Unlock the Value of Big Data With Master Data Management

August 20, 2015
Contributor: Rob van der Meulen

CIOs and Chief Data Officers can implement four initiatives for better data management.

A mass of unstructured data can be more burden than benefit. Many organizations struggle to get their house in order and turn data into dollars.

“The more data you have, the more crucial it is to better manage your master data and improve the maturity of your master data management (MDM) program,” said Saul Judah, research director at Gartner. “Existing approaches to data management are, in many cases, insufficient to accommodate big data sources on an enterprise scale. Collecting data without managing it properly also creates ongoing costs as well as regulatory and compliance risks.”

More importantly, immature MDM limits an organization’s ability to extract valuable insights form data. CIOs and Chief Data Officers who oversee big data initiatives need to consider the following steps:


Update Information Strategy and Architecture

Many organizations have had success leveraging big data insight around specific business operations, but typically it’s limited to a single business unit or use case. Few firms have explored how to make big data insights actionable across the entire organization, by linking big data sources with trusted master data.

For example, many marketing organizations use data from social sources — such as Twitter and Facebook — to inform their campaigns, but they don’t reconcile this with trusted data in customer/prospect repositories that are used by customer services or sales. This can lead to incoherent customer communication that can actually undermine the sales or customer service process.


Become More Agile

Effective use of big data requires a mixture of old and new technologies and practices. This necessitates an agile approach that applies a bimodal IT framework to information governance (see “Why Digital Business Needs Bimodal IT”). MDM traditionally uses a Mode 1 approach which is policy-driven and approval-based. Big data typically uses a Mode 2 approach with little or no predefined processes or controls. Tactical and exploratory initiatives are much better suited to the “faster” Mode 2.


Move to Limit Risk Exposure

When an organization executes actions based on information sources outside the curation of MDM — as is the case in many big data implementations — exposure to certain types of business risk increases. Factors such as poor data quality, loss of critical information, and access to unauthorized information become more likely. Gartner recommends appointing a lead information steward role in relevant business units to assist in creating and executing risk controls with regards to data use in business operations.


Identify Medium and Long-Term Requirements

The scale of challenges that face organizations and their information infrastructure are rapidly shifting. This doesn’t necessarily mean that current MDM implementations are no longer fit for purpose. Immediate assessment and planning in light of new and future requirements is, however, essential to ensure that both investment and hiring keep up with the information demands of digital business. Data modelling, quality management, integration and synchronization are all areas that may soon require additional tools and skills for a business to remain competitive.

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