Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Data Access in A Cloud World

Data Access in A Cloud World

Two key strategic trends are in progress: pedagogical use of learning analytics and the move to cloud infrastructure. This session explores the intersection of these two trends. As we seek to bring more learning analytics to drive student success, ensuring robust access to learner data is essential. We will discuss past practices and look to current options in the context of cloud infrastructure, and invite attendees to bring their practices and questions to our session.

Sean Yo

May 17, 2017
Tweet

More Decks by Sean Yo

Other Decks in Education

Transcript

  1. Sean Yo – D2L
    Sr. Product Manager
    Analytics & Data Platform
    In a Cloud World
    Data Access

    View full-size slide

  2. Hi! I’m Sean Yo
    • Sr. Product Manager @ D2L
    – Most of my 4 years: Analytics & Data Access
    • 12 Years in Higher Ed IT
    • Teach with Brightspace at the College
    level
    • Get the slides: http://sean.ly/LILI17

    View full-size slide

  3. Why are we here?
    • Two key trends in education
    – Learning Analytics
    – Cloud Computing
    • Both continue to have strong growth
    • How does the intersection of these
    trends affect data access in EdTech?

    View full-size slide

  4. Learning Analytics

    View full-size slide

  5. What does this change mean?
    • I want to level set on Learning Analytics
    • This is an investment for our discussion
    about the cultural change, strategy and
    tactics that we’ll wrap up with.

    View full-size slide

  6. The Brave New World of Data
    http://www.economist.com/news/leaders/21721656-data-economy-demands-new-approach-antitrust-rules-worlds-most-v
    aluable-resource

    View full-size slide

  7. Learning Analytics
    • What is Learning Analytics?
    – For individual learners to reflect on their progress;
    – As predictors of students requiring help;
    – To help instructors plan interventions;
    – To drive instructional design improvement; and
    – For institutions to make business decisions.
    Powell, Stephen, and Sheila MacNeill. Institutional Readiness for Analytics A Briefing Paper. CETIS Analytics Serie
    s. JISC CETIS, December 2012. http://publications.cetis.ac.uk/wp-content/uploads/2012/12/Institutional-Readiness
    -for-Analytics-Vol1-No8.pdf.

    View full-size slide

  8. IT needs to Bring Data to Campus
    Not If…
    But When

    View full-size slide

  9. Learning as a Digital Experience
    • Today’s notion of Learning Analytics is
    built on the data capture capabilities of
    digital platforms
    – If it doesn’t happen online – we can’t see it
    – If we can’t see it we can’t count it
    – If we can’t count it…there is no data

    View full-size slide

  10. Learning Analytics Growth
    Source: Ovum 2015 ICT Enterprise Insights Survey

    View full-size slide

  11. Trough of Disillusionment

    View full-size slide

  12. Campus Computing 2016
    https://www.campuscomputing.net/content/2016/11/21/the-2016-campus-computing-survey

    View full-size slide

  13. Emerging Value
    • Shifting learner intervention to an increasingly
    evidence-based process
    • Detailed tracking of learner and instructor
    behaviour
    • Large, well-formed data to analyze
    – Analytics, Machine Learning, Prediction, Adaptation
    • Easy to automate and low cost to distribute

    View full-size slide

  14. Trade Offs
    • Digital course design requires explicit
    development to drive data collection
    • Pedagogical methods need to be adapted
    • LMS systems can only measure what is
    delivered via the LMS
    • Data Literacy increasingly important

    View full-size slide

  15. Cloud Computing
    Cloud Computing

    View full-size slide

  16. What does this change mean?
    • I want to level set on Cloud Computing
    • This is an investment for our discussion
    about the cultural change, strategy and
    tactics that we’ll wrap up with.

    View full-size slide

  17. What is Cloud Computing?
    • Co-location?
    • 3rd Party Hosting?
    • External Data Centre?
    • Outsourced Computing Infrastructure?

    View full-size slide

  18. Computing as Utility
    • On-demand
    – computing resources, over the internet on a pay-for-use basis.
    • Elastic resources
    – Scale up or down quickly and easily to meet demand
    • Metered service
    – Only pay for what you use
    • Self service
    – All the IT resources you need with self-service access
    https://www.ibm.com/cloud-computing/learn-more/what-is-cloud-computing/

    View full-size slide

  19. Consolidation
    https://hbr.org/2002/12/the-consolidation-curve

    View full-size slide

  20. Cloud Computing Growth

    View full-size slide

  21. Emerging Value

    View full-size slide

  22. What does this change mean?
    • We’ve level set on Learning Analytics and
    on Cloud Computing
    • Now we get the payoff for our discussion
    about the cultural change, strategy and
    tactics that we’ll wrap up with.

    View full-size slide

  23. Data Access
    • What is it?
    – Exports of data from the LMS to use outside of the L
    MS
    – ODBC, SQL Export, CSV, JSON/API
    • What isn’t it?
    – Reporting, Visualization
    • Why is it important?
    – Custom/in-house analysis, data discovery, integration

    View full-size slide

  24. Data Access – On Prem
    • On-Prem Data Access was essentially
    transparent
    • Infrastructure is on-site – data storage &
    transfer are effectively $0
    • Direct access via SQL or File System
    access = fast, simple & convenient
    • Risk: Capacity Planning, Cost, No data
    contract

    View full-size slide

  25. What have you done?
    • How have you used on-prem data access?
    • Are you still doing this?
    • What are the benefits for your org?
    • What are the pain points for your org?

    View full-size slide

  26. Data Access - Cloud
    • Cloud Data Access
    – Typically CSV extract or JSON API
    – Could be a SQL export, but this is inefficient
    • Benefit: Data Contracts, built for integration
    • Risk: Storage and Transfer are metered,
    New skills (scripting/API) may be
    required

    View full-size slide

  27. What have you done?
    • How have you used cloud data access?
    • How has integrations worked?
    • What are the benefits for your org?
    • What are the pain points for your org?

    View full-size slide

  28. The Hard Problem
    • Cultural Change is the hard problem with
    Cloud-based Data Access
    – Shifting away from infrastructure being
    “under the desk” and accessible by “sneaker
    net”
    – More value by more usage of LMS
    – More success with clear requirements in
    advance

    View full-size slide

  29. Strategies
    • Support data standards! Put them in your purchase
    requirements!
    • Identify what you’re doing today around data access
    • Validate the “We Need All The Data” request from
    internal stakeholders
    • Articulate measurable outcomes and the data needed
    to achieve those outcomes
    • Lean in the strengths of Cloud delivery services

    View full-size slide

  30. Tactics
    • Prepare for a heterogeneous data pipeline
    • Start/Grow in-house data ecosystem
    – ETL/DW, Data Lake etc.
    – How can you make your data ecosystem
    Future Friendly?
    • Assess if you have sufficient data expertise
    – Data Analysis is a mature discipline

    View full-size slide

  31. Thanks!
    • Lets connect!
    – @seanyo on Twitter
    – www.linkedin.com/in/seanyo/
    • Get the slides: http://sean.ly/LILI17

    View full-size slide