DAMA International Webinar: 10 Keys to World-Class Metadata Management20150616 meta data dataversity...

www.EWSolutions.com© 2015 Enterprise Warehousing Solutions, Inc. (EWSolutions) – 1

EWSolutions

Strategic Partner & Systems IntegratorIntelligent Business Intelligencesm

10 Keys to World-Class

Meta Data Management

By David Marco

President

EWSolutions

www.EWSolutions.com

Contact us at [email protected]© 2015 Enterprise Warehousing Solutions, Inc. (EWSolutions) – 2


EWSolutions’ BackgroundEWSolutions is a Chicago-headquartered strategic partner and full life-cycle

systems integrator providing both award winning strategic consulting and full-

service implementation services. This combination affords our clients a full

range of services for any size enterprise information management, meta data

management, data governance and data warehouse/business intelligence

initiative. Our notable client projects have been featured in the Chicago Tribune,

Federal Computer Weekly, Journal of the American Medical Informatics

Association (JAMIA), Crain’s Chicago Business, and won the 2004 Intelligent

Enterprise’s RealWare award, 2007 Excellence in Information Integrity Award

nomination and DM Review’s 2005 World Class Solutions award.

For more information on our Strategic Consulting Services, Implementation Services,

or World-Class Training, email us at [email protected] or call at 630.920.0005

Best Business Intelligence Application

Information Integration

Client: Department of Defense

World Class

Solutions Award

Data Management

2007 Excellence in Information

Integrity Award Nomination

http://www.ewsolutions.com/news-events/news-press-releases/press_release.2005-10-03.9140171518


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EWSolutions’ Partial Client List

For more information on our Strategic Consulting Services, Implementation Services,

or World-Class Training email us at [email protected]

AFLACArizona Supreme Court

Bank of MontrealBankUnited

Basic American FoodsBecton, Dickinson and Company

Blue Cross Blue Shield companies

Booz Allen HamiltonBranch Banking & Trust (BB&T)

British Petroleum (BP)California DMV

California State Fund

Canadian National RailwayCapella University

CignaCollege Board

ComcastCorning Cable Systems

Countrywide Financial

Defense Logistics Agency (DLA)Delta Dental

Department of Defense (DoD)Driehaus Capital Management

Eli Lilly and Company

Environment Protection AgencyFarmers Insurance Group

Federal Aviation AdministrationFederal Bureau of Investigation (FBI)

Fidelity Information Services Ford Motor Company

GlaxoSmithKlineHarbor Funds

Harris BankThe Hartford

Harvard Pilgrim HealthCareHealth Care Services Corporation

Hewitt Associates

HP (Hewlett-Packard)Information Resources Inc.

International PaperJanus Mutual Funds

Johnson Controls

Key BankLiquidNet

Loyola Medical CenterManulife Financial

Mayo ClinicMcDonalds

Microsoft

MoneyGramNASA

National City BankNationwide

Neighborhood Health Plan

NORCPhysicians Mutual Insurance

PillsburyQuintiles

Sallie MaeSchneider National

Secretary of Defense/LogisticsSingapore Defense Science & Technology Agency

Social Security AdministrationSouth Orange County Community College

Standard Bank of South Africa

SunTrust BankTarget Corporation

The Regence GroupThomson Multimedia (RCA)

Thrivent Financial

United Health GroupUnited Nations (ICAO)

United States Air ForceUnited States Army

United States Department of StateUnited States Navy

United States Transportation Command

University of MichiganUniversity of Wisconsin Health

USAAUS Cellular

Waste Management

Wells FargoWisconsin Department of Transportation

Zurich Cantonal Bank

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David Marco – Professional Profile

Best known as the world’s foremost authority on meta data management and the father of the Managed Meta Data Environment, he is an internationally recognized expert in the fields of data governance, big data, data warehousing, master data management and enterprise information management (EIM). In 2004 David Marco was named the “Melvil Dewey of Metadata” by Crain’s Chicago Business as he was selected to their very prestigious “Top 40 Under 40” list. DavidMarco has authored several books including the widely acclaimed “Universal Meta Data Models”(Wiley, 2004) and the classic “Building and Managing the Meta Data Repository: A Full Life-Cycle Guide” (Wiley, 2000).

2014 EWSolutions was inducted into the Hinsdale business Hall-of-Fame after 6 consecutive years of receiving “Best of” awards in Enterprise Information Management

Selected to the prestigious 2004 Crain’s Chicago Business “Top 40 Under 40”

2008 DAMA Data Management Hall of Fame (Professional Achievement Award)

2007 DePaul University named him one of their “Top 14 Alumni Under 40”

Presented hundreds of keynotes/seminars across four continents

Published hundreds of articles on information technology

Author of several best selling information technology books

Taught at the University of Chicago and DePaul University

Holds both a CDMP and a CBIP certification

Email: [email protected]

http://lnkd.in/bky55wQ

http://lnkd.in/bky55wQ

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Agenda

Meta Data Management Fundamentals

Business vs. Technical Meta Data

Meta Data Management Use Cases

Meta Data Return on Investment (ROI)

Managed Meta Data Environment (MME) Fundamentals

Top 10 List

Real-World Case Studies

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Meta Data

Management

Fundamentals

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Meta Data vs. Data

Meta Data: Meta data contains the knowledge that a 1) field is called “Customer_Name”, is 40 characters in length, and exists in systems A, B, and C; 2) that our company has 3 systems which contain customer master data. These systems are…

Data: Data would be a specific instance of “Customer_Name” equaling “John Doe”

Information: Data that is meaningful to a business user. They understand it and they know what to do with it

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Meta Data Management Fundamentals

(content) (context)

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Managed Meta Data

Environment ROI

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Managed Meta Data Environment ROI

“The key to your company’s prosperity is how well

you gather, retain and disseminate knowledge”

“Managed meta data environments are the key to

gathering, retaining and disseminating knowledge”

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Meta Data for the Business (business meta

data)

Meta Data for the IT Department (technical

meta data)

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Business Meta Data

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Meta Data for the Business

Reduces training costs

Makes strategic information (e.g. data warehousing, CRM, SCM, etc.) much more valuable as it aids analysts in making more profitable decisions

Create actionable information

Limits incorrect decisions

Assists business analysts in finding the information they need, in a timely manner

Bridges the gap between business users and IT professionals

Increases confidence in the IT system data

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Meta Data Providing the

Semantic Layer

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Meta Data for the Business2015 Monthly Global Sales Report February 7, 2015

Month Sales $ (in thousands)

U.S

Sales $ (in thousands

International Product Category Sales $ (in thousands

Total

December TV 22,101

DVD

12,190

Digital 4,002

1,209Miscellaneous

Cellular Phone

11,190

10,200

7,193

1,301

870

4,300

32,301

19,383

5,303

2,079

15,490

November TV 42,000

DVD

28,193

Digital 8,901

2,730Miscellaneous

Cellular Phone

21,190

22,200

12,193

2,901

1,530

9,878

64,200

40,386

11,802

4,260

31,068

October TV 70,100

DVD

41,700

Digital 20,000

4,850Miscellaneous

Cellular Phone

31,900

32,950

17,550

4,100

2,850

14,878

103,050

59,250

24,100

7,700

46,778

“Sales $ U.S.” is comprised of

aggregated sales revenues from the

United States, Canada, and Mexico,

but does not subtract sales dollars

from returned orders

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Meta Data for the Business

2015 Monthly Global Sales Report February 7, 2015

Month Sales $ (in thousands)

U.S

Sales $ (in thousands

International Product Category Sales $ (in thousands

Total

December TV 22,101

DVD

12,190

Digital 4,002

1,209Miscellaneous

Cellular Phone

11,190

10,200

7,193

1,301

870

4,300

32,301

19,383

5,303

2,079

15,490

November TV 42,000

DVD

28,193

Digital 8,901

2,730Miscellaneous

Cellular Phone

21,190

22,200

12,193

2,901

1,530

9,878

64,200

40,386

11,802

4,260

31,068

October TV 70,100

DVD

41,700

Digital 20,000

4,850Miscellaneous

Cellular Phone

31,900

32,950

17,550

4,100

2,850

14,878

103,050

59,250

24,100

7,700

46,778

Information Quality Tracking Statistics

8.4% of the dollar values were not loaded

1.7% of the records were not loaded

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Technical Meta Data

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Meta Data for the IT (Information Technology) Department is

Technical Meta Data

Help IT departments better manage, maintain and grow their

IT systems and assets

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What Do Our Current IT

Systems Look Like?

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Islands of Data

Operational

Applications

Islands of

Data

End User

Reporting

Systems

Claims

Pharmacy

Financial Analysis

Health & Medical

Services (CQM, HSA)

Actuarial & Underwriting

Analysis

Sales & Mktg /

Network Development

Utilization

Membership/Enrollment &

Billing

Standard

Adhoc

Standard

Adhoc

Standard

Adhoc

Standard

Adhoc

Standard

Adhoc

Standard

Adhoc

Standard

Adhoc

Standard

Adhoc

North E/B

TOPPSES-9000

IPS- Inter Practice SystemVAX(Burlington)

PSIMEDHPE-980

MGD ClaimsAS/400

Query

Pharmacare (outside vendor)AS/400

Pharmaview (outside vendor)

NED E/BACPS- Automatic Claims

Processing SystemPASS - Patient Appointment

Scheduling SystemENCOUNTERFFS - Fee For Service

REF - Referrals

HP-992 NEDClinical Computer

Pharmacy DB

Provider Master

AMISYSMARS

•Hospital Summary•Quality Assurance Request

HP (9 series)

•Network & Medical Request•Actuarial End User Request•ClaimsProv DBDrug DB

AMRS-Advanced Medical

Record SystemRIS- Radiology Information

SystemLAB/LIS- Laboratory

Information System

VAX ClusterRX42

HPE-980

MHUM - Mental Health

Utilization Management

AST 486 serverHealthchex

Pentium PCBulletin Board System (BBS)

NED DatawarehouseHP937

HSA dept. Lan Server

NED Multiview GL and AP

PHC Pharmacy Server

PHC Actuarial Analysis Server

Analytic Database

QuantumDec Alpha

MAMSYS/PAPSYS

PHC JV Finance Server

PHC Network Development Server

PHC Medical Services Server

PHC Multi-view GL.

(14) Foxpro Applications

ASAP - Actuarial System

Analysis Program

MS SQL Server

DB2 and SAS datasetDecision Analyzer

GL

SAS , SAS screens,

Viewpoint

GMIS-Claim Check

Actuarial SAS dataset

ES-9000

Medical

Groups

HCD MGD NED PHCLegend Multiple colors indicate the system is

used by multiple divisions.

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Meta Data for the IT Department

Dramatically reduces the probability of project failure

Speeds system’s time-to-market

Reduce system development life-cycle time

Limit redundant data

Limit redundant processes

Managing IT portfolios

Leverage work done by other teams

Reduced rework

Reduce research time

Reduce unproductive work

Lowers the impact of staff turnover

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Technical

Impact Analysis

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Impact Analysis Report January 7, 2015

Impact Field Tables/Files

Impacted

Fields ImpactedProgram Impacted

Customer_Name CUSTOMER_PR02 DW_CUSTOMER T

I02_CUSTOMER

Cust_Name_First

Cust_Name_Middle

Cust_Name_Last

Source

System

Order Entry

Table

Type

I Cust_Name_First

Cust_Name_Middle

Cust_Name_Last

CUSTOMER_PR01

Source

Table

CUST

Customer_Addr DW_CUSTOMER T

I02_CUSTOMER

Cust_Name_Address

Cust_Name_City

Cust_Name_State

I Cust_Name_Address

Cust_Name_City

Cust_Name_State

CUSTOMER_PR02

CUSTOMER_PR01

Cust_Name_Zip

Cust_Name_Zip

Question: Show all decision support tables/files, programs, and fields impacted by a change to the

“CUST” table in the “Order Entry” system

*Legend

“T” = Target

“I” = Intermediate

“S” = Source

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Impact Analysis Report January 7, 2015

DomainTables/Files Fields

Alphanumeric 20

DW_CUSTOMER

Order Entry

ORDER_HEADER

CUST_NAME

CUST_NAME

CUST_NAME

Field

Customer Name

System

CUST_NAME

CUST_NAME

Cust_Name

EXPENSES

I01_CUSTOMER

Cust_Name

Cust_Name

Cust_Name

Cust_Name

DM_Cust_Name

DM_Cust_Name

Cust_Name

DM_Cust_Name

Question: Show all systems, tables/files, fields, and their domains impacted by a change to the length of

all occurrences of the Customer_Name field

General Ledger

Data Warehouse

Data Mart - Marketing

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

I02_CUSTOMER

I03_CUSTOMER

DM_CUSTOMER

I01_DM_CUSTOMER

I02_DM_CUSTOMER

CUST_ACCOUNTS

CUSTOMER

ORDER_DETAIL

CUSTOMER_SHIP_TO

CUSTOMER_SELL_TO

CUSTOMER_BILL_TO

Cust_Name

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

Alphanumeric 20

Alphanumeric 35

Alphanumeric 35

Alphanumeric 35

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MME For Systems

Consolidation

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Meta Data for the IT DepartmentAugust 15, 2015Systems Consolidation Report

Small Town BankBigCity Bank

Attribute

Name

Attribute

Definition

Entity

Name

System

Name

Attribute

Name

Attribute

Definition

Entity

Name

System

Name

Cust_Nbr Cust_Nbr is the attribute of

record for BigCity Bank

customer numbers

Cust_Tbl Central

Customer

System

CUSTNUM Customer numbers from

the deposit system.

CUSTTABLE CUSTAPPL

Purchase_No Customer numbers from

the purchase in the legacy

deposit system

Purch_Tbl CUSTSYS

Borwr_No Customer numbers from

the loan system.

Borrower_File LoanSys

Cust_Type Cust_Type is the attribute

of record for BigCity Bank

customer types (affluent,

upward, standard, high

risk).

Cust_Tbl Central

Customer

System

CUSTCDE Customer types from the

general ledger system.

GL_CUST GLAPPL

Cust_Card_Ind Cust_Card_Ind is the

attribute of record for

BigCity Bank customer ‘s

that have a BCB credit

card.

Cust_Tbl Central

Customer

System

None applicable

Cust_Crdt_Ratg Cust_Crdt_Ratg is the


BigCity Bank customer

credit ratings (Superior

Risk, Low Risk, Standard

Risk, High Risk, Extreme

Risk).

Cust_Tbl Central

Customer

System

Credit_Rate Customer rate is from the

general ledger system and

refers to the credit

rating/worthiness of a

customer.

GL_CUST GLAPPL

BigCity Bank

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Meta Data for the IT DepartmentAugust 15, 2015Systems Consolidation Report

Small Town BankBigCity Bank

Entity

Name

Attribute

Definition

Attribute

Name

Domain

Value

Attribute

Name

Transformation

Rules

Entity

Name

Domain

Value

Cust_TypeCust_Type is the attribute

of record for BigCity Bank

customer types:

1 = affluent

2 = upward

3 = standard

4 = high risk

Cust_Tbl

1 CUSTCDECust_Type = 1 WHEN

CUSTCDE = 3 AND

CUSTBAL > 500,000

GL_CUST3

CUSTBAL GL_CUSTHigh cardinality field


CUSTCDE = 4 AND

CUSTBAL <= 500,000 AND

CUSTBAL > 200,000

GL_CUST3



CUSTCDE = 1 or 2 AND

CUSTBAL <= 200,000 AND

CUSTBAL > 75,000

GL_CUST3



CUSTCDE = 0 AND

CUSTBAL < 75,000 AND

Credit_Rate < 22

GL_CUST3


Credit_Rate GL_CUSTHigh cardinality field

Cust_Card_Ind Cust_Card_Ind is the


BigCity Bank customer ‘s

that have a BCB credit

card.

Cust_Tbl

BigCity Bank

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The Cost of Redundancy

Large healthcare insurance company

Has a $1.6 billion IT budget

They estimate it costs them $2 per month to store each gigabyte of data

$8 per month if you add in services and maintenance

They estimate that they have 1.6 petabytes of redundant data

What does this cost them yearly? Simple math

$8 x 12 months x 1,000,000 (1.6 petabytes) = $153,600,000

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“We Build Systems To Manage Every Aspect

Of Our Business, Except One To Manage The

Systems Themselves.”

“A Managed Meta Data Environment Is A

System That Manages Our Systems.”

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MME ROI

Intel finds huge ROI in managing meta data

Estimates $6 in savings for every $1 spent

• Emphasis on reducing developer’s average research time of 30%

• Uses “Centralized” architecture

• Key to success is based on regular, frequent “scan updates”

Source: Computer World magazine – July 2005

A Canadian government agency achieved:

More than 90 percent reuse of existing data definitions

85 percent improvement in application integration

25 percent reduction in DW analysis and design

Impact analysis study in 2 hours vs. 36 person-days of consulting

“Knowledge workers spend up to 2.5 hours each day looking for information… but find what they are looking for only 40% of the time.”

Kit Sims Taylor – Economist and Researcher in “Economics of information and networks” Bellevue Community College, WA

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50% of developer time today is spent “searching”i.e: Determining the effects and depth of changes/ enhancements/ new

development. Understanding system problems, semantics, etc.

20% of the 50% (10% overall) can easily be reduced by implementing and utilizing a Metadata management solution.

Source: Gartner group

MME ROI

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Managed Meta Data

Environment

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Managed Meta Data Environment

Managed Meta Data Environment (MME): The

managed meta data environment represents the

architectural components, people and processes

that are required to properly and systematically

gather, retain and disseminate meta data

throughout the enterprise.

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Managed Meta Data Environment

Meta Data Sourcing Layer

Meta Data

Extract Meta Data

RepositoryMessaging/Transactions(EAI, web services, XML, etc.)

SoftwareTools

Meta Data Delivery Layer

Meta Data

Management LayerDocuments/Spreadsheets

End Users(business and technical)

Third Parties (business partners, vendors, customers, government agencies)

Meta Data

Extract

Meta Data

Extract

Meta Data

Extract

Meta Data

Extract

M

e

t

a

D

a

t

a

I

n

t

e

g

r

a

t

i

o

n

L

a

y

e

r

Data Warehouse/

Data Mart(s)

Websites/E-Commerce

Third Parties (vendors, customers,government agencies)

Meta Data

Marts


Business Users

Applications (CRM, ERP, etc.)


Websites/E-Commerce

Applications(CRM, ERP, data warehouses, etc.)

Meta Data

Extract

Messaging/Transactions(EAI, web services, XML, etc.)

Software Tools

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Six Components Of The MME

Meta Data Sourcing Layer

Meta Data Integration Layer

Meta Data Management Layer

Meta Data Repository

Meta Data Marts

Meta Data Delivery Layer

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RBC Financial

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RBC Financial Group

Canada’s largest financial institution as measured by market capitalization and assets, and is one of North America’s leading diversified financial services companies

Provides personal and commercial banking, wealth management services, insurance, corporate and investment banking, and transaction processing services on a global basis

Employs 60,000 people, who serve more than 12 million personal, business, and public sector clients through offices in North America and some 30 countries around the world

Has millions of active Canadian online customers

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RBC Financial Group

Challenges/Opportunities

RBC Financial Group’s Data Warehouse Environment (DWE) consists of five databases and contains more than 5 terabytes of data

DWE end users required a tool to gain knowledge of the data content as well as an understanding of the data sources to effectively utilize the DWE environment

RBC Financial Group has hundreds of applications, all interfacing and sharing data

Need to reduce the risk and effort necessary to modify their IT systems during application changes

Must improve their product’s time to market

Many applications within the organization are well known by only a handful of key individuals. Therefore, they needed to capture this information (meta data) from these individuals before the corporate knowledge is lost

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RBC Financial Group

MME Overview

Enterprise-level MME that provides an inventory of the company’s information assets, a documentation facility for IT applications, the capability for enterprise-wide impact analysis, and a map for data movement

This meta data management solution was directly supported by RBC Financial Group’s executive management

Deployed in 1993

MME provides value to both business and technical users via a customized Web front end

The MME’s use has grown significantly in recent years and has become ingrained into the work processes at the bank

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RBC Financial Group

Custom

Web Interface

Managed Metadata

Environment

(Vendor Products and

In-house Developed)

Data

Warehouse

Environment

(Enterprise Data

Warehouse, Data

Marts)Catalog Info,

ETL Mapping,

Transformatio

n

Application

Database

Catalogs

Catalog

Information

Data Models

- Logical models

- Physical models

- Standards

Tool

Interface

Mainframe

Metadata

Legacy

COBOL

Nig

htly S

ca

ns

Change

Management Tool

Batch

Interfaces

Extract

Update

Metadata

RationalizationExtract/

Reload

Non-Mainframe Metadata

- XML tags

- Distributed Systems

- External Sources

Import

Development

Community

Business

Community

Defin

itions, T

ech

nica

l

info

rmatio

n

Busi

ness

Meta

data

Secu

rity

Cla

ssifi

catio

ns

Researc

h /

understa

ndingResearch /

understanding

Load

Business Users

Data Stewards

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RBC Financial Group

MME ROI

RBC Financial Group believes that the largest part of application support and maintenance is spent on manual impact analysis

Therefore, they focused their MME on reducing the cost of their IT environment. This MME accomplishes this by providing the following benefits: Documentation, source-to-target mapping, and change notification for the DWE

Identification, publication, and maintenance of over 4,900 batch interfaces among more than 200 applications

Assisting applications in mapping and gap analysis. One particular project generated more than 10,000 hits to the web site, preventing thousands of phone calls

Rationalization of the MME data elements, which allows impact analysis across 200 applications and can be completed in hours or days as opposed to weeks or months

Identification and publication of data element standards

In the late 1990’s, a major credit card company asked RBC Financial Group to change their credit card number from 13 bytes to 16 bytes This company assigned three people for 4 to 6 months to identify the 122 changes they needed to

make to their systems

Using the MME RBC Financial Group identified 144 changes that would be needed to its systems and accomplished this analysis in 15 minutes

Typically, large banks spend 15% to 22% of non-interest expenses (NIE) on their IT systems, while RBC Financial Group spends approximately 13% of NIE on their IT systems—See next slide

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RBC Financial Group

12

CITIGROUP

J P MORGAN CHASE

BANK OF AMERICA

BANK ONE

WELLS FARGO

WACHOVIA

FLEET BOSTON

RBCFG

PNC GROUP

5.3 US$ Billion

4.6

3.9

2.0

1.9

1.6

1.1

0.9

U.S. Industry Total (2002): US$32.1 Billion

For largest US banks (assets over

US$70 Billion) IT spending ranges from

15 - 22% of NIE

RBCFG estimate is 13%

Projected 2002 IT Spending by U.S. Banks

0.6

(1)

(1) IT spending defined as excluding Voice Telecom. RBC estimate is $1,484MM CAD less $130MM Voice Telecom =

$1,354MM / 1.55 = $0.9Billion USD

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What To Avoid When

Building A Managed

Meta Data

Environment

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What To Avoid

Top 10 List

#10 MME team creates standards none of the supporting teams can follow

#9 Not creating a MME team and/or trivializing the MME effort

#8 Failing to have an experienced meta data project manager/architect leading the project

#7 Neglecting to change the “status quo”

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What To Avoid

#6 Creating meta data silos – “Islands of Meta Data”

#5 Too many manual meta data integration processes

#4 Not providing EASY access to the meta data

#3 Selecting a meta data tool without conducting an

evaluation or defining requirements

#2 Trying to do a “Big Bang” (waterfall)

implementation…Boiling the Ocean

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What To Avoid

Not defining tangible business/technical objectives of the managed

meta data environment!!

Number #1 Reason

Good Business Drivers

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Department of Defense



World Class Solutions Award

Data Management



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How Large is the DoD Supply Chain?

$480 Billion Dollars Budget

$80 Billion Supply Chain

3 Million People

8 Million Parts

Global – 150 Countries

Dynamic Supply Chain



World Class Solutions Award

Data Management



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What’s the Challenge

We Can’t Account for Several Billion Dollars a

Year

We Have Data Quality Issues

We Fix or Refine a Process and Break Several

Other Processes

Never Planned the Enterprise

The Enterprise “Just Grew”

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DoD Enterprise Architecture is Based on:

Support rapid, agile deployment, employment,

sustainment and reset/reconstitution Total Force,

within acceptable risk, across the full

spectrum of operations in a cost-

effective manner (ROI)

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Enterprise Integrated Data Environment (EIDE)

Provide an enhanced environment that enables the DoD Logistics Enterprise to execute practices, processes, applications and decision support tools to achieve logistics interoperability and allow for information exchange within and between internal and external DoD business partners.

- Non-system dependent transactions

- Consolidation and reuse of Interfaces

- Data integration/sharing

- Leverage Modernization Efforts

- Data Standards not Standard Data

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DoD Enterprise Logistics

DMMSS(G005M)

ATLASSII+

CEMS1(D042A)

REMIS

CAEMS

MUMMS-SS06

LOGMOD

OWRMR(D072)

RSSL(D040)CMOS

JFAST

GDSSTOPS

WPS

IBS

AMS(MTMC)

CCSSGFM(CFM-HOST)

TC-AIMSII

SDS

MRDB MRDB

SAMMS EMACS

WARRS

IMWRP(D035A)CMOS

CALM

LOGMODWSMIS-ETADS

(O132A)

CEMS1

(D042A)

MUMMS-SS10

ATLASSII+

TMS

MUMMS

-SS06

CAEMS

MRP(MC)

DISMSDISMS

DSS DAISY

FAS

HMIS

TOPS

GTN JFAST

WPS

IBS

MISILCISIL

TC-ACCIS

SDSSARSS-1 MTMS

MRDBSPBS-R

AFMIS

COMPASS

ERSSARSS-2AC/2BAMS(MTMC)

TC-AIMSII

SAAS-MOD

AALPS

ETADS

DSS FAS

DAISY

HMIS

TOPS

WPS IBS

JFAST

GTN

MISILCISIL

SARSS-GATEWAY

COMPASS

TC-AIMSIIAALPS TC-ACCIS

AMS(MTMC)SARSS-1

MIDAS

AMS(MTMC)

CCSS

SAAS-MODCOMPASS SPBS-R

SARSS-GATEWAYTC-ACCIS

AFMIS

MIDAS

SARSS-2AC/2BSARSS-2AD SARSS-1

SDS

SUPMIS

ROLMS TANDEM

RAM

UICP-RESYS

LOGMOD

REMISMIICS(D043)

WARRSIMWRP(D035A)

JAMSSRSSL(D040)

CMOS

SBSS/ILS-SAFPS(D220)

SCS(D035)WSMIS-ETADS

(O132A)

CALMETADS

OWRMR(D072)

CEMS1(D042A)

ITEMAPPS

MRP(MC)MUMMS-SS07

MUMMS-SS10

SASSYMAARSII

ATLASSII+

CAEMS

DAISY

DSS

BOSS

EMACS

FAS

DISMS

SAMMS

TOPS

WPS IBS

JFAST

GTN

AFMIS

TC-ACCIS

AMS(MTMC)CCSS TC-AIMSII

COMPASSMIDAS

SPBS-R

AALPS

SARSS-GATEWAYSARSS-1 SARSS-2AD

SARSS-2AC/2B

SAAS-MOD

SDS

TANDEM

RAM UICP-RESYS

SUPMIS

ROLMS

CALM

WSMIS-ETADS(O132A)LOGMOD

CMOSREMIS

AFPS(D220)MIICS(D043)

ETADS

SBSS/ILS-SSCS(D035)

IMWRP(D035A)CEMS1(D042A)

JAMSSWARRS

OWRMR(D072)

RSSL(D040)

MUMMS-SS07

ATLASSII+MAARSII

ITEMAPPS

MRP(MC)MUMMS-SS10

SASSY

CAEMS

BOSS

DISMS

DSS

FAS

SAMMS

EMACS

DAISY

JFAST

TOPS WPS

GTN

IBS

ACCLAIMS COMPASS

ATAVGCSS-A LIDB

TC-AIMSIISAAS-MODELIST

IC3

CMOS

BROKERCEMS1(D042A)

LOGMODMANPER-B

MAGTFII

CAEMS

LMIS

ATLASSI

MCDSS

JFRGIIMDSSII

MUMMS-SS06

WRS

GCCSICIS

TOPS

AMPAPODModel

IBS

WPSGDSS

JFASTBDSS

OWRMR(D072)

RSSL(D040)

SAMMS

SARSS-2AC/2B

SARSS-2ADSARSS-1

SPBS-RSDS

SARSS-GATEWAYSAAS-MOD

MIDASAMS(MTMC)

CCSSATS

UITATAV

DESCBS-X

AFMIS

ROLMS

SUPMIS

FACTSUICP-RESYS

HMMS

CAIMSMMS

RAM

TANDEM

MIICS(D043)

CEMS1(D042A)

AFPS(D220)REMIS

JTAVSAMMS

BOSSDFAMS

DAISY

DESEXDSS

DISMS

FAS EMACS

SDSCCSS

REMISDMMSS(G005M)

ATLASSI

ATLASSII+

MDSSII

EMACS

SDSCCSS

REMIS

OWRMR(D072) RSSL(D040)

DMMSS(G005M)

ATLASSII+

MDSSII

ATLASSI

EMACSSAMMS

DAMMS-RBLKIII

GFM(CFM-HOST)

AMS(MTMC) ELIST

TC-ACCIS

GOPAX

FACTSNAOMIS

CMOS

GATES LOGMOD

GTN21

TC-AIMS

CAEMS MDSSII

MAGTFII

JFRGII

WPS

JFAST GTN

GDSS

IBS

SDSIFS

CCSS

DMMSS(G005M)

EMACS

DBMS

DAMMS-RBLKIIIELIST

TC-AIMSIICOMPASS

GFM(CFM-HOST)GOPAX

TC-ACCISAMS(MTMC)

AALPS

FACTSNAOMIS

GATES

ETADS

CALM

WSMIS-ETADS

(O132A)

LOGMOD

CMOS

GTN21

JFRGII

MAGTFII CAEMS

TC-AIMS

MDSSII

JFAST

WPS

GTN

GDSS

TOPS

IBS

TRAC2ES

SARSS-2AD

CCSSCBS-X

DESUIT

SDSATS

SARSS-GATEWAYSARSS-2AC/2B

SARSS-1ATAV

SPBS-RAFMIS

MIDASAMS(MTMC)

SAAS-MOD

UICP-RESYS

RAM

ROLMSTANDEM

HMMS

CAIMSSUPMIS

MMS

FACTS

REMIS

MIICS(D043)

AFPS(D220)OWRMR(D072)

JAMSSSIS(D035T)

RSSL(D040)

SBSS/ILS-SCEMS1(D042A)

SCS(D035)SSRAC(D169)

WARRS

IMWRP

(D035A)

MUMMS-SS07

MRP(MC)MUMMS-SS10

SASSY

MUMMS-SS06

ATLASSII+

MDSSIIATLASSI

ITEMAPPS

MAARSII

DISMS

DESEXDSS

DFAMS

DAISY

BOSS

JTAVFAS

SAMMS

EMACS

SARSS

-2AC/2B

SARSS-

GATEWAY

GFM

(CFM-HOST)

SARSS-1 ACLDBFEDLOG

ERSMIDAS SDS

SB-

700-

20

SPBS-RSAAS

-MOD

AFMISCCSS EIC

LIF MRDBMILSTEP

SARSS-2AD

MMS

ROLMS

SUPMIS

UICP-RESYS

RAM

TANDEM

MIICS(D043)

AFERS(D143C)REMIS

CSCPS(D155)CE-CM(D042E)

CEMS1(D042A)WARRS

FSSSYSTEM

SSRAC(D169)

DMMSS(G005M)


SBSS/ILS-SSCS(D035)

IMWRP

(D035A)MIIDB(D043A)

JAMSS

RSSL(D040)

ATLASSII+

ITEMAPPS

MRP(MC)MUMMS-SS05

TDMS

SASSY

SAMMS

EMACS

MEDALSFAS

DAISYBOSS

BSM

DSSDISMS

DESEXDFAMS

TOPS

RASFIARS

CISILMISIL

MOCAS

MTMS

SDSERS SPBS-R

MRDBSAAS-MOD CCSS

AFMISSARSS-1SARSS-2AC/2B

JCALS

ATIS(32BIT)

ATIS(16BIT)

MSPECS

MCA

SETS

JEDMICS

CE-CM(D042E)

CEMS1(D042A)

REMIS

DMMSS(G005M)

IMWRP(D035A)

WARRS

OLVIMS

MUMMS-SS10

ATLASSII+SASSY

MUMMS-SS06

TMSTDMS

MRP

(MC)

CAEMS

TMPODS

DSSEMACS

MEDALS

HMISFAS

DISMS

DAISY

MISILCISIL

MIIDB(D043A)

JAMSSRSSL(D040)

FSSSYSTEMOWRMR(D072)

MIICS(D043)SBSS/ILS-S

CEMS1(D042A)

WARRS

AFPS(D220)

CE-CM(D042E)IMWRP(D035A)

SCS(D035)REMIS

CSCPS(D155)DMMSS(G005M)

SSRAC(D169)

AFERS(D143C)

ATLASSII+

MAARSII

SASSYMRP(MC)

ATLASSI

ITEMAPPS

TDMS

MUMMS-SS05MUMMS

-SS10

MUMMS-SS07

MUMMS-SS06

TMPODS

FLIS

CALM

ETADSIMWRP(D035A)

CEMS1(D042A)

WARRSCMOS

LOGMOD

WSMIS-ETADS

(O132A)

MRP(MC)

ATLASSII+

MUMMS

-SS06

TMS

MUMMS-SS10

CAEMS

SDS

SPBS-RAFMIS CCSS

SAAS-MOD

SARSS-2AC/2B

SARSS-2AD

ROLMS

RAM TANDEM

UICP-RESYS

SUPMIS

AFPS(D220)

CALMOWRMR(D072)

RSSL(D040)JAMSS

ETADSREMIS

SBSS/ILS-S

WSMIS-ETADS

(O132A)CEMS1(D042A)

MIICS

(D043)WARRS

IMWRP(D035A)SCS(D035)

LOGMOD

CMOS

MAARSII

CAEMSSASSY

MUMMS-SS10

MUMMS-SS07MRP(MC)

ITEMAPPS

ATLASSII+

FAS

DAISY

DSS

SAMMS

EMACS

BOSS

DISMS

IBS

GTN WPS

TOPS

JFAST

AALPS

TC-AIMSII

OWRMR(D072)JAMSS

SIS(D035T)

RSSL(D040)SSRAC(D169)

SCS(D035)WARRS

IMWRP(D035A)

SBSS/ILS-S

MUMMS-SS10

MDSSII

SASSYATLASSII+

MRP(MC)

MUMMS-SS07MAARSII

ATLASSI

ITEMAPPS

MAARSII

MUMMS-SS10ATLASSI

MUMMS-SS07

MUMMS-SS06

DFAMS

EMACS

FLISDSS

MEDALSDISMS

SAMMS

DESEXDAISY

BSMBOSS

TMPODS

FAS

TOPS

CISIL

RASFIARS MOCAS

MISIL

CCSS

AFMISGFM(CFM-HOST) EIC

SDSSPBS-R MILSTEP

LIFMRDB SARSS-2AC/2B

ERSFEDLOGSARSS

-GATEWAY

SB-700-20SARSS-1 SAAS-MOD

SARSS-2ADMIDAS

ACLDB

SUPMIS

MMS

ROLMS

TANDEM

RAM

UICP-RESYS

WARRS

SCS(D035)REMIS

JAMSSRSSL(D040)

IMWRP

(D035A)SBSS/ILS-S

CEMS1

(D042A)

AFERS(D143C)

CSCPS(D155)

SSRAC(D169)DMMSS

(G005M)


MIIDB(D043A)MIICS(D043)

FSSSYSTEM

CE-CM(D042E)

ATLASSII+

SASSY

TDMSMUMMS-SS10

MUMMS-SS07

MUMMS-SS06

MUMMS-SS05

MRP(MC)ITEMAPPS

ATLASSI

MAARSII

DISMS

FLIS

ELISTATAV

SAAS-MOD

ACCLAIMSGCSS-A

COMPASS

IC3

MANPER-BBROKER

MCDSSWRS

JFRGII

MAGTFIIMDSSII

ATLASSILMIS

GCCSICIS

AMPAPODModel

SDSAFMIS SAAS-MOD

SARSS-1

SARSS-2AC/2B

ERS SPBS-R

MTMSJCALSCCSS

MSPECS

JEDMICS

ATIS(16BIT)

ATIS(32BIT)

MCA

SETS

WARRS

IMWRP

(D035A)

CE-CM(D042E)

OLVIMS

FASDSS

SAMMSEMACS

MEDALS

BSMDAISY

DFAMSBOSS

TMPODS

DESEX

TOPS

MOCAS

MISILCISIL

RASFIARS

SAAS-MOD

AFMIS LIF

GFM

(CFM-HOST)

SARSS-

2AC/2BMIDAS

MILSTEPMRDB SPBS-R

FEDLOG

ERSSDS ACLDB

SB-700-20CCSS SARSS-2AD

SARSS-GATEWAY

SARSS-1

EIC

RAM

SUPMIS

TANDEM

UICP-RESYS

MMS

ROLMS

DMMSS(G005M)

REMIS

CEMS1(D042A)

ATLASSII+MRP(MC)

MUMMS-SS10

SASSYTMS

MUMMS-SS06

TDMS

CAEMS

HMIS

EMACSMEDALS

TMPODS

DAISYFAS

DISMS

DSS

MISILCISIL

SPBS-RSDS AFMIS

SARSS-2AC/2B

CCSS

MTMS JCALS

SARSS-1SAAS-MODERS

SETS

JEDMICS

ATIS(16BIT)

ATIS(32BIT)

MCA

MSPECS

WARRS

IMWRP(D035A)

DMMSS(G005M)

OLVIMS

REMIS

CE-CM(D042E)

CEMS1(D042A)

MUMMS-SS06

ATLASSII+TMS

MUMMS-SS10

MRP(MC)TDMS

SASSY

CAEMS

DSS

DAISYEMACS

TMPODS

DISMSMEDALS

FAS

HMIS

CISILMISIL

COMPASS

MTMSSPBS-R SDS

TC-ACCISAMS(MTMC)

SARSS-2AC/2B

SARSS-1

SAAS-MODAALPS TC-AIMSII

MRDB

ERS

AFMIS

CMOS

LOGMODCALM

IMWRP(D035A)

WSMIS-ETADS

(O132A)WARRS

ETADS

CEMS1(D042A)

TMS

ATLASSII+

CAEMS

MRP(MC)

MUMMS-SS06

MUMMS-

SS10

DAISY

HMIS FAS

DISMS

DSS

GTN

WPS IBS

TOPS

JFAST

CISILMISIL

SAAS-MOD

AFMISERS AMS(MTMC)

TC-ACCISMTMS

AALPS

SARSS-1

COMPASSSARSS-2AC/2BTC-AIMSII

SDS

MRDB

SPBS-R

ARMY

NAVY

AIR FORCE

(USAF)

MARINE CORPS

(USMC)

DLA

TRANSCOM

OTHER

PLAN SOURCE MAKE DELIVER RETURN ENABLE

Pla

n S

upply

Chai

n

Pla

n S

ourc

e

Pla

n M

ake

Pla

n D

eliv

er

Pla

n R

eturn

Sourc

e Sto

cked

Pro

duct

Sourc

e M

ake-

to-O

rder

Pro

duct

Sourc

e Engin

eer-

to-O

rder

Pro

duct

Mak

e-to

-Sto

ck

Mak

e-to

-Ord

er

Engin

eer-

to-O

rder

Del

iver

Sto

cked

Pro

duct

Del

iver

M

ake-

to-O

rder

Pro

duct

Del

iver

Engin

eer-

to-O

rder

Pro

duct

Ret

urn

Def

ective

Pro

duct

Ret

urn

MR

O

Pro

duct

Ret

urn

Exc

ess

Pro

duct

Enab

le P

lan

Enab

le S

ourc

e

Enab

le M

ake

Enab

le D

eliv

er

Enab

le R

eturn

DoD ENTERPRISE LOGISTICSOperational Activity to System Function Traceability Matrix (SV-5)

NOTE: The data displayed in thisdiagram is collected from the LSM'sFuture Logistics Enterprise OV-5.

= System with Operational

to System Process Mapping

= System with Operational

to System Activity Mapping

www.EWSolutions.com



Distributed Meta Data Architecture (DMDA)

End User -

Reporting Tool

(e.g. Data

Shopper, Cognos,

Crystal Reports)

COI Data

Champion

NavyDLA/DSS

Global Meta Data

Public Meta Data

Private Meta DataOther

Repositories

Air force

Meta Data Sources

Global Data

Champion

Logistics Domain

Global Repository

DOD

Meta Data

Registry

Msg/Trans

Broker

Rules

Engine

Army Marines

Weapons Platforms

Suppliers

Other Domains

(Acquisition)

www.EWSolutions.com



Summary

Plan Your Enterprise Around the “To Be Business

Processes” not your “As Is” (80-20 Rule)

Use Commercial Processes and “COTS” Products

Data Strategy is the Key to Data Interoperability

Across the Enterprise

No Meta Data Management, No Data Strategy

Compliance is an “On-Going Process”

Your Business Processes Should Not Be Unique


Information IntegrationWorld Class Solutions Award

Data Management



www.EWSolutions.com



Questions

DAMA International Webinar: 10 Keys to World-Class Metadata Management20150616 meta data dataversity...

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Transcript of DAMA International Webinar: 10 Keys to World-Class Metadata Management20150616 meta data dataversity...