What are data sharing agreements and where do they fit in a Data Governance framework? On first analysis, it’s not obvious that they do! However, they are relevant when we consider the scope of that framework. The production, manipulation and use of data outside of our organisations are often forgotten when considering data quality. We focus on internal ingress points which are mostly controlled through our own stewards and producers. This can be a dangerous assumption as external data is far more common than we might think. It fits into two distinct areas: Additional data sets. These are often paid-for datasets which augment [...]
Nicola Askham and I recorded this pre-lockdown. We only finally found time to publish it now! It is the first of five webinars taking you from the Business Case for Data Governance, through the development and operationalisation of a data strategy, and finishing on how to make Data as an asset sustainable. Data as your GPS https://datapromedia.wistia.com/medias/6kt27nnc6p The next one 'How to create a pragmatic data strategy' will be a slightly different format, but hopefully just as informative. Due to be released end August 2020.
Who are the DGN and why are we running an assessment. The Data Governance Network (DGN) is made up of practitioners from over 30 UK universities. It is primarily a support network to develop and share good practice in relation to data management and governance for the HE sector. It has become clear that in order to provide this support we need to understand where the sector currently is in terms of its capabilities around the management and governance of data. By understanding this we can target the development of tools, techniques and associated guidance to increase our mutual data capability [...]
This is the recording of the webinar and the lively Q&A hosted July 15,2020. Thanks to my friends at Waterstons for co-creating and delivering the content. They also did all the hosting, so all I did was virtually turn up and - initially - forget to unmute my Mic :) We've had great feedback from the attendees so I hope you enjoy our views on what's changed and how to take advantage of it.
There are many ways to develop a Data Strategy. I don't pretend to have 'the best way', but I do know - from long experience - what works and what doesn't. This was somewhat thrown into turmoil when COVID-19 enforced virtual working. Since then I'm close to completing my second virtual strategy delivery, and will soon be starting a third. I was asked by my latest client to summarise the differences/challenges/opportunities of creating Data Strategies through virtual delivery. I thought it would be useful to share what I feel are the key points.: Engagement: virtual breakouts, voting, time for discussions, etc. [...]
I'm co-hosting a one hour webinar with my friends and colleagues from Waterstons It's based on feedback from our clients on gaining clarity on what to measure, and how to make best use of the outputs of those measurements. Sign up here: https://www.waterstons.com/events/data-driven-decision-making-in-unprecedented-times A litte more context below. Universities are an eclectic mix of cutting-edge research, world changing-innovation and centuries old tradition. Ultra-modern, glass-plated campuses can mask communities that are slow to embrace change. “We’ve always done it like that” and “we tried that in the last transformation programme and it didn’t work” echoes down corridors while world class scientists recreate [...]
Any data professional should be a clear advocate of implementing good data management and governance. Like many apparently self-evident statements, this is not quite as simple as it seems. Consider data quality. The go-to best practice approach is 'Clean at the point of capture'. Which is absolutely best practice if you have first understood why you need to capture that data, whether you have the right source or have already captured it elsewhere, what the full range of use cases are and how quality tolerances will be calculated and measured. This is still less than half the job done though. And that's [...]
Data Governance is not Data Science. Which is a shame because it is the latter that excites the senior leadership of most organisations I work with. This is understandable as these individuals are interested in high quality information which informs the decisions and actions they are making on a daily basis. Much of this information is purportedly an output of Data Science. What is less understandable is how the good management and governance of data is somehow divorced from the use of it. This is not a new problem; in the last ten years ‘Data Science’ could be replaced by ‘Analytics’, [...]
Testing out the whiteboard. Optional Labrador available for all remote workshops! Let’s start by saying there are far more important things going on in the world right now. We’re in uncharted territory with the concept of being on a ‘war footing’ not seeming too far-fetched. The efforts being made by our healthcare, retail, logistics and so many other sectors renders what we do significantly less important. Although how data is being used in this crisis is fascinating. We’ll be back to that in a later post. Our approach has been to control only what we can control and not [...]
The Data Quality Issue Log (DQIL) is a central tenet of any sustainable data governance framework. It is the central repository for the entire organisations data issues, themed by urgency, priority and business alignment. It drives activity for the Data Stewards and acts as a point of accountability for the Data Owners. So why does nobody to care about it then? Mostly because it’s hard to link 500+ issues to something that feels tangible and important. The problem with a DQIL is it is a repository not a source of management information. It is a passive receiver of issues. We want to [...]