Blog

Read up on our technical blogs, covering technology & AI, data management and data quality, and insights from the market.

What is driving the need for Data Quality Metrics in Retail Banking?

marathon, running, runner

Retail Banking Part 1 – Marathons present a titanic challenge that has long dominated the human psyche: the will to finish, to get over the line, to win. Whether in-person or virtual, the London Marathon is no different! In previous years, the official app has contained a feature to help friends, family and supporters locate […]

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Explainable AI with Dr. Fiona Browne

explanin

The AI team at Datactics is building explainability from the ground up and demonstrating the “why and how” behind predictive models for client projects. Matt Flenley prepared to open his brains to a rapid education session from Dr Fiona Browne and Kaixi Yang. One of the most hotly debated tech topics of 2020 concerns model

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Fundamentals of AI ethics with Dr. Fiona Browne

Logic

AI Ethics Dr Fiona Browne heads Datactics’ four-strong AI team building explainable AI solutions. Here, Fiona delves into the thorny topic of ethics, the centrepiece of any AI expedition. More specifically,  the post goes into how to ensure that the potentially negative ethical impacts of AI do not outweigh the positives it can deliver across

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Self-Service Data Quality for DataOps

Vision

At the recent A-Team Data Management Summit Virtual, Datactics CEO Stuart Harvey delivered a keynote on “Self-Service Data Quality for DataOps – Why it’s the next big thing in financial services.” The keynote (available here) can be read below, with slides from the keynote included for reference. Should you wish to discuss the subject with

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Unlocking Data Quality and Value to Power Innovation & Insight

At last week’s Virtual Data Management Summit, the A-Team’s CEO Angela Wilbraham sat down for a Q&A on all things data quality and unlocking data value with our Head of Sales Kieran Seaward. Topics covered in this interview are: – The biggest issues in data management right now (0:31) – Why data quality is such

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Beyond data prep – Whitepaper SSDQ

As featured in the recent A-Team webinar, we’ve been strong advocates of a self-service approach to data quality (SSDQ), especially when it comes to regulated data types and wide-ranging demands on a firm’s data assets. This whitepaper SSDQ, authored by our CTO Alex Brown, goes deeper into the reasons why this approach is so much

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Best Practices For Creating a Data Quality Framework

Chief Technology Officer, Alex Brown featured as a panellist in Data Management Insight’s webinar discussing the best practices for creating a data quality framework within your organisation.  What is the problem? A-Team Insight outlines that ‘bad data affects time, cost, customer service, cripples decision making and reduces firms’ ability to manage data and comply with

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“We are just finishing up our first full week of working from home” – Week 1: DaveOps

Like most, here at Datactics, we are just finishing up our first full week of ‘Working from home’. In line with government advice, we made the decision to close our office in Belfast and to port the entire workforce over to working from home last weekend. As the guy in charge of making sure everything

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Why you should read the European Banking Authority report on AI and Big Data

You might have missed this highly informative report from the European Banking Authority (EBA)  – because the title didn’t contain the popular buzzwords of Artificial Intelligence – AI or Machine Learning – ML (nor does the front cover have a picture of a robot!). But for anyone who is trying to understand the challenges ahead for AI and

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Easy Ideas To Get Your People Excited About Data Quality

With Statista.com reporting that 59 zetabytes of data has been captured, created, copied and consumed worldwide since 2010, it’s easy to see the problems that arise when even a fraction of this is incorrect.  The chaos that can – and does – arise can seem totally insurmountable, creating a problem that’s as unappealing to solve as it is difficult. It can also make

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