Paul is Experian Data Quality’s Data Strategy Manager. With a wealth of experience in Data Product Management, Data Strategy, Governance and Privacy; Paul is championing the benefits of strong reference data capabilities and business processes for our clients and our business. Paul is also a leading advocate of Open Data and Transparency; helping organisations and society get the best out of the growing deluge of information.
I recently blogged on the emergence of the IoT (Internet of Things) and how it’s a new front in the battle against poor quality data. This time I wanted to take a two-pronged approach to another emerging trend – machine learning. With this blog, I want to examine whether machine learning can be used to maintain and improve data quality but also look at the risks to machine learning posed by poor quality data.
As a founding member of The Data Literacy Project alongside Qlik, Accenture, Cognizant, Pluralsight and the CIM, Experian is supporting the Data Literacy Project to help organisations, educators and individuals speak the language of data. Today, data literacy is as important as reading and writing, but we're facing a significant skills gap.
In my last blog we looked at the rise of IoT and some of the challenges that organisations are facing around the privacy and security of data. But what about the data itself? Whilst there might be more data out there than ever before, for it to be useful there’s some very important groundwork to be done. Let me explain.
Those of us who’ve been in technology and data for a while know a ‘hype’ when we see one. I’ve personally been through the hype cycles of CRM systems, the Cloud and big data. We’re now seeing more and more in industry and mainstream press about the Internet of Things (IoT) and Blockchain.
I won’t cover the latter in detail (as I, like most people am still trying to understand it!) but will look at how smart fridges, connected cars and pretty much every device you can think of are presenting our societies with huge opportunities but also a major data quality headache.
The pressure on the NHS is widely reported and after an exceptionally difficult winter, the knock-on effects appear to be on-going according to this article. One particular challenge that was widely reported in early January 2018 is the estimated £1bn annual cost to the NHS of ‘no shows’ at GP and hospital appointments.
8 million missed appointments each year, with an average cost to the NHS of £120 each will clearly be putting added financial pressure on services that are already stretched. Whilst the growing use of phone and online services (such as the 111 helpline) can go towards reducing pressure on frontline services, could the NHS be doing more with its data to help cut the cost of ‘no shows’ and reallocate this saving to better use?
I’ve been involved in personal data for my entire professional career – it’s something that I fell into but that I now find fascinating due to the power that data can have to change lives.
I wanted to use this blog to look at something that I’ve certainly been aware of for a long time but is now becoming a much more visible area of data governance namely Data Ethics.
Many of us in the data industry have become familiar with the term Single Customer View (SCV) over the last decade. Those that have worked on an SCV project will have seen how they can improve our data management processes, save on marketing costs or improve your customer experiences.
However, with many SCVs being focussed on just one of those outcomes, there has sometimes been an air of disappointment with the results. Some organisations have even ended up with multiple SCVs for different purposes that don’t agree when there is an urgent need to bring together data for another reason, such as a Data Subject Access Request (DSAR).
Whilst many businesses understand the challenge for more personalised and seamless experiences, they struggle to cope with the growing volumes of data available. It’s predicted that by 2025 the ‘datasphere’ will grow to 163 zettabytes – ten times the 16.1ZB of data generated in 2016. It’s no surprise that less than one in five (19%) say they are unlocking the full potential of their data to improve their relationship with customers.
This torrent of information is causing an ‘infobesity’ problem. Businesses are faced with an information overload. They have so much data, it can be overwhelming to know what to do with it all. How can they turn that data into useful information, unlocking its value and delivering better outcomes for their customers?
We recently brought you the first in a two-part series of blogs about the changes now in place to data processing rules under the new GDPR and how organisations need to review the basis and permissions that govern their processing of personal data. In this second instalment, I’ll be diving into consent in more detail and look at how the combination of sound data management practises and cutting edge technology could help your organisation towards a Permissions Strategy to support the GDPR.
As with the previous blog in this series, there is going to be some useful content for everyone involved in personal data but you may find that some of this is most applicable to you if you work in marketing where consent has been so important over the years. Whilst the other 5 lawful bases for processing data are just as important (and can be applicable to marketing too) my conversations with clients over the last couple of years have thrown up consent as the initial focus area for many.
A lot of organisations have been focussing on the GDPR and how they can implement a data governance strategy that aligns with this change in data privacy regulation. In this two-part blog, we’ll take a look at Lawful Processing with a focus on consent, legitimate interests and how good data quality and specialist technology can support your strategic approach.
In the first instalment, I’m delighted to bring you an interview with J Cromack from the Consentric team at MyLife Digital. He’s an expert on the challenges of managing permissions – from Consent to Legitimate Interests - and we’ll be discussing what Lawful Permissions for processing data mean to organisations preparing for the GDPR. We’re partnering with MyLife Digital to bring the power of their Consentric platform to our clients. With the unique focus on both usability and privacy, we believe that it’s a valuable piece of a GDPR-ready data governance strategy.