Post on 01-Nov-2014
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transcript
#AIIM12
Perspec'ves on Big Data Why Should You Care?
John Mancini, AIIM @jmancini77
DigitalLandfill.org
Era
Years
Typical thing
managed
Best known company
Content mgmt focus
Mainframe
1960-‐1975
A batch trans
IBM
Microfilm
Mini
1975-‐1992
A dept process
Digital Equipment
Image Mgmt
PC
1992-‐2001
A document
MicrosoR
Document Mgmt
Internet
2001-‐2009
A web page
Content Mgmt
Social and Cloud
2010-‐2015
An interacUon
Social Business Systems
Systems of Record
Systems of Engagement
Systems of Engagement
• For the past decade, companies have been accumula5ng data in what we call a system of record. Those who survive going forward will also have systems of engagement – h=p://www.aiim.org/futurehistory -‐-‐ start with evalua5ng how you can have a relevant conversa5on with each individual customer across all channels. And insuring you have the analy5cal capability and the data to support that analysis. That is where the linkage is between the system of record data to system of engagement. On the technology side, we believe the future of handling this volume lies in leveraging the capability of the cloud. • Yuchon Lee, Vice President, IBM
Massive Volumes of Informa'on
• Per Fortune, by 2020, Internet connected devices will grow from 400 million today to 50 billion. These devices will be talking to each other and to the Internet. By 2020, it is also predicted that our smart phones will have the capability of storing and accessing as much informaUon as IBM’s Watson and super-‐computers can.
0% 20% 40% 60% 80% 100%
Structured data
Unstructured data
5 Fully 4 3 2 1-‐Poorly Unsure
Considered overall, to what degree does your organiza'on exploit its informa'on assets for
analysis and decision making purposes?
Source: Online survey of Register readers, 122 respondents, first half of November 2011, Freeform Dynamics
Structured InformaUon i.e., “data”
Unstructured InformaUon i.e., “content” Managed in
ECM & ERM systems
HIGH DENSITY
Managed via tradiUonal BI and Data
Warehousing
Currently unmanaged
Value of InformaUon per Unit to OrganizaUon
BIG DATA
Original concept – Freeform Dynamics
2
3
LOW DENSITY
Social, images, audio, video, text
BIG CONTENT
Key driver #1: COST revoluUonized by cloud, HADOOP, NoSQL
Key driver #2: USABILITY revoluUonized by advances in semanUcs, search, content & text analyUcs, print stream analyUcs, NLP,
and visualizaUon
4
5
6
Volume, Velocity, Variety, Complexity
Systems of Record Systems of Engagement 1
What kinds of business problems can big data help address?
• Modeling risk and failure predicUon • Analyzing customer churn • Web recommendaUons (ala Amazon) • Web ad targeUng • Point of sale transacUon analysis • Threat analysis • Compliance and search effecUveness
Source – Cloudera.com
Vendor opportuni'es
§ Move “Big” value proposiUon from reduced cost to new value § “Big data” vendors – extend reach beyond pure data by
helping organizaUons extract value and extend analyUc techniques to unmanaged unstructured informaUon.
§ “Big content” vendors – extend reach beyond tradiUonal “high-‐value” (largely document-‐centric) content to find value in massive new quanUUes of unstructured informaUon.
AIIM’s Plans – and where you can connect
• AIIM Industry Watch • Late May publish; survey to go live the first week of April. • Those who commit to sponsoring by the end of March
can see the draR quesUons and weigh in. • AIIM Webinars
• Archiving & Governance in the Big Data Era, April 11 • Big Data/Big Content (based on survey), June 20
• Execu5ve Leadership Council • Understanding Big Data and its Impact on Buyer
Behavior • London, Sept 6 -‐ 7 for the European Council • Dallas, Nov 29 -‐ 30 for the American Council • White paper and all deliverables extensively
distributed
Cool stuff
Mining social streams… for predic'ons about the next hit…
nextbigsound.com
Mining social streams…for the best food DishUp.com
Mining social streams…for drug info Treato.com
Using text analy'cs to mo'vate voters
Taking Watson to finance and healthcare
Using sta's'cal analysis to predict tastes