Comparing algorithms – how to decide which one is better?

by Matthew Harris on 17 October, 2017

Evaluating Matching When implementing an MDM solution, or any matching algorithm, you may be replacing a previous matching algorithm. You will need to be really sure that the new algorithm will be an improvement on the old one. However, knowing which algorithm is better, or worse, is a challenging...

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How to evaluate the performance of matching algorithms – top tips

by Matthew Harris on 19 September, 2017

It can be difficult to evaluate the performance of matching algorithms. However there are several ways to determine how accurate they are and the actionable insight that could be gained by applying them to the data related to your business challenges. In a technical sense, there are 2, and only...

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How to optimise probabilistic matching performance on massive data sets

by Matthew Harris on 13 September, 2017

Within a probabilistic matching* engine (PME) there are 3 key stages: Standardization Candidate Selection Comparison *For an explanation of probabilistic matching see my previous blog here. These 3 key stages, when implemented together, allow for very efficient performance on massive data sets, both in terms of speed of matching...

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Why probabilistic matching is not a black box

by Matthew Harris on 27 July, 2017

What is probabilistic matching and who cares? If you are a developer then you probably (!) already know that it is possible to trace back everything that happens in a probabilistic algorithm and why it happens. If you are a business lead interested in business outcomes only then perhaps...

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A six-step action plan for EU GDPR consent mastering

by Jason Edge on 20 March, 2017

Why GDPR is relevant to all of us All EU citizens, as data subjects, have a vested interest in industry getting GDPR compliance right because it can impact our trust in the organisations who hold and process our most personal information. If you are a Data Controller or Data...

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