2. Big Data in one sentence
Gartner
“Big data is high-volume, high-velocity
and high-variety information assets that
demand cost-effective, innovative forms of
information processing for enhanced
insight and decision making.”
3. Purpose of dissertation
Is to investigate how perception of Big
Data concept changed over the time and
how Google and other company monetise
this unbelievable hidden value inside Big
Data.
4. The Progress of Big Data
Growth
Employee generated data
User generate data
Machine generated data
5. The ownership of Big Data
Who owns the data?
Is this a Division that collects the data; the
business as a whole or the Customer whose
data is collected?
Forrester believes that for Data Analytics to
unfold its true potential and gain end-user
acceptance, the users themselves must
remain the ultimate owner of their own data.
6. Application Delivery
Strategies
“ Trough 2003/2004 practices for resolving e-
commerce data volume, velocity and variety
issues will become more formalised diverse.
Increasingly these techniques involved
tradeoffs and architecture solutions that
involved /impact application portfolio and
business strategy decisions”
Gartner Jan 2001
7. Case study
Weather models
There are satellites going around
the earth that are measuring high and low
pressure zones.
They use sophisticated algorithms to
determine when those zones are moving and
what the weather patterns are going to look
like.
8. Case study
(Continued)
Walmart’s stock control
This retails stock analysis is based on
weather – hurricanes in particular.
All the normally expected sales products
were on the list, but there was one
consistent entry that they didn’t expect it -
strawberry pop tarts.
But it turns out that strawberry pop tarts
consistently go up in sales when a hurricane
is coming .
9. Case study 2
Wine stock
Grocery stores typically have wines in the
10-$ range,25-$ range and 45-$ range.
The truth is that nobody buys the 45-dollar
bottles, but just having them on the shelf
increases the sales of the 25-dollar bottles
because people always want to buy the middle
solution.
10. Secondary Research
–Main Findings
Important of common business definitions
Technical requirement for successful Big
Data Management (BDM)
Merge of Big Data (BD) and Big Data
Management (BDM)
Driving source of Data Management
Value of Data Analytic
11. Primary Research
–Progress
Big Data immerge as immature discipline
with hidden value
Necessity of Technical approach in Data
Management
Data Analysis as key factor for Big Data
Management
12. Plans for Completion/Areas for
Further Investigations
Further investigation on Big Data’s case studies
and academic journals.
Investigate the potential of social media
marketing as part of the Big Data revolution.
Answering the question of “ What is the future of
Big Data?”
Highlight the problems with Big Data
Conclusion and recommendation
