Three tips for laying the ground work for machine learning
data quality, hyperscale and Python – the foundation of machine learning
Why is data being taken more seriously?
I some times joke to my customers and prospects that I have been doing data since long before it was fashionable. One of the challenges of working in a relatively small market is that one tends to revolve through the same doors – having got a “not now” response i tend to come back six…
Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models
Poor data quality is the single biggest contributor to the poor performance of customer risk-rating models. Incorrect know-your-customer (KYC) information, missing information on company suppliers, and erroneous business descriptions impair the effectiveness of screening tools and needlessly raise the workload of investigation teams. In many institutions, over half the cases reviewed have been labeled high risk simply due to poor data quality – McKinsey
Data Governance, Customer Experience and a tale of data in the insurance industry
Digital transformation is not a technology problem, but a business imperative, and insurers need to begin to look at their data as a business asset and not simply the domain of the IT department
How does data quality underpin success in a changing and disrupted banking environment?
To remain competitive, traditional banks must be able to make intelligent decisions on how best to serve their customers – and the crux of intelligent decision-making is quality data.
Integrating data quality and data governance
For someone that’s been preaching data governance and data quality for more than fifteen years, its been fascinating to see how these two topics have been gaining traction in the last few years. A few week’s back I touched on the difference between data governance and data quality – governance is about “what” and “who”,…
Creating a single customer view – harder than you think
But to business, having customer data consolidated into a master data management application often leaves a bad taste.
