Gary Allemann
Gary Allemann is passionate about Information Communication Technology (ICT) and more specifically data quality, data management and data governance. His introduction to the field of ICT was cemented with the completion of a Bachelor of Science degree (Hons) at Rhodes University which saw him enter the workplace in 1993 where he secured a position at First National Bank as a programmer. In 1996, Gary moved on to Dimension Data where he began to be more intimately involved with master data management as a Dimension Data CRM specialist. In 2001, Gary moved onto ILC Lerumo, a company that provides asset management and logistics consulting services to the defence and manufacturing industries, as a sales and marketing manager. In 2003, armed with 10 years’ experience, Gary formed Master Data Management, a business that provides specialist solutions for data governance, data quality, data integration and MDM. Leveraging the international expertise of its vendors including Harte-Hanks Trillium Software and Global Data Excellence, MDM has provided solutions for a range of clients in financial services, government, mining and telecommunications.
Website URL: http://www.masterdata.co.za
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Oscar Pistorius trial shows the importance of data management
Wednesday, 26 March 2014 17:22 Published in Analytics & BI
Oscar Pistorius’ trial has been dubbed the ‘trial of the century’ and is receiving a lot of media attention. A young woman has died, under tragic circumstances and the fate of her killer lies in the evidence, the prosecutions ability to create a picture from that evidence, and the ability of the defence to create reasonable doubt. The same concept can be applied to data management within an organisation.
Typically, we think of data as information captured in a database. The evidence used in this trial serves as a reminder that data is simply raw information and can take many forms.
A court case presents evidence - data - and draws conclusions based on this data. This can be likened to the decision-making process of any business. Ironically, in a court case, the prosecution and the defence are each pushing for diametrically opposed conclusions – innocence or guilt, using the same data.
While the merits of the case are for the court to decide, what has been interesting is the legal process itself, and how the opposing counsel is applying data management principles to support their desired outcomes.
Indeed, the outcome of this case could depend on the data management principles of data governance and data quality.
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- Oscar Pistorius
- Oscar Pistorius trial
- Oscar Pistorius trial translator
- Interpretation
- data management
- data governance
- data quality
Can you account for the value of data in your business?
Tuesday, 22 October 2013 11:43 Published in Analytics & BI
While IT staff talk about 'data as an asset' rather glibly in the boardroom, the value of digital information in an organisation is interpreted quite differently from the accounting department's perspective. Traditionally data could be quantified in terms of traditional storage, backup, data recovery and in-house management costs, but there are questions abound about its actual recognition as a value asset in the field of accounting. How do you manage data from a tax perspective? How do you measure the value of data throughout its useful life cycle? Importantly, how do you credibly depreciate these data assets on the balance sheet?
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- data value
- tax
- information asset
- accounting standards
Data integration and migration challenges arise every time an organisation moves to a new data system, or wishes to combine multiple data systems, either internally or as a result of a merger. This is a significant undertaking, which, if it fails to meet expectations, inhibits a business’ ability to function effectively. Yet, surveys indicate that more than 80% of all data integration projects fail. There are several reasons for this failure, but the most commonly cited issue is a lack of understanding of the extent and nature of problems that were to be experienced within the data itself. Data quality is critical to the success of any data integration and migration initiative, and organisations leave this aspect to the last minute at their peril.
- data migration
- data integration
- data quality
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