Data Management Future: An ECAR Presentation (180601411)
Transcript of Data Management Future: An ECAR Presentation (180601411)
8/14/2019 Data Management Future: An ECAR Presentation (180601411)
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8/14/2019 Data Management Future: An ECAR Presentation (180601411)
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Data Management FutureAn ECAR Presentation-
Friday Oct 18, 9:10 AMGuy Almes, Judy Caruso, Mike Fary, Curt Hillegas
8/14/2019 Data Management Future: An ECAR Presentation (180601411)
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Agenda
Overview ECAR DM group and Data Management
Administrative, Research and Academic Data – commonalities, uniqueness, future
Data visions
Discussion - What do you think about the differences,similarities between the different data and where is thisgoing?
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Administrative Research Academic
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Administrative Data
What does it have in common with Research data?
Academic data?
What is unique?
Where is administrative data management going?
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Define Administrative Data
Data which is used in the day to day running of thebusiness activities of the institution.
Examples of administrative data include student course
grades, employee salary information, vendor payments,
and facilities work orders.
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Where Does It Live?
Today:
Typically, on premises applications
Vendor provided
University managed (application and infrastructure)
Moving Toward:
Off premises (SaaS)
Many support models
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In Common with Other Data Types
Asset of the Institution
Policy, and in some cases law, govern it
Demand for access to it is growing
Core infrastructure (network, IdM, etc.)
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Unique
Tends to be structured
Relatively small in volume
Relies on established technologies
Institutionally managed for 50 years
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Where is it going?
To the “Cloud” (SaaS, PaaS, IaaS)
Traditional data models (ER)vs.
Non-traditional (NoSQL)
Data Services
Predictive Analytics
Data Protection
Public Data Sources
Internal/External Sharing
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Research Data
What does it have in common with Admin data?
Academic data?
What is unique?
Where is research data management going?
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Define Research Data
Data that is used by or is a product of research.
Examples include:
Output from experimental devices
Masses of data collected from the internet
Results of computation modeling and simulation
Results of data analysis
Data about the data
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Where Does It Live?
TodayOn campus
In the cloud
At research “centers”
Moving toward
As the size of data sets grow, research data will needto live near where it will be used
Significant portions of data will live distributed in thecloud, and “Big Data” techniques will need to be usedto collect and analyze
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In Common with Other Data Types
Growing
Asset of the Institution
Policy and law govern some of it
Core infrastructure requirements
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Unique
Can be very large (TB, PB, and beyond)
Not necessarily centrally controlled
May require very high performance access
Increasing need to share (both inside and outside the
institution)
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Where is it going?
Humanities
Social Sciences
Cloud
Research “centers”
Through bigger pipes
Will the data come to the computing or will the
computing come to the data?
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Academic Data
What does it have in common with Admin data?Research data?
What is unique?
Where is research data management going?
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Define Academic Data
Data that is associated with teaching and learning. Thisincludes objects and processes.
Examples of academic data include course catalog,
learning objects, academic program information, learning
outcomes, learning analytics, teaching methods
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Where Does It Live?
Today:
On premises applications and in the cloud
Scattered – all locations are not known
Moving forward:
More of the same?
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In Common with Other Data Types
Asset of the Institution
Policy, and in some cases law, govern it
Demand for access to it is growing
Core infrastructure (network, IdM, etc.)
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Unique
Individual faculty have control over where the data is
What data the institution has is not always known
Course catalog and Program information is critical to
Accreditation
Increasing demand for analytics
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Where is it going?
To the “Cloud” (SaaS, PaaS, IaaS) – without contracts?
Predictive Analytics
Increased attention to learning outcomes
Data Protection
Internal/External Sharing
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Visionary – Technology Trends/Drivers
Rapid exponential growth in capacity over time
Mostly a good thing, but note complex societal implications
Role of the network:
Enables sharing of (even) large data, especially research
Campus-to-campus and/or campus-to-cloud
Sharing raises hard IdM and related federated authentication
challenges
Hard technical / infrastructure / policy challenges
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Discussion
What do you think about the differences and similaritiesbetween the different data?
Where do you think this is going?
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Join the ECAR Data Management WG
Contact [email protected].
http://www.educause.edu/ecar/ecar-working-
groups/get-involved
We’d love to have you join us!
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