Nigel Turner
Global Data Strategy
[Please note that this half day workshop is delivered as a virtual training and allows adequate interaction!]
In our digital age many organisations seek to become data driven and are investing heavily in new technologies to make it happen. But this investment will not deliver its promised riches unless the data itself on which it depends is fit for purpose and of the required quality. Having accurate, complete and reliable data is a ‘must have’ for any digital business or organisation.
One of the oldest maxims in data management is ‘Garbage in, Garbage Out’. If data is of poor quality other data management disciplines can never fulfil their promise. Business Intelligence initiatives will generate information and outcomes that cannot be relied on, leading to poor decision making. Master Data Management will fail to deliver a single, integrated view of a customer or product, and so on.
More importantly, poor data quality has a significant adverse impact on the business or organisation itself. When data is not fit for business purpose, revenue is lost, unnecessary costs are incurred, productivity and efficiency suffer, and the risks of breaching regulatory and legal requirements (for instance with GDPR) are greatly increased.
Despite this, the reality is that data quality in most organisations remains poor, and often very poor. A study conducted by The Harvard Business Review and MIT in 2017 found that fully 97% of records surveyed in key organisational databases contained critical data quality errors.[1] Identifying and tackling these issues is a top priority for any organisation which seeks to extract the maximum value from its data assets.
The Workshop
In this half-day workshop Nigel Turner will answer a number of fundamental questions that need to be addressed to deliver fit for purpose data quality. These include:
The workshop will help you answer these questions by taking you through a five step approach to identify, deliver and sustain data quality improvement. The five steps of Assess, Baseline, Converge, Develop & Evaluate (A2E) provide a simple framework and methodology to enable data quality to be tackled in a systematic and repeatable way. The session will also contain practical exercises to help participants apply A2E before doing it for real back in their own organisations.
Learning Objectives
Who is it for?
Payment by credit card is also available. Please mention this in the Comment-field upon registration and find further instructions for credit card payment on our customer service page.
[1] “Only 3% of Companies’ Data Meets Basic Quality Standards”, Tadhg Nagle, Thomas C. Redman & David Sammon, Harvard Business Review, 11 September 2017
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