Richard (Dick) Fisher Organizations are creating data records at a pace few could have imagined just five years ago - terabytes (1 trillion bytes) now and heading toward petabytes (1,000 terabytes) that may need to be archived or disposed of! This session uses the requirement for archiving and disposition of PeopleSoft records and data elements as one example, plus other real world requirements. Read more: http://www.rimeducation.com/videos/rimondemand.php

1. Cohasset Associates, Inc.
NOTES
Big Data
Requires Big ERM
Session 17 – Panel Discussion
Richard Fisher,
Cohasset Associates, Inc.
and Panel Members
Panelists
 EMC
 Christopher D. Preston
Senior Director, Integrated Technology Strategy
 IBM Corporation
 Jake Frazier, JD, MBA,
Worldwide Information Lifecycle
Governance Solutions
 Autonomy, an HP Company
 Manu Chadha
Vice President of Sales, Americas
Topics
 Where and What is Big Data?
 What Does it Mean to ERM
 Focus - Case Study
y
 Challenges
 Audience Questions
2012 Managing Electronic Records
Conference 17.1

2. Cohasset Associates, Inc.
NOTES
BIG DATA - Where is it?
 Have you done your “Data Map” yet?
 “Buzz word” since 2006 changes to
Rule 26(f) of Federal Rules of Civil Procedure
 Inventory or Roadmap of Electronically Stored
Information (ESI)
 “Big” is relative
 Gigabytes, terabytes, petabytes, exabytes –
Depends on size of organization and
velocity/volume of data
Big Data – What Is It?
Examples
 Large scale e-commerce transactions
 Many large-volume business operation databases or
file-based data records, e.g., HR, accounting,
procurement, etc.
procurement etc
 Social network communications, postings
 Internet text & documents
 Scientific research
 Medical records
 Other?
What Does it Mean to ERM?
 To ERM, Big Data is NOT:
 Business analytics/trends – a typical IT focus for
Big Data
 To ERM, Big Data is:
 Gigabytes, terabytes, petabytes, exabytes of
data with few or no retention controls
 Determining where/how to apply retention:
Archive set
File or data set
Data transaction
 Attributes for search and disposition
2012 Managing Electronic Records
Conference 17.2

3. Cohasset Associates, Inc.
NOTES
Big Data – Case Study
 PeopleSoft HRIS - Current Situation
 340 Gigabytes growing at 15%/yr.
 17,000 tables
 20 tables with 10,000,000 rows of data
, ,
 Over 33,000 data elements
 No current destruction for eligible
records/rows/transactions.
 Archiving is done, but does not solve
disposition problem.
Big Data – Case Study?
 Database Element Retention
Type of Employee Data Retention Period
Name 25 years
Pay Data 25 years
Pay Summary (e.g., W-2) 50 years
Demographics (address changes, etc.) 10 years
Assignments (job class, grade, salary 10 years
changes, etc.)
Time/Attendance Data 7 years
Big Data – Case Study
 Requirements:
 Retention periods vary by need –
from 8 to 25 years or more.
 At what level can retention be applied:
Data base record
Data base row
Database transaction
 How to index/search archived data for
disposition purposes.
 What are industry best practices?
2012 Managing Electronic Records
Conference 17.3

4. Cohasset Associates, Inc.
NOTES
General Requirements & Challenges
 Manage retention/disposition at various
“record” levels:
 Archive set
 File or data set
 Data transaction
 Automation may be mandatory for
classification, retention & disposition in order
to handle the record volume.
 Use “Categorization” or other “Analytics” to
classify/apply retention?
Big Data
Questions?
2012 Managing Electronic Records
Conference 17.4