Trends in Master Data Management

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by Paul Williams

Data is continuing its seemingly perpetual growth and therefore Master Data Management must also continue to grow in importance to organizations interested in overall data quality, whether driven by some from of compliance requirement or a desire to improve operational efficiency. Defining and organizing the master data of any enterprise is usually a highly important component of any Data Governance program.

This article looks at some recent trends in products and concepts related to the practice of Master Data Management.

Global IDs’ Solutions to Facilitate the MDM Process

The MDM Track at the recent Enterprise Data World 2012 conference featured sponsorship by Global IDs. Founded in 2001 to address problems related to large scale information integration, Global IDs developed the first commercially available data integration software using smart mobile agents for large-scale data tasks.

In addition to software suites used for the management of enterprise metadata in data mapping and profiling, the rest of Global IDs product line is focused on MDM, namely the Master Data Governance Suite, as well as the Master Data Integration Suite.

The Master Data Governance Suite features a collection of specialized applications used for the automation of master data analysis within any large enterprise. Global IDs’ systematic approach promises to “create transparency within the data environment, create quality insurance monitors on the data environment, and establish a master data governance portal for data stewards.”

Considering the significant number of databases at most larger organizations, combined with the advent of Big Data and its exponential data growth, tools like the Master Data Governance Suite become highly important when dealing with master data, especially considering the suite’s scalability. The suite also provides an automated view of an enterprise’s data inventory, recognizes important business identifiers, and handles cross-enterprise business data distribution.  All these help to ensure data quality accountability and data compliance.

Global IDs’ Master Data Integration Suite assists an enterprise with the automated integration of core data assets. This suite’s set of applications includes software that analyzes the organization’s redundant data, thus helping to improve costs in the process. It also includes functionality that auto generates mapping for corporate data assets, along with creating hubs facilitating access to the integrated data.

Like the Master Data Governance Suite, the integration suite is able to work in a mostly automated manner, providing excellent scalability.  This all occurs as a highly systematic and repeatable process. Anyone looking at a MDM solution for their organizational needs should consider Global IDs product line.

DataFlux’s Platforms for Master Data Management and Governance

DataFlux is a subsidiary of SAS and is known for their MDM-focused product line. Of particular importance is their Data Management Platform, a complete solution for any enterprise’s data management needs.

The Data Management Platform provides enterprises with the ability to perform tasks related to Master Data Management and Data Governance. The software suite features standardized web-based and smart-client interfaces for data management, as well as data governance functionality accessed through a single platform.

Users are able to use the platform to define and manage a number of data management tasks, including data integration and merging, customer and product information validation, metadata management, and compliance and data quality monitoring. In short, this is a fully functional data management product suite.

DataFlux’s qMDM product leverages the Data Management Platform suite (namely its data quality, data integration, and data governance framework) to create a focused solution for Master Data Management. qMDM sports a configurable data hub, providing the user with a singular view of an enterprise’s master data.

Implementing qMDM is generally easy, as the standards-compliant, platform-agnostic software plays nicely with most IT environments. The suite features a multi-domain data model, metadata discovery, data stewardship of the master data hub, data lifecycle management, and a full reporting suite.

DataFlux’s qMDM and their Data Management Platform are both worthy products well-suited for any Master Data Management practice.

David Loshin Gives an Introduction to Master Data Management

Those still unfamiliar with the concepts behind Master Date Management would do well to check out the published work of David Loshin. Loshin is the President of the data management consulting firm, Knowledge Integrity, Inc., and is highly regarded as a thought leader in the data management industry.

Loshin’s 2008 book, Master Data and Master Data Management, serves as a useful introduction to the concepts surrounding MDM. Publisher Morgan Kaufmann released the first chapter of the book as a free download for interested readers. In addition to teaching about master data and its management, Loshin’s book also functions nicely as a “bible” referencing the best practices for MDM.

In a morning tutorial at Enterprise Data World 2012, Loshin provided an effective introduction to Master Data Management. The robust tutorial stressed the importance of interoperability and data integration in any enterprise whose business applications and processes require the sharing of data.

After defining “Master Data” and “Master Data Management” as terms, Loshin covered the relevance of the practice of MDM in helping organizations improve overall data quality and reduce business process errors. Coverage of related concepts like Data Governance, Master Data modeling, risks, challenges, and enterprise architecture considerations combined to provide a full overview of Master Data Management as a practice. Looks to MDM 3.0 to Maintain Its Advantage earned a reputation as a leader in the CRM industry with their role as a progenitor in the use of Business Intelligence in leveraging the customer relationship. Recently, the advent of Big Data and analytics caused the company to take another look at Master Data Management and how the practice could be improved to ensure’s competitive advantages in its business sector. Enter MDM 2.0 and 3.0.

Mehmet Orun is a Director of Data Quality at business unit, He is well known in the data management community as an evangelist for the evolution of Master Data Management as it grows in importance in this age of Social Media-driven information. Orun developed many of his MDM concepts in a data management role for the biotechnology firm, Genentech.

In the mid 2000s, MDM began to evolve as a practice in the enterprise, Genentech’s need for an overall architecture to better integrate IT applications and BI became apparent. Improved data stewardship was another desire. Orun encapsulated these evolved practices and data architecture as MDM 2.0, presenting his findings at an earlier Enterprise Data World.

Orun recently moved into his role at, and the development of MDM 3.0 soon followed. Driven by Social Media data, MDM 3.0 emphasizes flexibility over governance, and newer concepts like data virtualization and mobilization; Big Data and Cloud Computing all play important roles.

A key point in MDM 3.0 is the use of agile data architectures that ensure the latest data is available for consumption. This data can be from unstructured, external, and web-based sources through a data virtualization portal as well as from traditional stores. Flexibility is vital.

Any data-dependent firm looking to compete in today’s fast-changing marketplace needs to look closely at the best practices detailed in Orun’s MDM 2.0 and 3.0 frameworks to ensure said firm’s competitive advantage.

Eli Lilly Sees Benefit from MDM Implementation

Pharmaceutical company Eli Lilly is experienced with Master Data Management in its Research and Development division, as well as in the overall enterprise. The company feels MDM is less of a project than an “enabling capability” that is nurtured over time. From using an external MDM tool in the early 2000s to their current E-MDM capability, the data management practice has evolved at Lilly over the past decade. Christine Denney, a data management professional at Lilly and a DATAVERSITY blogger, presented her company’s experiences with an evolving Master Data Management capability at Enterprise Data World 2012.

As the MDM process matured, setting up a formalized governance practice became vital. The governance team included cross-domain stewardship and cross-domain technical resources. Ultimately, this team was part of a process creating a reusable architecture pattern for Master Data Management, allowing Lilly to usher in a corporate environment where data is shared across the enterprise as opposed to just within the individual divisions.

Denney describes the transformation as moving from the “little e” to the “Big E.” The main deliverable from this matured capability was the 2011 rollout of the company’s internal E-MDM tool. Lilly’s plans for the upcoming years include the development of an enterprise-wide Taxonomy and Ontology.

Master Data Management continues to grow in importance for both data professionals and enterprises. From the latest software products facilitating the management of master data to the latest MDM concepts honed in Fortune 500 companies, these trends are ones to follow for the interested data manager.

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