Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
    car expense data analytics
    Data Analytics for Smarter Vehicle Expense Management
    10 Min Read
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Master Data Management (MDM) – Going Where the Enterprise Data Warehouse has Gone Before
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Warehousing > Master Data Management (MDM) – Going Where the Enterprise Data Warehouse has Gone Before
Business IntelligenceData Warehousing

Master Data Management (MDM) – Going Where the Enterprise Data Warehouse has Gone Before

RickSherman
RickSherman
3 Min Read
SHARE

Word_MDM There is a lot of industry buzz on Master Data Management (MDM). It would appear from this chatter that MDM is a new thing. But if you look under the covers, you’ll see some aspects of MDM that look mighty familiar.

Word_MDM There is a lot of industry buzz on Master Data Management (MDM). It would appear from this chatter that MDM is a new thing. But if you look under the covers, you’ll see some aspects of MDM that look mighty familiar.

The reality is that for many years, whether people realized it or not, the Enterprise Data Warehouse (EDW) has served as the default MDM repository. This happened because the EDW has to reconcile and produce a master list of data for every data subject area that the business needs for performing enterprise analytics. Most of my customers referred to this as reference data management years before the term MDM was coined.

More Read

It’s Just a Little More Disk Space
Customer Service Queues – Fair, Fast or First?
Mr. Jassy, Tear Down This Wall! – a Letter to Amazon’s Web Services
In a Petabyte Age, Is Understanding Passé?
What Big Data Doesn’t Appear to Tell Us, But Actually Does

These subject areas generally include customers, products, suppliers and employees along with variations based on industry. Each subject typically has hierarchical relationships within it (such as products, marketing, and sales territories) that need to be managed.  Again, all this is done to support enterprise analytics.

Naturally, the data for each master data category has to be consistent. In data management terms the process to achieve a master list for each subject is referred to as conforming dimensions. This means as you gather master data from disparate enterprise applications the data-integration process must create one consistent list for reference data such as products, customers and suppliers. This process usually requires creating a surrogate unique key for each master data row and involves de-duping lists. This master list enables enterprise business intelligence and analysis.

The fact that EDWs have served as default MDM solutions means there’s a history there – a history you can learn from. Before you go out and buy an MDM solution it’s important to be sure about what you need to buy.

The history of having the EDW serve as the default MDM solution shows that it has encountered two barriers to success:

  • Too many “master” lists or multiple “single versions of the truth”
  • The assumption that technology would be a silver bullet

See my post next week for an explanation of these two barriers faced by enterprise data warehouses serving as default MDM solutions, and a wrap-up of my thoughts on the subject.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

cybersecurity essentials
Cybersecurity Essentials For Customer-Facing Platforms
Exclusive Infographic IT Security
ai for making lyric videos
How AI Is Revolutionizing Lyric Video Creation
Artificial Intelligence Exclusive
intersection of data and patient care
How Healthcare Careers Are Expanding at the Intersection of Data and Patient Care
Big Data Exclusive
dedicated servers for ai businesses
5 Reasons AI-Driven Business Need Dedicated Servers
Artificial Intelligence Exclusive News

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Left Menu in GA
AnalyticsBusiness IntelligenceData VisualizationDecision ManagementExclusivePredictive AnalyticsStatisticsWeb Analytics

Using TIBCO Spotfire to Analyze Google Analytics Data

5 Min Read
Image
Big DataData Warehousing

How to Solve Data Fragmentation, or Why to Invest in a Distributed Data Warehouse

6 Min Read

Advantages of Artificial Intelligence in Virtual Worlds While we…

1 Min Read
Marketing Potential
Business IntelligenceData ManagementMarketing

3 Indispensable Ways to Reach Your Marketing Potential with Data

12 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?