Lançamento ERwin 08/02

CA ERwin Data ModelingVisualize the Power of Your DataOn Premise or in the Cloud

VP, Product Marketing

Donna Burbank

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

Where I Live (Photo taken on Saturday)

February 8, 2012

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

Are you Using CA ERwin? Survey

—Are you using CA ERwin currently?

A. Yes!

B. No.

C. I’m not sure

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 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.

Agenda

February 8, 2012

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 ase Study: Major Oil Company4 What’s New in the CA ERwin Product Family

The ChallengeManaging Data Complexity

9 CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.February 8, 2012

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 and acquisitions, or for data warehousing or master data management projects

The decision of what data to move to the Cloud is an important consideration

Fewer Staff and Resources

Organizations are cutting back on IT staff, making it difficult to manage these growing databases

Skill sets for individual databases are very specialized. It is unrealistic (and expensive) to have multiple experts for all platforms

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?


Information in ContextThere’s more to data than meets the eye

I’d like a report

showing all of

our customers

Support

Engineer

A person’s not a

customer if they don’t

have an active

maintenance account.

HR

My customers

are internal

employees.

Sales

A customer is

someone who

wants to buy

our product.

Accounting

A customer is

someone who

owns our

product.

Sybase

SAP

DB2Oracle

SQL

Server

MSSQL

Azure

InformixTeradata

DBA

Which customer

database do you

want me to pull

this from? We

have 25.

Data

Architect

And, by the way, the

databases all store

customer information in a

different format. “CUST_NM”

on DB2, “cust_last_nm” on

Oracle, etc. It’s a mess.

Business

Executive

The CA ERwin SolutionVisualize the Power of Your DataOn-Premise or in the Cloud

Sybase

MySQLOracle

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

EngineeringCA ERwin® Data Modeler

Teradata

Sybase

SQL Server

DB2

Teradata

SQL Server DB2

MySQLSQL Azure

SQL Azure

Oracle

CA ERwin Data Modeling

Data Governance

Application Development

Data Quality

Master Data Management

(MDM)

Data

Management

ERP

Integration

Business Intelligence +

Data Warehousing

Cloud or SaaS BI +

Data Management

CA ERwin® Data ModelingAt the Center of Your Data Management Initiatives

CA ERwin Data ModelerProduct Editions

Why High-Level (Conceptual) Data Modeling Is Important

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

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.

“A Picture is Worth a Thousand Words”Examples of High-Level Data Models


Product

Customer

Location

Order

Raw

MaterialIngredient

Region

Levels of Data Models

Levels of Data Models

—Models can be built

− Top-Down

− Bottom-Up

− Using a Hybrid Approach

VHDM HDM LDM

Defines the scope, audience, context for

information

Defines key business concepts and their

definitions

Represents core business rules and data

relationships at a detailed level

Main purpose is for communication and

agreement of scope and context

Main purpose is for communication and

agreement of definitions and business

logic

Provides enough detail for subsequent

first cut physical design

Relationships optional. If shown,

represent hierarchy.

Many-to-Many relationships OK Many-to-Many relationships resolved

Cardinality not shown Cardinality shown Cardinality shown

No attributes shown Attributes are optional. If shown, can be

composite attributes to convey business

meaning.

Attributes required and all attributes are

atomic. Primary and foreign keys

defined.

Not normalized (Relational models) Not normalized (Relational models) Fully normalized (Relational models)

Subject names should represent high-

level data subjects or functional areas of

the business

Concept names should use business

terminology

Entity names may be more abstract

Subjects link to 1-M HDMs Many concepts are supertypes, although

subtypes may be shown for clarity

Supertypes all broken out to include sub-

types

‘One pager’ Should be a ‘one pager’ May be larger than one page

Business-driven Cross-functional & more senior people

involved in HDM process with fewer IT.

Multiple smaller groups of specialists

and IT folks involved in LDM process.

Informal notation ‘Looser’ notation required – some format

construct needed, but ultimate goal is to

be understood by a business user

Formal notation required

< 20 objects < 100 objects > 100 objects

How is this Different from a Logical Model?

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

DB2

Oracle

Oracle

SQL

ServerSAP

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??

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

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.

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???

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!!

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

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”

Resolving Differences

—Our new high-level data model looked like this:

Identify Model Stakeholders

— Make sure ALL relevant parties are involved in the design process Get buy-in!

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

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

Some Creative Ways to Facilitate Conversations with Stakeholders

— 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

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

only be owned by one

Customer.”

“By next quarter, an

Account can be owned by

more than one Customer.”

Application “In the legacy Account

Management system, we

call the customer an

Account Holder.”

“When we migrate to

SAP/R3, Account Holder

will be represented as

Object.”

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?

DB2

Oracle

Oracle

SQL

ServerSAP

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

Design Layers Create both Business and Technical Designs

Business

Sponsor

Data

Architect

DBA

Conceptual Data

Model

Logical Data Model

(Business Area 1)

Logical Data Model

(Business Area 2)

Physical Data

Model

(Oracle)

Physical Data

Model

(SQL Server)

Physical Data

Model

(DB2)

A Data Model can be your Filter

SAP

DB2

DB2

Oracle

Oracle

IDMS

SQL

Server

—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

Developers Business

Sponsors

3NF

Data Architects

ETC! ETC!

DBAs

Create Different Displays for Different Audiences: BUSINESS

—Business

Create Different Displays for Different Audiences: TECHNICAL

Generate Intuitive Reports for End UsersMany users want to see definitions, but not read a data model.

Use the Web to Share Information

Managing the Data Inventory with a 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 audiences

Central Model Store

TeradataOracle

SQL

Server

DB2

Multiple

ModelsMultiple

DBMSs

Multiple Tools Multiple

Audiences

Single Definition of

“Customer”

Business

Sponsors

3NF

Data Architects DBAs

DevelopersSpreadsheets

BI Tools

ETL Tools

Understanding ERP Systems with CA 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

Understanding ERP Systems with CA 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.

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.

What’s New in the CA ERwin Product FamilyCA ERwin Data Modeling r8.2

CA ERwin Data Modeling r8.2Three New Offerings

CA ERwin® Web Portal

Visualize Information from the Web – for All

Audiences

CA ERwin® Data Model for Microsoft

SQL Azure

Managing Data –Both On-Premise + in

the Cloud

CA ERwin® Data Modeler r8.2

CollaborationFacilitated

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

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

MySQL

DB2

Teradata

SQL Server Sybase

Oracle

MSSQL Azure

— While some users need a

desktop tool to build and

analyze data models,

CA ERwin Web PortalSharing Information with All Audiences

60

— Many more can access &

understand information via

a web-based interface.

Data

Architect

Database

Administrator

(DBA)

Data Modeler

Business User /

Steward

MDM Analyst

Developer

BI AnalystData

Architect

DBA

Data Modeler

Business

Analyst

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

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.


CA ERwin Web PortalInternet-style Keyword Search


CA ERwin Web PortalGraphical Impact Analysis & Lineage


CA ERwin Data Modeler r8.2Collaboration 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


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— Ability to Reuse and Synchronize Enterprise Model Objects with other models across the Organization.

Active Model TemplatesCreating Enterprise Standards

February 8, 2012

Enterprise Model Objects

Synchronize

Project 1

Project 2

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— 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 r9

Active Model Templates

February 8, 2012

— 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

Summary

CA ERwin Data Modeling Copyright © 2012 CA. All rights reserved.February 8, 2012

thank you

Lançamento ERwin 08/02

Technology

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