In my 'Getting to Grips' series of articles I try to cut the hype and show my readers what is important before plunging headlong into extracting information and new insights from an organization's data.
This blog will point out the subtle difference between Data Governance and Master Data Management while underlying the noteworthy aspects of each.
It is increasingly important that organizations that have a large amount of data need to establish data governance which must precede master data management. Wayne Eckerson of b-eye-network.com says;
”Most business executives don't perceive data as a vital corporate asset until they've been badly burned by poor quality data... Since risk is virtually invisible until something bad happens, this is why selling a data strategy is so hard to do”.
Although there is allot of overlap between the two, master data management is largely about ensuring data quality especially where there are multiple departments using the same data or in the situation of acquisitions and mergers. Master data management therefore is more like an extension of data governance and a project. Master data management will be a complete waste of money if data governance has not been established first with proper controls and standardization of data.
A key point about data governance is that it requires a C-suite executive in charge of a dedicated data management department for the entire corporation, that is to say a Chief Data Management Officer. Wayne Eckerson (2011) of b-eye-network.com, points out that data governance has to be set in motion for sound business reasons and therefore should not be an IT project. Rob DuMoulin of Hubdesignmagazine.com, would say that organizations thinking of data governance need to appoint dedicated staff rather than assigning the role to the IT department who instead should act as the librarian for the data management staff.
In addition one should establish a data governance committee, data owners, and data stewards. Data owners are senior management who take charge of a particular subset of the data such as, ‘Customer data’, ‘Product data’ or ‘Financial data’. Data owners are responsible for the accuracy and completeness of data while the data stewards are entrusted to maintain this accuracy and completeness. Data stewards are usually assigned operational responsibility for a subset of the data such as ‘Customer demographics’ and Customer transactions’. S/he will likely be responsible more specifically for agreement on ‘data characteristics’, maintaining ‘data regulations’, documentation on requirement for ‘historical versions of the data’, text definition of ‘business meaning’ to ensure that each data element is unambiguously understood across the enterprise and 'Definition of Service Level Agreement (aka SLA)' including the business criticality prioritization of each database table. Definition of content quality, proactive monitoring of data quality, definition of access rules and formal approval of access to data whether direct or indirect is included in those tasks.
The Governance Council defines the standards and processes to be followed by the data owners, data stewards and librarians. The following video by Jeffrey Scott, shows the importance of Data Governance in an organization.
https://youtu.be/F5SQJh4gY6M
MDM on the other hand usually is needed where there is allot of data overlap and inconsistencies in data management throughout the organization or where a particular department needs to be brought into line with the rest of the organization. DuMoule (2011) states:
”MDM is an information-centric business process to consolidate and manage specific enterprise data that just happens to use technology to assemble, merge, and distribute the data in question. MDM arose from a need to ensure consistency of strategic shared information to improve data quality, accessibility, and security”.
Good data quality will be complete, timely, consistent, valid, have integrity and be accurate.
However where a MDM initiative is started it is important that defined global controls should be finalized and introduced early into the process. In many ways an organizations data owners and stewards are the real customers in a MDM initiative as the results should make for a more manageable process and as such they are always the drivers of policy and need to be committed to the initiative otherwise it will likely fail. In addition as Wayne Eckerson says; “There has been a lot more innovation in technology than processes. So, today, organizations should strive to arm their data management teams with the proper tool for every task”.
Components of Data Governance and Master Data Management Strategy - http://www.kwezisoftware.co.za/MasterDataManagement.php
Master Data is information about customers, suppliers, partners, products, materials, employees, accounts and more, Master Data is at the heart of every business transaction, application and decision therefore Data Governance and Master Data Management go hand in hand and should be developed together wherever data management is important in an organization and then the strategy should be monitored and tweaked as conditions change and the business develops into the future.
Page references: • http://www.b-eye-network.com/blogs/eckerson/archives/2011/05/keys_to_creatin.php# on 10-04-2015 • And http://hubdesignsmagazine.com/2011/10/13/where-data-governance-stops-and-master-data-management-starts/ on 10-04-2015