metadata is found beyond traditional databases. ERP Systems also contain critical information about customers, employees, etc.  SAP, Oracle, JD Edwards, etc. These ERP systems are difficult to manage with a traditional “reverse engineering” process using a data modeling tool  There are thousands of tables  When we reverse engineer them, we get unintuitive technical names
  54. 54. Understanding ERP Systems withCA ERwin Saphir Option Using the CA ERwin Saphir Option, we can easily group tables by subject area, and can translate table and column names into intuitive, English versions. And can more easily integrate ERP data models into our enterprise data architecture.
  55. 55. CA ERwin Data Model Validator CA ERwin Data Model Validator checks models for consistency & accuracy with a “teach me” facility to learn from errors Great for new modelers and team members. Helps with governance of modeling projects.
  56. 56. What’s New in the CA ERwin Product FamilyCA ERwin Data Modeling r8.2
  57. 57. CA ERwin Data Modeling r8.2Three New OfferingsCA ERwin® Web Portal CA ERwin® Data CA ERwin® Data Model for Microsoft Modeler r8.2 SQL Azure Visualize Information Managing Data – Collaborationfrom the Web – for All Both On-Premise + in Facilitated Audiences the Cloud
  58. 58. Data Management – Moving to the Cloud Many customers are nervous moving their data to the Cloud. Concerns include:  Security/Privacy  Learning curve for new technologies  Integration with other data mgt. systems or applications A data model can help allay these fears  Assurance that your data is managed securely—using a data model as your roadmap. You decide what data stays on premise and what moves to the Cloud. Once in the Cloud, understand and manage the data stored off-premises.  Use Existing Skills: Customers can use the same familiar data modeling paradigm for Cloud- based data as for their on-premises data using CA ERwin Data Modeler.  Visualize both on-premises (Oracle, Sybase, SQL Server, DB2, etc.) and Cloud-based databases (MS SQL Azure) from a single data modeling environment
  59. 59. CA ERwin Data Modeler for Microsoft SQL AzureA Data Model is your Roadmap to the Cloud A Data Model is your “roadmap” for:  What data to move to the Cloud, and what to keep on-premise  Defining data structures (physical model) and business requirements (logical model) for Cloud databases Off-Premise doesn’t mean Out of your Control CA ERwin Data Modeler for Microsoft SQL Azure  Manage data structures in the Cloud on the MS SQL Azure platform  Visualize both on-premise (Oracle, Sybase, SQL Server, DB2, etc.) and Cloud-based databases (MS SQL Azure) from a single data modeling environment Oracle DB2 MS SQL SQL Azure Server Sybase MySQL Teradata
  60. 60. CA ERwin Web Portal Sharing Information with All Audiences— While some users need a — Many more can access & desktop tool to build and understand information via analyze data models, a web-based interface. Data Database Data Modeler Business Architect Administrator Analyst (DBA) Developer Business User / Steward Data Data Modeler BI Analyst Architect DBA MDM Analyst 60
  61. 61. CA ERwin Web PortalWeb-Based Search, Impact Analysis, Reporting The CA ERwin Web Portal makes it easy to share metadata (information in context) with both Business and Technical users  Internet-Style Keyword Search  Diagram Visualization  Graphical Impact Analysis  Reporting  Interfaces for Business vs. Technical Users  Easy to roll-out to multiple users (no local install) CA ERwin Web Portal
  62. 62. CA ERwin Web PortalDiagram Visualization with Drill-Down  View models in a variety of formats  IE, IDEF, UML, and more  Drill-down to see object details  Definitions, Comments, User- Defined Data Types, etc. 62 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  63. 63. CA ERwin Web PortalInternet-style Keyword Search63 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  64. 64. CA ERwin Web PortalGraphical Impact Analysis & Lineage64 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  65. 65. CA ERwin Data Modeler r8.2 Collaboration Facilitated CA ERwin Data Modeler r8.2 has two main features to facilitate collaboration across the enterprise: Active Model Templates  Allows more granular reuse of model object (tables, entities, domains)  Supports reuse and object sharing to help reduce costs and increase quality  Intuitive, wizard-driven interface Concurrent Licensing  Licenses can be more easily shared and managed across the organization via a web-based interface  Helping customers get the most our of their ERwin investment 65 February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  66. 66. Active Model Templates Creating Enterprise Standards— Ability to Reuse and Synchronize Enterprise Model Objects with other models across the Organization.Enterprise Model Objects Project 1 Synchronize Project 2 66 February 8, 2012
  67. 67. Active Model Templates— Ability to define “Enterprise” objects for Reuse − Share individual model objects, not just models • tables, entities, domains, etc. − Wizard-driven − Synchronize with other model objects • Automatically on model load • Or manually, user-driven through Wizard— First phase in “Data Dictionary” style model sharing − Next Step is Repository (Mart)-based sharing in r967 February 8, 2012
  68. 68. To Learn More, visit February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  69. 69. Summary— CA ERwin helps you manage the data complexity in your organization— Using high-level models can help increase communication with the business and achieve better results— CA ERwin Data Modeler r8.2 offers three new solutions − CA ERwin Web Portal − CA ERwin Data Modeler for SQL Azure − CA ERwin Data Modeler r8.2 point release— Helping you Visualize the Power of Your Data: On Premise or in the Cloud February 8, 2012 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.
  70. 70. thank you