Richard Boire

Math vs. Data: Exploring the Big-Data Buzz

NO RATINGS
View Comments: Newest First | Oldest First | Threaded View
SethBreedlove
User Rank
Data Doctor
Re: Not so different
SethBreedlove   1/9/2013 7:51:05 PM
NO RATINGS
As mentioned, research in labs and academia are pristine environments.  In business, it is much more messy.  A change in x will cause a change in y, but that might cause an unknown change in A, B,C.   In real life, individuals are not pool balls and may not go in the direction you hit them.  However, we are getting better at predicting.  A lighthouse doesn't get rid of the fog, but it is sure better than no lighthouse at all.  I think this is why five years is considered a long-term business plan here in the U.S.

Noreen Seebacher
User Rank
Blogger
Re: Not so different
Noreen Seebacher   1/9/2013 11:35:01 AM
NO RATINGS
Phil, what would you consider an ongoing issue?

philsimon
User Rank
Data Doctor
Re: Not so different
philsimon   1/9/2013 10:32:57 AM
NO RATINGS
The types of data are new. So are the amounts. Ditto the velocity. But many of the tools and issues are pretty similar to those previous decades.

rboire
User Rank
Blogger
Re: Not so different
rboire   1/9/2013 10:03:27 AM
NO RATINGS
I would agree with you that perhaps the new terms are more consumer-friendly. But I also think that definitions and descriptions regarding predictive analytics discipline have increased significantly due to increased public understanding of the value of analytics. The industry of predictive analytics is no longer the new frontier in business which it was 15 years ago. It is now more mainstream where consultants are attempting to brand the discipline with new terms such as data scientist.  Is that really different than a data miner which is what we called ourselves 15-20 years ago.         

BethSchultz
User Rank
Blogger
Not so different
BethSchultz   1/9/2013 9:18:27 AM
NO RATINGS
Hi Richard. I think one the benefits of framing the predictive analytics role in "consumer friendly" terms like big-data and data science makes the whole discipline more approachable for non-practitioners even if behind the scenes things haven't changed much. That's important in overcoming business resistance to using analytics-based decision making. 

Information Resources
More Blogs from Richard Boire
Just because the nature of data is changing doesn't mean analytical best-practices need to change, too.
Applying domain knowledge to traditional baseball metrics made the difference for the Oakland A's -- and started a trend.
Understanding business processes and industry trends can help improve analytical projects.
Successful data miners require soft skills like an understanding of data, business familiarity, and communications ability, on top of their book learning.
Radio Show
A2 Conversations
UPCOMING
James M. Connolly
Retail Analytics: See Where Style Meets Statistics


12/6/2016   REGISTER   0
ARCHIVE
James M. Connolly
Why the IoT Matters to Your Business


11/29/2016  LISTEN   45
ARCHIVE
James M. Connolly
Will Data and Humans Become Friends in 2017?


11/22/2016  LISTEN   40
ARCHIVE
James M. Connolly
We Can Build Smarter Cities


10/20/2016  LISTEN   31
ARCHIVE
James M. Connolly
Visualization: Let Your Data Speak


10/13/2016  LISTEN   70
ARCHIVE
James M. Connolly
How Colleges and Tech Are Grooming Analytics Talent


9/7/2016  LISTEN   56
ARCHIVE
James M. Connolly
How Machine Learning Takes Handwriting Recognition to New Levels


8/25/2016  LISTEN   40
ARCHIVE
AllAnalytics
A Look at Tomorrow's Data Scientist


8/9/2016  LISTEN   83
ARCHIVE
James M. Connolly
Analytics and the Making of a President


7/21/2016  LISTEN   76
ARCHIVE
James M. Connolly
Analytics: Where We've Been, Where We're Going


7/12/2016  LISTEN   48
ARCHIVE
James M. Connolly
How Predictive Analytics Can Take Your Company to the Next Level


6/28/2016  LISTEN   22
Information Resources
Quick Poll
Quick Poll
About Us  |  Contact Us  |  Help  |  Register  |  Twitter  |  Facebook  |  RSS