Successfully reported this slideshow.
Your SlideShare is downloading. ×

The Sixty Minute (Data Dashboard) Makeover!

Loading in …3

Check these out next

1 of 38 Ad

More Related Content

Slideshows for you (20)

Similar to The Sixty Minute (Data Dashboard) Makeover! (20)


More from Marieke Guy (20)

Recently uploaded (20)


The Sixty Minute (Data Dashboard) Makeover!

  1. 1. #IWMW17 #A7 The Sixty Minute (Data Dashboard) Makeover – in 1 hour 30 minutes! Marieke Guy, QAA Jon Rathmill, University of Kent Tuesday 11th July 2017 16:00 – 17:30
  2. 2. #IWMW17 #A7 Introductions
  3. 3. #IWMW17 #A7 • Data analyst at Quality Assurance Agency for higher education (QAA) • QAA mission is to safeguard standards and improved the quality of UK higher education, wherever it is delivered in the world • Does this by:  delivering elements of revised operation model for quality assessment  managing assessment process for TEF  regulating Access to HE qualification  maintaining UK Quality Code  advising on degree awarding powers  carrying out review of Alternative Providers  Strategic international work (TNE) Marieke Guy - QAA
  4. 4. #IWMW17 #A7 Jon Rathmill - University of Kent • Planning Analyst in the Planning and Business Information Office (PBIO) • Previously worked in FE college MI department • PBIO is responsible for the provision of management information, both external and internal, on the complete range of student academic activity. • Migrating to use of Qlikview to display data and statistics.  Allows users to filter and shape reports to meet their needs  Quicker to disseminate data  Visualisations improve understanding  Standardised design across dashboards to help users  Allows greater data control – only certain users see certain things
  5. 5. #IWMW17 #A7 Overview of the Workshop Time Session Introduction session 16:00 – 16:30 Data in Higher Education (MG & JR) Practical session: Sixty second dashboards 16:30 – 16:45 User stories (All) 16:45 – 17:00 Data sources (All) 17:00 – 17:20 Designing a dashboard (All) Show and tell and feedback 17:20 – 17:30 Delegates present their dashboard (All)
  6. 6. #IWMW17 #A7 Data in Higher Education
  7. 7. #IWMW17 #A7 Data Landscape
  8. 8. #IWMW17 #A7 • DLHE – Destination of Leavers in HE • NSS – National Student survey • LEO – Longitudinal Education Outcomes • POLAR – Participation of Local Areas • PRES – Postgraduate Research Experience Survey • KIS – Key Information Sets • HE-BCI – HE Business Community Interaction • JACs – Joint Academic Coding System • HECos – HE Classification of Subjects • CAH – Common Aggregation Hierarchy • HESA – Higher Education Statistics Agency • TEF – Teaching Excellence Framework • REF – Research Excellence Framework Acronyms…
  9. 9. #IWMW17 #A7 “The HE sector has always been a data-rich sector, and universities generate and use enormous volumes of data each day. However, the sector has not yet capitalised on the enormous opportunities presented by the data revolution, and is lagging behind other sectors in this area.” From Bricks to Clicks report, Higher education Commission
  10. 10. #IWMW17 #A7 • Data everywhere in the HE sector:  Collection by HESA and through surveys  Use in TEF, REF, league tables • Data collection/use is (to some extent) in hand (HEDIIP/data Futures) but data analysis isn’t • Data ownership and management is slowly evolving • Data seeping in to all aspects of HE provision and decision making: programme design, retention, WP, learning analytics • Many staff concerned about their data capabilities • Agencies need to work together (Bell review) Data in HE
  11. 11. #IWMW17 #A7 “A business intelligence dashboard (BI dashboard) is a software interface that provides preconfigured or customer defined metrics, statistics, insights and visualisation into current data. It allows users to view instant results into the live performance state of business or data analytics.” Technopedia
  12. 12. #IWMW17 #A7 Where the Work is - IPPR - Institute for Public Policy Research
  13. 13. #IWMW17 #A7 Some Unis doing really well… Liverpool HopeDe Montfort Gloucestershire
  14. 14. #IWMW17 #A7 Business Intelligence Analytics Lab Project
  15. 15. #IWMW17 #A7 • HESA data:  Summary data from the HESA Student, Staff and Finance submissions  HE Business and Community Interaction (HE-BCI), Estates Management and Destinations collections  Performance Indicators, Student Staff Ratios, Aggregate Offshore Record (AOR) • Heidi - web-based management information service developed for accessing, extracting and manipulating data • Heidi plus – New BI service, more granularity, more visualisation opportunities , Heidi and
  16. 16. #IWMW17 #A7 • National analytics experimentation project led by Jisc and HESA • Aim to refresh Heidi Plus content with insights from a wide range of alternative data sources • Teams comprise staff from multiple institutions • Teams themed – agile approach • Working towards ‘proof of concept’ dashboards • These dashboards will be further developed by HESA • 130 people, 70 institutions, on 6th round BI Analytics Labs
  17. 17. #IWMW17 #A7 Labs Overview
  18. 18. #IWMW17 #A7 Team member Institution Tom Wale University of Oxford (Product owner ) Jon Rathmill University of Kent Carolyn Deeming Plymouth University Marieke Guy QAA Elena Hristozova University of Nottingham Myles Danson Jisc (Scrum Master) Kris Popat Cetis (Data Wrangler) Neil Richards HESA/Jisc (Data viz) Team Tom
  19. 19. #IWMW17 #A7 • Employability (including TEF planner) • Staff • Market insights • Library resources • Finance • FE – in particular manufacturing and how it links to local FE colleges • Research Theme areas
  20. 20. #IWMW17 #A7 Research Student Experience I want to: Understand the progress and completion of my research students, and the issues that they face So that I can: Ensure that my institution can improve its research student experience and improve the proportion graduating, and how this compares with others Brexit and International Exposure I want to: Understand my exposure to the EU by subject for research in terms of research students, staff and research income So that I can: Understand what gaps I might have should European students, staff and income dry up, and whether this is particularly different from other institutions Preparation for REF I want to: Understand how my institution’s activity since REF14 contributes to REF21 So that I can: Understand how my institution’s performance compares with others operating in the same subject areas User stories
  21. 21. #IWMW17 #A7 • Low shelf data  Publicly available & openly licensed  Vast, distributed, no common vocabulary, complex  May be patchy  Not designed to be combined with other data  Examples include demographic, geo-spatial, international, census • High shelf data  Closed licensing - available by subscription or is locked to third party organisations  Examples include funding and regulatory, local councils, Government bodies, fees and admissions, careers and trajectory, current study data, staff, research, financial, estates or even institutions themselves Low shelf vs high shelf data
  22. 22. #IWMW17 #A7 • HESA Student • HESA Staff • HESA Finance • HEA – PRES data • Eurostats training/data/database • EU Community Research and Development Information Service (CORDIS) • RCUK – funding awarded – Gateway to Research Data sources used
  23. 23. #IWMW17 #A7 BI Labs Dashboards
  24. 24. #IWMW17 #A7 Kent Qlikview Dashboards
  25. 25. #IWMW17 #A7 Practical session – Designing dashboards
  26. 26. #IWMW17 #A7 Practical: User stories (All)
  27. 27. #IWMW17 #A7 • Brainstorm possible themes • Decide on a theme to be explored • Craft up to three user stories for your dashboard using the user stories template In your groups
  28. 28. #IWMW17 #A7 User Stories • As a: <user> • When: <context> • I want to: <feature> • So I can: <benefit>
  29. 29. #IWMW17 #A7 Practical: Data Sources (All)
  30. 30. #IWMW17 #A7 • Brainstorm HESA data fields that may be useful (student, staff, finance, other) • Brainstorm possible external data sources to use • Have a look at: • Think about connections between your data sets (unique IDs) • Think about the possible challenges your choices may pose:  High shelf vs low shelf data  Data quality, availability, licence  Time, cost, date In your groups
  31. 31. #IWMW17 #A7 Practical: Designing a Dashboard (All)
  32. 32. #IWMW17 #A7 • Pick an artist • Agree on one user story to develop • Create some sketches of what your dashboard could look  Think about potential users  Consider usability, layout, colour  Consider filters, searches, titles, legends, navigation  Sense check that it tells an honest story! In small groups
  33. 33. #IWMW17 #A7 “It’s not good enough for there to be a looming fear in the sector; we should have an open forum for debate about the detail of data, and the best ways to use it.” Ant Bagshaw, Wonkhe
  34. 34. #IWMW17 #A7 • Make friends:  Find out who deals with data in your organisation  Find out what tools they use  Build up links with them • Think about data:  Start thinking about data, visualising data and the complexities of data  What data do you have? Google analytics, other?  Are there opportunities for embedding it on your website? • Watch out for the M5 (Jisc, HESA, QAA) data conference (3rd November – London) • Get your staff involved in the BI Analytics Labs work ( Future activities
  35. 35. #IWMW17 #A7 Resources
  36. 36. #IWMW17 #A7 • BI Analytics labs website: • BI Analytics labs data catalogue: • Tablea public: • Tableau HE: higher-ed • The Seven Hats of Visualisation Design: A 2017 Reboot – Slideshare – by Andy Kirk: visualisation-design-a-2017-reboot • Neil Richards Tableau Public: • Subscribe JISC-HESA-BUSINESS-INTEL’ to • Twitter @HESA @jisc #hesajiscbi Useful resources
  37. 37. #IWMW17 #A7 • All images from:  Courtesy of Jisc and HESA  Pixabay – CC0 -  or author’s own Credits
  38. 38. +44 (0) 1452 557000 © The Quality Assurance Agency for Higher Education 2016 Registered charity numbers: 1062746 and SC037786 #IWMW17 #A7 Thank you