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The Data LAB: An overview

Darran Gardner, Business Development Executive (Glasgow Hub) @ DataLabScotland. The Data LAB: An overview. The Data Lab Mission. Value: Create economic and social value for Scotland through the application of data science.

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The Data LAB: An overview

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  1. Darran Gardner, Business Development Executive (Glasgow Hub) @DataLabScotland The Data LAB: An overview

  2. The Data Lab Mission • Value: Create economic and social value for Scotland through the application of data science. • Enablement: Facilitate value creation through funding and resources. The goal is not to make a profit or take IP. • Market led: Operating in partnership with Industry, Public Sector and Academia.

  3. Innovation Centres

  4. Landscape Alan Turing Institute

  5. Operating model • Based in Edinburgh (EU, admin centre), Aberdeen (RGU) & Glasgow (GU). • Financial Services, Government, Health, Oil & Gas, Online & Digital • Will work with Industry, Public Sector and SICSA universities across Scotland.

  6. The Data Lab Organisation CEO Gillian Docherty HR (PT) Cheryl Stewart Innovation Advisory Group Education Advisory Group PA Craig Skeldon Head of Product Management Brian Hills Head of Business Development Jude McCorry Head of Operations Dave Fitch Lead Data Scientist Marketing and Communications Cecilia Bouroncle Finance Controller Manolo Perez Legal and Contracts TBH BDE Edinburgh Andrew Mitchell Project Manager Michelle Galea BDE Glasgow Darran Gardner Data Scientist Roman Popat BDE Aberdeen Duncan Hart Data Scientist Richard Carter

  7. Enablers

  8. Collaborative innovation www.thedatalab.com

  9. Public Policy Data Challenge www.thedatalab.com

  10. We welcome “problem” or “challenge” owners from the private and public sectors to engage with The Data Lab • We will fund projects and facilitate match funding (industry, SE, Innovate UK, EU, etc) to support academic engagement • Quick-start research/ exploratory projects (<£20k) • Medium-scale projects (~£50k) 3 to 6 months duration • Large projects and strategic engagements (£50-200k+) • Themed calls (e.g. FinTech in 2015) funding multiple projects • Ultimately, we want to see economic and social impact The Data Lab: Value from Data

  11. Volume (the scale of data) Velocity (speed of change) Veracity (uncertainty of data) Variety (different forms of data) Vulnerability (security and privacy) Visualisation (and other forms of interaction) There’s more to data than size…

  12. Question (scoping to clearly define) • Data Capture (quantity, quality, real time v batch, security / anonymity) • Data Model (the how, e.g. Hadoop) • Analyse (the process) • Inform (the output) What makes a good big data project?

  13. Delivery team / skills • Right mix/experience: BD architectures, BD techniques (stats/ maths/ machine learning), programming, soft skills • Scale / integration/ roll-out / commercialisation What makes a good big data project?

  14. Asking the wrong questions • Selecting the wrong uses • Lacking the rights skills • Accessing the correct data • Disagreement on enterprise strategy • Data silos • Management resistance • Problem avoidance Source:  Svetlana Sicular, Gartnerhttp://blogs.gartner.com/svetlana-sicular/big-botched-data/ What makes a ‘bad’ big data project?

  15.  Insti­tute for Data-Intensive Research (IDIR)  What makes for a good data project? www.thedatalab.com

  16. Events www.thedatalab.com

  17. Contact:TheDataLab.com@DataLabScotlandDarran.Gardner@TheDataLab.comDuncan.Hart@TheDatalab.comContact:TheDataLab.com@DataLabScotlandDarran.Gardner@TheDataLab.comDuncan.Hart@TheDatalab.com

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