WRG BigData Presentation DonMoody Nov2012

8/13/2019 WRG BigData Presentation DonMoody Nov2012

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"How 'Big' Do I Have To Be To Have 'Big Data' Issues?

Don C. Moody, J.D., M.S.

Don C. Moody, 2012


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1.0: Overview/Agenda


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1.0: Overview/Agenda1.1: Short preso (15 mins!)

Follow-up at lunch or offline

1.2 'Set the table'

Framing the Issue (Perspectives on BD)

How 'big' is data getting? (fun exercise)

A few BD tools/technologies Is BD a real biz issue or just hype?

BDs current popularity wave

Real legal concerns or just Chicken Little?

1.3: Handouts


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2.0: Perspectives on Big Data


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2.0: Perspectives On Big Data2.1 This is old hat!! (See innumerable beer and diapers examples from 1990s

even before Target & pregnancy)

2.2 Framing the threshold question Do I Have to Worry About Big Data legal

concerns? from two points of view:

Small-to-Medium Enterprises (SMEs): (or lawyers representing them)

Large Enterprises/Fortune 1000: I know Im a big company, I knowdata, and (if applicable) I know Im in a heavily privacy regulated area like

health/HIPAA, financial/GLBA, education/FERPA, video history (VPPA), kids(COPPA) but when do I have to worry about separate BD legal issues?

BD legal issues typically center around privacy but also can include:

False/deceptive/unfair business practices

e-Discovery

IP


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2.0: Perspectives On Big Data

2.3 "Big data" is relative term (& somewhat misleading) due to 3 V's:

Scalability of inexpensive technologies (volume)

Availability of many unstructured sources (variety)

Rapid proliferation (velocity)


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2.0: Perspectives On Big Data2.4 Better: "Lotta Data"

Not limited to large enterprises or large individual file sizes (e.g.trillions of small text entries)

2.5 Better Still: "Lotta Messy Data"

Lack of structure huge concern (e.g. 80% of data worldwide isunstructured

Imposing order on chaos (e.g. pattern recognition) is key goal of'big' data analytics


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2.0: Perspectives On Big Data2.5 Perspectives

Small-to-Medium Enterprises (SMEs): (or lawyers representing them)

Cheap IT and clustering = big (volume & velocity)

Prevalance of Social Media = (variety)

Large Enterprises/Fortune 1000:

When data is big enough or detailed enough for:

Temptation to de-anonymize

Likelihood of unintendedpattern reocgition (exceeds reasonable

consumer expectations and/or what Priv Policy says)(FTC)


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3.0: How Big Is Data Getting?


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3.0: How Big Is Data Getting?3.1 Measurement scales (with pragmatic examples and some fun

facts/tidbits for each)

Can be 'big' (if unstructured or high volume):

Kilobytes (Docs, spreadsheets, GIF/JPEGs)

Megabytes (MP3, higher res images)

Gigabytes (PC hard drives, HD video)


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3.0: How Big Is Data Getting?3.1 Measurement scales (with pragmatic examples and some fun facts/tidbits

for each)

Getting 'bigger': (big' but still not expensive!)

Terabytes (enterprise servers, large HDDs)

U.S. Library of Congress had over 235 terabytes of data in 2011 100 terabytes uploaded to Facebook/day

3 Terabyte Seagate HDD available on Amazon for $120 (as of11/01/2012)

AT&T claims to have largest single, unique database (1.9 trillionrows) @ 312 terabytes

]


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3.0: How Big Is Data Getting?3.1 Measurement scales (with pragmatic examples and some fun facts/tidbits)

Definitely 'big':

Petabytes (supercomputers, large virtual "drives")

The total file size of the movie Avatar (incl. encoding for 3-D, IMAX, HD, etc.)constituted over 1 petabyte of data, roughly equivalent to a 32-year long MP3 song.

In 2008, eBay, Walmart and BofA were considered data storage leaders with 4 PB,2.5 PB and 1.5 PB respectively

Now, however, Facebook reportedly has over 30+ petabytes of data in a massiveHadoop cluster

IBM put together a 120 Petabyte (120 million gigabyte) data cluster (virtual drive)using over 200,000 smaller HDDs, equaling a 1 trillion files or 2 billion hour longMP3


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Definitely 'big':

Exabytes (largest individual data sets globally)

Zettabytes (total data currently on Earth projected to be 2.7 ZB)


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Mostly theoretical (for now):

Yottabytes

Bored geeks at play:

Reverse alphabet proposal (X,Y,Z)

Brontobytes

Excellent video demonstration from Univ. of Utah Prof. Chris Johnson

@ TEDx Salt Lake City 2011: http://www.youtube.com/watch?v=5UxC9Le1eOY
http://www.youtube.com/watch?v=5UxC9Le1eOYhttp://www.youtube.com/watch?v=5UxC9Le1eOY


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4.0 A Few Big Data Tools and

Technologies


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3.0: A Few Big Data Tools/Technologies Massively parallel processing v. single supercomputer

Open source BD projects/technologies

Apache Hadoop (application framework facilitating MPP for BD purposes (integratesMapReduce)

Apache Cassandra (distributed DBMS for BD)

Helpful Intro Video on Hadoop: http://www-01.ibm.com/software/data/infosphere/hadoop/

Proprietary platforms (storage management, analytics, DBMS)

Greenplum (acquired by EMC in 2010)

IBMs Big Data Platform

SAPs HANA

MapRs Drill (Hadoop re-done as proprietary platform with value-adds)

Google Dremel
http://www-01.ibm.com/software/data/infosphere/hadoop/http://www-01.ibm.com/software/data/infosphere/hadoop/http://www-01.ibm.com/software/data/infosphere/hadoop/http://www-01.ibm.com/software/data/infosphere/hadoop/


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Getting 'bigger': (big' but still not expensive!)

Terabytes (enterprise servers, large HDDs)

Definitely 'big':

Petabytes (supercomputers, large virtual "drives")

Exabytes (largest individual data sets globally)

Zettabytes (total data currently on Earth = 2.7 ZB)


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5.0 Nailing Down The Real 'Big

Data' Business/Legal Issues


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5.0 Nailing Down The Real 'Big Data' Business/Legal Issues

5.1 Business: All just hype and marketing spin?

Yes! CRM/ERP in 1990s = lots of hype/promise + lots of (expensive)flameouts

No!

Internet closing in on 20+ yrs of mass adoption; meaningful patterns inonline histories now emerging

So much info available now that companies do not have to guess ormake assumptions. Now (like Jeopardy) the only hurdle to an answer isknowiong which questions to ask.

Kinda/sorta: Data is still data, and many traditional data mining techniquesstill apply to 'big' data (e.g. market basket analysis), just thought of in new

ways


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5.0 Nailing Down The Real 'Big Data' Business/Legal

Issues

5.2 BD industry/subsector now getting a lot of press coverage (and money thrownthat way):

IDC Estimates: Market for BD-related services projected to grow from $3.2Bin 2010 to $16.9B in 2015

Time Magazine write-up on extensive use of data profiling analyticsbyObama Camp (Released yesterday)

Obama Administration projected to be spending over $200M on BigData-related projects

Harvard Business ReviewOctober 2012 Expose

BD Legal Practice Groups Being Formed: Law Technology News October2012


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Issues

5.3 Legal:

De-anonymization temptation (e.g. "Database of Ruin")

(Unintended) pattern recognition (e.g. Target example)

Risk v. reward analysis (likelihood of occurring v. severity of harm)


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Issues

5.3 Legal:

Data source type:

search queries

IP addresses (not anonymous!)

log/use data


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Issues

Legal:

Data subject matter:

Financial (GLBA)

Health care (HIPAA)

Video/library histories (VPPA)

Education (FERPA)


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CONCLUSION

Documents

WRG BigData Presentation DonMoody Nov2012