Readings
#19
The class will be about cyber-security, with a focus on databases. Read chapter 12 from the oReilly book. If you are not on grounds, you will need a VPN. If you do not find UVA in the drop-down list on the webpage, no problem: follow the instructions 'Not
listed? Click here.'
Skip 'Multilevel Relations and Polyinstantiation'. Then read the document from the NIST (National Institute of Standards and Technology, a federal government body). Read sections 1.0,
2.1, 2.4, and 3.0.
Literacy: NIST framework, The five components of the framework, Privacy, Database integrity, Database availability, Database audit, Authentication, Access control, Discretionary access control, Mandatory access control, Bell–LaPadula model, Clearance, Role-based access control, Encryption, Digital signatures, Non-repudiation, Statistical database.
#20
The class will be about blockchain, which is at the core a database technology (who knew?). We will focus on the blockchain, as
opposed to BitCoin or crypto currencies. Begin by watching a short (6 min) video on what is the blockchain. Then learn about potential
use cases for the technology. Next, read about a real world case of
blockchain used to prevent fraud. Skip the methodology sections and focus on the story: the company, the frauds, the controls,
etc. Lastly, read the first five pages of DeFi, the latest twist on FinTech.
Literacy: blockchain, ledger, hash, DeFi, smart contract
#21
Our guest, John Duncan, is an UVA MSMIT graduate. He will talk about data quality in the real world. John works at CarMax, where he is the Director and Head of Data Governance and Master Data. As background knowledge, please read the following two short articles: Only 3% of Companies’ Data Meets Basic Quality Standards and To Improve Data Quality, Start at the Source.
It is your job to make Mr. Duncan feel appreciated for sharing his substantial professional knowledge with us. Prepare a couple of good questions in advance, ask them, and stay engaged.
#22
Our Guest today will be Ms. Jamie Specter Dattilo. Jamie holds an MSMIT degree from UVA and a Law degree from the University of
Richmond. She will introduce the broad topics of data ethics and privacy. What "privacy" means depends on who you ask and there
is a lot of history behind the topic. Broadly speaking, privacy is the right to be let alone, or freedom from interference or
intrusion. Information privacy is the right to have some control over how your personal information is collected and used. Also,
various cultures have widely differing views on what a person’s rights are when it comes to privacy and how it should be regulated.
Watch this ~15 minute video on The
History of Privacy - you should have three trial videos available without having to sign up.
Why it matters. With speed-of-light technological innovation, information privacy is becoming more complex by the minute as more data is
being collected and exchanged. As the technology gets more sophisticated, so do the uses of data. And that leaves organizations facing an
incredibly complex risk matrix for ensuring that personal information is protected. As a result, privacy has fast-emerged as perhaps the
most significant consumer protection issue—if not citizen protection issue—in the global information economy. According to the
International Association of Privacy Professionals, Organizations that don’t “do privacy” right are at risk—of government enforcement, class
action lawsuits, financial ruin, damaged reputation and loss of customer loyalty. Privacy is now a necessity of doing business.
Read: Do you care as
much about privacy as your consumers? (oReilly link - see instructions about the previous reading)
Read: UVA's privacy policy
Review: Building Digital Trust: the Role of Data Ethics in the Digital
Age
Complete this survey to share your thoughts on privacy.
#23
For the last session of the semester I picked a couple of related topics that I hope will spark a lively conversation. The first is data
monetization, or how to extract measurable value from data. Read these two short pieces from Forbes and from the CISR center at MIT.
Question for you: in your internships have you seen examples of data monetization? Be ready to describe them. If you do not have a direct experience, can you think about some other examples?
The second topic will be Non Fungible Tokens, or NFTs. I have two more short pieces from Forbes and from the FT. In class I will ask you what would you say (and why) if you had to advise a client who wants to purchase an NFT collectible.