The document summarizes a meetup about dark data. It defines dark data as data that is collected and stored by organizations but not used for insights or decision making. Examples of typical dark data sources are log files, customer information, previous employee data, and old documents. Reasons why dark data grows include legal risks, lost opportunities, and open-ended exposure. Estimates suggest 80-90% of organizational data is dark. Tips to manage dark data include implementing data governance, ongoing data assessment, retention policies, and specifically auditing dark data for security.

1. Prague Data
Management Meetup
#3
23. 11. 2015

2. Agenda
• About group
• Dark data

3. About our group (meetup)
• Our group is the best
• Everybody is welcomed
• Everybody can bring own presentation to get
feedback of others
• There are no bad data management topics, there
are only bad presentations
• There are no silly question and now it is time to get
some knowledge

4. Meetup Program
Bring our ideas together
Data Lake Meetup
Dark Data Meetup
Data Lake: Pins and Needles
Self-service BI: Street Battle
Mighty Data Warehousing in Oracle Database
Black Data Science
Clouds: DWH & BI in Skies
Sad Stories About DW Modeling

8. •The information assets organizations collect, process and store during
regular business activities, but generally fail to use for other purposes.
Organizations often retain dark data for compliance purposes only.
Storing and securing data typically incurs more expense (and
sometimes greater risk) than value.
Gartner
•Dark data is that which is acquired through various operational
sources but not used in any manner to derive insights or for decision
making.
Technopedia
•Dark data is a type of unstructured, untagged and untapped data that
is found in data repositories and has not been analyzed or processed.
It is similar to big data but differs in how it is mostly neglected by
business and IT administrators in terms of its value
Wikipedia
Dark Data Definition

9. Dark Data is growing…

10. Big Data Definition

11. Typical Dark Sources
Customer
Information
Log Files Account Information
Previous Employee
Data
Financial
Statements
Raw Survey Data
Email
Correspondences
Notes or
Presentations
Old Versions of
Relevant Documents

12. Reasons of Dark Data
Legal and
regulatory risk
Intelligence
risk
Reputation
risk
Opportunity
costs
Open-ended
exposure

13. John Kelly, IBM:
“80-90% of data is 'dark.' What's the cost of not knowing?”
IDC:
“Up to 90% of Big Data is Dark Data “

14. https://www.youtube.com/watch?v=Uou_4k2ECzg

15. Tips to Slow Down Dark Data
Data Governance
Ongoing data
inventory and
assessment
Pruning and
backuping old
data
Retention
policies
Encryption
Specific auditing
of dark data for
security purposes

16. …or do it yourself