Thomas Redman

Garbage in, Garbage out: What It Means for Big-Data Quality

NO RATINGS
View Comments: Newest First | Oldest First | Threaded View
BethSchultz
User Rank
Blogger
Re: Quality personnel
BethSchultz   8/13/2012 10:50:15 AM
NO RATINGS
Seth, and let's not forget that S&P $2 trillion error from last year! I don't know if we can link that to spreadsheets, but certainly there was a data quality issue there with widespread ramifications.

Alexis
User Rank
Data Doctor
Re: Quality personnel
Alexis   8/13/2012 9:57:59 AM
NO RATINGS
The potential errors are mind-boggling, especially from companies that should know better. (ie, a company that specializes in metrics that apparently did not realize how excel truncates numbers after a certain number of digits. yes, this really happened.)

Noreen Seebacher
User Rank
Blogger
Re: Quality personnel
Noreen Seebacher   8/13/2012 9:46:43 AM
NO RATINGS
I'm apprehensive about the numbers of companies that still rely on spreadsheets -- and the potential errors created from less than adequaltely treined employees who use them

SethBreedlove
User Rank
Data Doctor
Re: Quality personnel
SethBreedlove   8/12/2012 2:30:29 AM
NO RATINGS
@ Beth, that's a good question. Big data could lead to big errors.   The more data there is the more potential.  For example, audits of financial instituations can have tens of millions of spread sheets , which any one could have an error.  In Oct, 2011, the German government announced it  €55bn richer after an accountancy error undervalued assets at the state-owned mortgage lender Hypo Real Estate. It was due to a sum being entered twice. 

Richard Cuthbert, CEO of UK outsourcing specialist Mouchel, stepped down after a spreadsheet-based accounting error reduced Mouchel's full-year profits by more than £8.5 million to below £6 million.   Ooops! 

With these spreadsheets being connected to various data bases, a simple error can spread like wild fire. 

BethSchultz
User Rank
Blogger
Quality personnel
BethSchultz   8/10/2012 10:13:06 AM
NO RATINGS
Hi Tom. I'm wondering what you see internally these days relative to how companies handle  data quality and how that might change as big-data comes into play. Do you see distinct data quality groups set up? If not, do you think such would be a necessity going forward?

Information Resources
More Blogs from Thomas Redman
Big-data analytics will help drive necessary change, but data quality will be a hurdle.
You can't make money from poor-quality data that folks don't trust.
Sometimes a well-constructed small sample experiment yields more relevant results than what's pulled out of big-data.
Make no mistake, high-quality data will be an imperative for big-data analytics.
Radio Show
Radio Shows
UPCOMING
James M. Connolly
Hire and Manage a Great Analytics Team


9/1/2015   REGISTER   0
ARCHIVE
James M. Connolly
Use Mobile Analytics to See the Big Picture


8/26/2015  LISTEN   83
ARCHIVE
James M. Connolly
Survive the Digital Transformation


8/18/2015  LISTEN   85
ARCHIVE
James M. Connolly
Health Analytics: Find Data Beyond the Hospital Doors


7/28/2015  LISTEN   47
ARCHIVE
James M. Connolly
Finding Answers Through Prescriptive Analytics


7/21/2015  LISTEN   117
ARCHIVE
James M. Connolly
Visualization: How to Bring Data to Life


6/22/2015  LISTEN   55
ARCHIVE
James M. Connolly
Learn Why Analytics Are at Home in the Cloud


6/15/2015  LISTEN   26
ARCHIVE
James M. Connolly
Analytics: Your Defense Against Cyber Threats


5/27/2015  LISTEN   60
ARCHIVE
James M. Connolly
Big Data & Big Pharma: How Analytics Might Save Your Life


5/19/2015  LISTEN   37
ARCHIVE
James M. Connolly
Live Interviews From SAS Global Forum


4/28/2015  LISTEN   11
ARCHIVE
James M. Connolly
How to Hire Great Analytics Talent


4/23/2015  LISTEN   51
Information Resources
Follow us on Twitter
Follow us on Twitter
Quick Poll
Quick Poll
Like us on Facebook
Like us on Facebook
About Us  |  Contact Us  |  Help  |  Register  |  Twitter  |  Facebook  |  RSS