Data Governance must drive Big Data strategy

Data Governance trumps Big Data and this can demonstrated with the recent National Security Agency (NSA) extradition debacle.

September 10, 2013

By Gary Allemann, MD of Master Data Management

Data Governance trumps Big Data and this can demonstrated with the recent National Security Agency (NSA) extradition debacle. Briefly, Edward Snowden is an American computer specialist who worked for the Central Intelligence Agency (CIA) and NSA. Snowden leaked details of the Unites States government’s Big Data surveillance programmes to the press, before fleeing via Hong Kong to Moscow, where he has currently been granted asylum.

So where does Data Governance come into play? Snowden’s escape from Hong Kong in June was aided by simple data quality errors in the extradition request put in by the United States government. According to Hong Kong officials, the documents the NSA submitted for Snowden’s arrest contained incorrect details and his passport number was omitted. The time it took to clarify these errors gave Snowden the opportunity he needed to board the flight for Moscow.

It is ironic that an organisation that is at the forefront of Big Data analytics could fail to deliver accurate and complete data for a seemingly simple task. Yet, all too often, new technologies and hype take precedence over basic business improvement.

Surely, from a Data Governance perspective, ensuring accurate and complete identification of staff with access to sensitive information should be a priority? This further proves how poor data quality breaks business processes and in this case, with highly embarrassing results. If the correct information was provided to the Hong Kong officials, Snowden could have been arrested.

Many data governance programmes suffer from being too complex and, largely, irrelevant. Getting the basics right, with our Lean Data Governance approach, is essential to minimising risk and maximising the value of information. Lean Data Governance is the optimisation of classic data governance and delivers a robust framework and standards for sustainable change, process and information mapping, and review to increase efficiency, functionality for tools and technology and value to the internal customer. By adopting a lean approach to data governance, businesses can eliminate wasteful data governance activities and further promote efficiencies.

Lean Data Governance can not only save embarrassment but also provide companies with the ability to take a systematic approach to identify and eliminate wasteful information through continuous improvement. This, in turn, allows organisations to improve all aspects of the organisations such as service management, and further ensure better productivity and efficiency within the organisation. A Lean Approach will result in improved quality control, effective management and increased competitiveness.

Learn more about this on 12 September 2013 when Trillium Software will be hosting a webinar to discuss data governance and data quality in a Big Data world. Join data quality experts, Nigel Turner and Ed Wrazen as discuss The Data Quality Dimension. To register, visit http://response.trilliumsoftware.com/DQBigDataAnalytics2.