Ch 19 Big Data - Exam IV

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Ch 19 Big Data - Exam IV
2013-11-08 23:20:46
Security Governance Big Data Environments

Security & Governance for Big Data Environments
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  1. information governance
    capability to create an information resource that can be trusted by employees, partners, and customers, as well as government organizations
  2. Security & Governance
    potentially the most critical of the pillars of data management
  3. data anonymization
    all data that can be uniquely tied to an individual are removed (ex: person's name, soc sec num, credit card number) - not always easily done
  4. tokenization
    protects sensitive data by replacing it with random tokens or alias values that mean nothing to someone who gains unauthorized access to this data - is argued that it's more secure than encryption
  5. cloud database controls
    access controls are built into the database to protect the whole database sot that each piece of data doesn't need to be encrypted
  6. data anonymization
    cloud database controls
    data-safeguarding techniques
  7. visibility - be aware of how the data will be used and controlled
    unvetted employees - trust of those working with the data
    two key issues to consider in regards to data governance
  8. ANY or ALL data
    ______ that will be ultimately be stored or embedded in organizational processes must be covered by some sort of governance policies
  9. legal constraints
    restrictions on the use of data - the organization has first say in how I can use their data
  10. visibility
    issue with data governance regarding seeing the data as it transforms - everything that happens to the data must be tracked - not all data access is always under the control of the org - all parties with access to the data should be able to track & share all movement & comply with the org's governance policies
  11. unvetted employees (without background checks)
    issue with data governance dealing with security threats coming from within an org - background checks - education on governance policies helps
  12. auditing protection
    a way to show logs or other evidence that the data you are using is secure and clean - explain the sources of that data & minimize the risk to the company
  13. creating data managament policies (can be put in place before any data has arrived - don't change much with big vs traditional data)
    the "first" step in the organizational structure process
  14. data steward
    one who needs to understand the company's data retention policy as well as the requirements for masking out personal data no matter where that data originates - the one who is tasked with data management oversight
  15. determine best practices
    compare policies w/self & others
    policy concerning length of time to hold on to info?
    importance of data being brought in
    some of the key elements that need to be codified to protect your organization in regards to governance
  16. what's already in place?
    compare w/others in industry?
    your policies complete?
    policies reflect data quality, trust, security, & risk issues?
    key elements of data policies
  17. what's your current approach to data security?
    what're your data access policies?
    what're your vulnerablities?
    are you secure from external intruders?
    how is encryption handled?
    does your software monitor questionable transactions?
    are you in control of all data resources?
    what're your recovery plans?
    questions to consider in developing a well-governed and secure big data environment