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CSG

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CSG Data Management & Governance at Berkeley Shel Waggener CIO/AVC IT UC Berkeley – PowerPoint PPT presentation

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Title: CSG


1
CSG Data Management Governance at Berkeley
  • Shel Waggener CIO/AVC IT UC Berkeley

2
Common Data Management Challenges
  • Data is replicated over and over again, modified
    and fragmented by the many independent systems
    and the organizations who manage them.
  • Security weaknesses exist as a result of both the
    spread of the data and the vast number of varying
    architectures used to collect, distribute, and
    manage the data.
  • The administrative and academic units that manage
    duplicated data (or create duplication for the
    purpose of local management) all assert some
    level of ownership to each data element, often
    overlapping.
  • Considerable and overlapping investments continue
    to be made across campus silos with technologies
    and staff time for both functional and technical
    groups to maintain this spaghetti architecture
    of legacy, current, and emerging technologies.
  • This represents a divergent strategy at a time
    where, more than ever, the campus needs greater
    visibility, accessibility to, and sharing of data
    within and across silos to make better decisions
    and work together as a campus.
  • The opportunity here is not only for
    administrative data, but also for scholarly
    information not only for structured, but also for
    unstructured data.

3
Berkeley Data Services
  • Four groups in support of Institutional and
    Scholarly Data
  • Data Repository Management Supports data
    modeling, data warehousing, data repositories,
    data integration, collections and archives/media
    vault.
  • Collaboration, Presentation, Analysis Supports
    tools for data capture and collection, user
    interface tools for reporting, decision support,
    visualization and collaboration.
  • Data Architecture Facilitates the definition of
    architectural standards for campus Information
    Services and coordinates architectural planning
    with the CIO Offices Architecture group.
  • Social Sciences Computing Laboratory Operates
    instructional facilities and consultative
    services for academic use. Operates environments
    to provide on-line access to large-scale
    collections of quantitative, structured, or
    image-type data. Provides specialized research
    services, including custom application for data
    collection and data management for the collection
    and processing of survey-type data.  

4
Scholarly Data
NSF Cyberinfrastructure View
Source NSF Atkins Report on Cyberinfrastructure
http//www.nsf.gov/od/oci/reports/fig21.html
5
Scholarly Data
NSF Cyberinfrastructure View
Source NSF Atkins Report on Cyberinfrastructure
http//www.nsf.gov/od/oci/reports/fig21.html
6
Case Study - Decision making UC Berkeley
Enterprise Data Warehouse
  • Opportunity analysis and conceptual EDW
    Architecture study performed over the last 30
    months.
  • From the inception, it was universally recognized
    that the core decision making structures and
    processes necessary to support prioritization and
    commitment beyond existing data was absent at a
    campus level. We have not made progress in
    developing an implementation plan for the EDW
    beyond tactical enhancements.
  • This has contributed to parallel implementation
    efforts and investments with separate data
    warehouses and reporting systems (and tools) for
    use across the same university community.
  • The issues involved are complex, however,
    inadequate decision making and the pace of that
    decision making equates to missed opportunities
    and greater risk.
  • Enterprise Data Warehousing and reporting are
    disconnected from other major campus initiatives.

7
Case Study Policy and Compliance UC Berkeley
  • Requests for data across organizational
    boundaries are increasing dramatically.
  • However, we have not adequately invested in the
    tools, infrastructure, processes or people needed
    to make the data safely available
  • The data itself may be sensitive, with
    ownership or stewardship issues associated with
    it.
  • While we have no perceived shortage of policies
    and regulations we do lack a compliance program
    to measure how effectively the policies are
  • Compliance is best effort approach rather than
    a systematic program

8
UCB Data Management Governance Status
  • New Campus Technology Council assembled and
    general IT Governance processes in development
  • Campus Data Stewardship Council exists as an
    advisory body
  • 2007 target to establish a formal Data Management
    Governance strategy, moving beyond advisory and
    into an operational mode with decision making
    abilities
  • Proposals under consideration, including

9
UCB - DM Governance Structure Proposal
10
A Use Case Restricted Data
  • Data Management for Restricted, Sensitive or
    Personally Identifiable Information IS different.
  • Stolen laptop with no encryption constant problem
  • Security Breach of Sensitive Data is big
    loss
  • Most of the centrally managed data is the
    greatest target but best protected. Most of the
    distributed data is smaller target but much
    easier to get to
  • Berkeley is trying a carrot with stick approach

11
What We Provide
  • Simply tell us where the PII is and we
  • Add rules to all the scanning tools to monitor
    your server
  • Setup 7x24 response procedures for notification
    any identified issues
  • Application scan for vulnerabilities against all
    registered apps
  • Provide augmented security training to
    administrators of those departments
  • Provide security tools and licenses at no costs

12
What We Do if You DONT tell us
  • Possible approaches
  • Once identified, give you 72 hours to get the
    system registered before we block traffic
  • Once blocked, require training and penetration
    testing before allowed back on the network.

13
Validation Email
  • Thank you for using the Restricted Data
    Management (RDM) system at http//rdm.berkeley.edu
    ! We appreciate your efforts to safeguard
    restricted university information assets by
    letting us know about your data systems and the
    machines that host them.
  • You are receiving this email because you have
    logged in to RDM, or have been set up as a user
    of the system by another member of your
    department. We want to follow-up with all users
    of RDM and find out if you have experienced any
    difficulty or need further information/assistance.
    Please reply to this email with any questions or
    comments about RDM, or if you would like to
    arrange an in-person meeting with us to
    demonstrate RDM.
  • To ensure that your systems are being protected
    by SNS, please make sure that you complete the
    following steps
  • 1) Add you systems to RDM and check appropriate
    data elements (if you aren't sure about any
    elements, just skip them for now as you can
    always update this information later).
  • 2) Let us know where the data is stored -- a
    local machine in your department or an IST
    supported service.
  • 3) For local machines, please BE SURE TO INCLUDE
    AN IP ADDRESS. This is critical to the SNS
    monitoring systems and will result in a higher
    level of SNS services for your host machine.
  • 4) Register a security plan for your system
  • Thanks again and please contact us with any
    additional comments or concerns.

14
Additional materials
  • Refer to
  • http//calshare.berkeley.edu/sites/RAPO/DRM/csgdat
    a
  • http//rdm.berkeley.edu
  • UCB CIOs Data Management Governance Proposal
    2007
  • UCB EDW Process Architecture Presentation 2006
  • UCB EDW Process Architecture Report 2006
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