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MDM Implementation Styles – Learn the Differences Between Them and Which Style Works Best for Your Organization

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Our Presenters

Kerry Young VP & General Manager

Ramesh Prabhala Founder and CEO

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Introducing EnterWorks

Empowering Business & IT Users for over 21 years

All-in-one platform for MDM, PIM, and DAM

Only Solution that is a Leader on both the Forrester PIM and MDM Waves

Highest customer satisfaction marks on industry analyst reports

Industry expertise: distributors, manufacturers, retail, hospitality, service companies, and member / buying groups

Strong Global SI & Technology partnerships

Business Mission Enable Our Customer’s Growth,

Efficiency and Differentiation through Exceptional Competency in Data

as Enabled by our MDM Technologies

Complexity Mastered

Master Shared and Application Data for

Business Model Agility

Discrete Views of Everything

Provide a Central View of Data Across Enterprise

Networks

Differentiated Experiences

Leverage Multiple Domains for Combinatorial Precision

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A Division of

51% LICENSES

OUTSIDE U.S.

2,200+ GLOBAL

CUSTOMERS

75+ COUNTRIES

200+ NEW ACCOUNTS

ANNUALLY

22 OF SAP’S TOP 25

CUSTOMERS

48 NET PROMOTER

SCORE

Auto Apparel Oil & Gas Food &

Beverage Consumer Products Retail Pharma Chemical Entertainment

MDM Implementation Styles Learn the Differences Between Them and Which Style Works Best for Your Organization

Certified Partner An There are hidden treasures in every data, we find them!

QUESTIONS PRIOR TO IMPLEMENTATION An Enterworks Certified Partner

Questions prior to implementation

Is there something we should know prior to implementing besides data model,

WF’s, BR’s, integrations etc.?

What homework should we do?

Should we jump straight into implementation?

Lets talk agile, waterfall etc. immediately?

THE BASICS An Enterworks Certified Partner

The basics

What is Master Data? Master Data = f(a1n) + f(a2n)

Where a1n = one or more identifier attributes

And a2n = one or more describer attributes

What is Master Data Management?

Improve data quality

Create a single source of truth or

golden record

Enrich data

Functional

Cut costs

Manage risk

Reduce labor cost

Improved productivity

Accelerate go-to-market

Process efficiency

Improved decision making

Benefits

BEFORE YOU BEGIN… An Enterworks Certified Partner

Before you begin…

Remember MDM is…

Know your customers business

What type of business What do they sell Their business model

Of the Business For the Business By the IT

IMPLEMENTATION STYLES An Enterworks Certified Partner

Architecture - 1: REGISTRY

• De-duplication of records

• Employs data cleansing – match/merge

• Data is not sent back to source systems

• Governance required to ensure reliable golden record

Architecture - 1: REGISTRY

Match/Merge Concepts

Architecture - 2: CONSOLIDATION

• Data consolidated into the MDM hub from multiple sources

• Data is cleansed to create single source of truth, high data quality system

• Mainly used as a high quality EDW for reporting and analytical purposes

Architecture - 3: COEXISTENCE

• Master records stored in MDM and updated to source systems

• Updates to Master Data within MDM and source systems

• Data must be cleansed prior to importing into MDM, continuous synchronization

• Single version of truth between MDM and source systems

Architecture - 4: CENTRALIZED

• All Master Data is managed in MDM, sole provider of source of truth

• Master Data is authored in MDM, not in source systems

• All systems subscribe to the MDM hub for Master Data

UNVEILING THE NEW PATTERN… An Enterworks Certified Partner

MDM Evolution Story

Architecture - 5: E-SYNDICATION

• Regardless of where data is authored the driver is the eCommerce destinations

• Data from MDM is syndicated to online channels via a API/gateway

• Between MDM and API hub, channel based rules and hierarchies will be orchestrated

Architecture - 5: E-SYNDICATION

Reasons for popularity

eCommerce is becoming a pivotal

sales channel

Business model transforming from B-B to B-C

Current crisis and future

ones will accelerate B-C

online sales

Architecture - 5: E-SYNDICATION

U.S. ecommerce penetration

Online and in-store sales as a % of total retail* spend, 2010-2019

2019

$602B e-com of $3,763 Billion of total retail

2020

Online sales have increased 25% on average for daily

sales March 13-15 compared with average daily sales

March 1-11

Architecture - 5: E-SYNDICATION

Features

Single to multiple online channel sales Some data quality can be compromised –

for speed!

Analytics will attain massive significance MDM’s evolve to support transformation – channel

selection, hierarchies, content etc.

DATA MODEL PATTERNS An Enterworks Certified Partner

Data Model Patterns

Three primary item level patterns

Parent

Level-1

Variant

Level-2

Variant

Parent

Level-1

Variant

Single Item

3 level parent child 2 level parent child Single entity

Examples • Apparel

• Footwear

Examples • Bikes

• Faucets

Examples • Welding machine

• Books

Data Model Patterns

Model your item level relationships

• Kit/package

• Cross-sell, up-sell

• Vendor to item

Always use the staging (WIP) and

production container pattern

Keep your workflows simple – design per

the industry/business pattern

Other important considerations…

MDM/PIM

Rollouts

50

Fortune 500

Consulting Experience

25+

Avg. Years of

Data Architects

Experience

8

Customer

Satisfaction

100% Verticals

10+

Continents

of Operation

3

IntelliTide at a glance

Master Data

Management

Services

Hosting &

Managed

Services

Analytics &

Business

Intelligence eCommerce

Syndication

Enterprise

Integration

Services

Digital

Transformation

What IntelliTide can do for you

Presented by

IntelliTide Corp.

hello@intellitide.com

832-899-5820

Certified Partner An

Questions?

ENTERWORKS MDM VIRTUAL CONFERENCE If you missed any previous sessions, the following sessions are available for playback.

enterworks.com/virtual-conference-mdm/

Week 1 Sessions featured by Bill Ferguson of IDEA, Marc Alvarez of Thomson Reuters, and Natalie Scott of Gourmet Foods International Week 2 Sessions featured by Martin Schmidler of UniPro, Jon Varo of Fender, and Ingryd Hernandez of US Foods Week 3 Sessions featured by Michael Ayanwale and Eric Gilboe of Amplifi, Christopher Holley of Productsup, and Ramesh Prabhala, Satheesh Ramachandran and Kartik Nanda of IntelliTide Week 4 Sessions featured by Jean Bordelon and Dean Rutter of Bounteous, Scott Rompala of DataCatalyst, and Octavio Perales of Intershop Week 5 Sessions featured by Rusty DiNicola of Pivotree, Allyson Taft and Libryia Jones of Amplifi, and Christopher Holley and Emeka Nwosu of Productsup Week 6 Sessions featured by Adam Sigg and Steve Ruff of Infoverity, Rusty DiNicola of Pivotree, and Ramesh Prabhala of IntelliTide