Higher Education fosters a culture of collaboration which is unique across all industry sectors. Each and every time I hear a delegate sharing a 'warts and all’ story with fifty other institutions in the room, I'm reminded of an diametrically opposite experience some twenty years ago. Two mobile phone companies were looking to merge. Forty people split across two conference rooms. Labelled 'red' and 'blue' teams. Self conscious engineers from both firms carefully mingled while sporting the appropriate badge. A pastiche of the cold war where the spies of both sides felt a kindred spirit ripped apart by dogma and ideology. [...]
The answer should be a firm yes, but first let me explain why it is often a definite no. Assessment scores are amongst the dirtiest data you can collect, with most methodologies being entirely qualitative Completing the assessment may give you a grade or a level, but other than printing it out and sticking it on the wall, what do you do with it? The HEDIIP programme originally envisaged publishing a data maturity assessment across the HE sector. My view was without a framework for that assessment to operate in, the cost of collection was not commensurate to the value we [...]
This template is a version of the Stanford EDU data maturity assessment model. It is formatted to allow each question to be assessed via a drop down box. When completed, a number of graphs representing the scores will be available for review. The original material is copyrighted for Stanford EDU, but free to use. Please find more details here.
A recurring problem with resolving cross domain data quality issues is the asymmetry of benefits. Essentially the data producer (responsible for entering or uploading data at the point of collection) has little visibility of how the quality of that data will affect the data consumer (the person or persons who use it). The utility of data is often scuppered at this collection point, as the producer - understandably - will apply only the business and quality rules relating to their own use cases. This is not simple to fix. I used to believe merely showing people the implications of these actions [...]
In my last blog post, I introduced a mapping tool linking the HESA Data Futures schema (2.01) to the UCISA HE capability model. This generated an enormous amount of feedback and interest. This interest made me appreciate - again - how powerful the capability model is if tuned to a real world scenario, and that I'd created a bit of a monster in terms of the tool itself. Having said I wasn't going to enhance it, the number of requested changes, and a bit of spare time over the break has brought forth version 2.1. The new functionality includes: A query function [...]
This free to use tool allow you to map the HESA Data Futures Schema to the UCISA HE capability map. It is provided without license or warranty! For more information, please read the accompanying blog post and the update for version 2.1 Latest update: V2.1: Capability Lookup Query, Additional analysis and ranking, new graphs and visualisations and new mapping functionality showing where a capability is both ‘captured’ and ‘used’. Bug fixes pointed out by a few people who downloaded it. Hope it proves useful. If you have any comments in questions, get in touch via the contact form, or leave me [...]
Some combinations just work; Bacon and Eggs, Fred and Ginger, Tom and Jerry, Sheringham and Shearer and - of course - Angus and Malcolm Young of AC/DC. Okay the last one might not be for everyone, but segues into the idea of this article. For universities developing solutions for in-year reporting to the Office for Students, there is a raft of material available. Most of which is provided by HESA as part of the 'Data Futures' Programme*. The most important of which is the Data Dictionary (or schema)which defines all the entities and attributes mandated for each reference point. I've seen [...]
What is it? A business glossary is a cornerstone of any successful data governance framework. It underpins much of the effort to assess, track and improve the data asset. A properly formed glossary is the foundation for driving up the utility of data. It does this by generating trust in that data because we know what it means, and the quality at which it is held. It is therefore an institution wide, agreed business view of the most important data and where it is used. As such, it's a key tool for data stewards and owners to move data out of [...]
This template gets you started with a place to define, store and understand the most important business terms in your institution. Details of how to get the best out of it can be found in this blog post.
The Data Capability toolkit originally developed in the HEDIIP programme is now hosted at HESA: https://www.hesa.ac.uk/support/tools/data-capability. The template we've provided here is a version tweaked to get your started with Data Futures. We have added a set of objectives, issues, aspirations and gaps which reflect the challenges and opportunities which come with a successful implementation of in-year reporting. This template has been used in a detailed form for a number of universities to develop their Data Futures scope and plan.