Dave Smith has been working with SAS for over 30 years, first as a customer and then since 1999 at SAS Institute. He has worked in many sectors including pharmaceuticals, academia, banking, insurance, retail, manufacturing, and government. He has a passion for delivering value for customers, ensuring that their projects are designed to succeed. His particular area of expertise is in Data Management, with a focus upon Data Governance and Data Quality.
I was recently told that an organization had tried to implement AI for forecasting in supply chain but had failed due to poor data. This got me thinking about exactly what the impacts of poor data would be. And whether the approaches I had applied elsewhere could help. It's probably
Predictive models are a critical component for automated and augmented decision making. As this deployment pattern becomes more widely adopted, two competing priorities emerge. How can we deliver more models faster while being certain of accurate and consistent performance? The key to solving this dilemma is in the automated testing
In just a few short months the European General Data Protection Regulation becomes enforceable. This regulation enshrines in law the rights of EU citizens to have their personal data treated in accordance with their wishes. The regulation applies to any organisation which is processing EU citizens’ data, and the UK
