Andy Koronios - School of Information Technology and Electrical

advertisement
Data Science Education
Prof Andy Koronios
Head
School of Information Technology & Mathematical
Sciences
Big Data – ‘Virtual trail of physical reality’
The Internet of Things
Everything, Everywhere….
An Intelligent, Instrumented
& Interconnected world!
2.2 Billion People use the Internet
60 % of Australians used it today
Big Data… Everywhere!
All these are widely available & virtually free
‘Data Scientists’ are not widely available
and certainly not ‘free’
“Data Scientists are better at
statistics than software
engineers and better at
programming than statisticians”
“they make discoveries while
swimming in data”
Data Science: A Multidisciplinary Activity
Data Sciences’ Value Chain
Data Capture
Data Mgt
• Transactions
• Social Media
• Stream Data
o Environmental
o Industrial
o GPS
o Image/Video
• Exhaust Data
o Network data
o System logs
• High rate financial data
Data Storage
& Access
Analytics
Application
Evaluation
Data Sciences’ Process Model
Data Capture
Data Mgt
•
•
•
•
•
Data Storage
& Access
Integration
Security
LCM
MDM
Data Quality
Analytics
Application
Evaluation
Data Sciences’ Process Model
Data Capture
Data Mgt
Data Storage
& Access
•
•
•
•
Analytics
Hadoop HDFS
Map Reduce
DWH
Federated Discovery &
Navigation
Application
Evaluation
Data Sciences’ Process Model
Data Capture
Data Mgt
Data Storage
& Access
Analytics
Application
• Descriptive Analytics
o Association Rules
o Sequence Rules
o Segmentation
• Predictive Analytics
o Regression
o Classification
•
•
•
•
Decision Trees
Neural Networks
Text Analytics
Real time Analytics
Evaluation
Data Sciences’ Process Model
Data Capture
Data Mgt
Data Storage
& Access
Analytics
Application
Evaluation
• Discussion of Insights with
domain experts;
• Running experiments at scale;
• Operationalising the Models;
• ROI calculations
• Business Case Development
• Implementation Issues;
Data Sciences’ Process Model
Data Capture
Data Mgt
Data Storage
& Access
Analytics
Application
Evaluation
• Monitoring;
• Model Optimisation;
• Evaluation of initiative
Attributes of a Data Scientist
1. Communication Skills are
underrated;
2. The biggest challenge is not
modelling, it is collecting and
cleaning;
3. A Data Scientist is better at statistics
than a SW engineer and better at
SW engineering than a statistician;
4. A curiosity about working with data is
a quality better than technical skills;
5. Good storytelling is a must.
6. The area is nascent and the role is
freeform – good time to join;
https://s3.amazonaws.com/leada/handbook/Handbook_Pt1.pdf
Ask the right Qs * Analyse data * Build statistical models * Developing data apps
A Very Rare Creature Indeed!
“a hybrid of data hacker,
analyst, communicator, and
trusted adviser…”
Data Scientist Employment Growth
The U.S. could face a
shortage by 2018 of
140,000 to 190,000
people with "deep
analytical talent" and of
1.5 million people
capable of analyzing
data in ways that enable
business decisions.
(McKinsey & Co)
Big Data and its Impact
Circa late 2012…..
…. ‘there are no university programs
offering degrees in data science’…..
HbR, 2012
Data Science degrees Today
US Universities
•
•
•
•
•
•
•
•
•
North Carolina State
Stanford
UC Berkley
MIT
North Western
Washington
George Mason
NY
Etc…
Australian
Universities
•
•
•
•
•
UniSA
Deakin
Macquarie
UTS
……+++
Certification Programs
•
•
•
•
•
EMC Data Science Associate (EMCDSA)
Cloudera CCP-Data Scientist
Insight Data Science Fellows Program,
SAS
Institute for Data Science and Engineering
More than 250 universities World wide now offer some courses in Data Science & Big Data
Late in 2013
UniSA MDSc - Key features
• Suite of nested programs developed in
conjunction with the Institute of Analytics
Professionals of Australia (IAPA) and SAS,
industry leader in business analytics
• Available face-to-face or entirely online,
part-time or full time
• Emphasis on professional practice
• Technical skills in Data Science as well as
project management, communications
and visualisation
School of Information Technology & Mathematical Sciences
Entry pathways
Bachelor degree
in any discipline
(plus relevant work
experience)
Graduate
Certificate
Bachelor degree in
Information Technology OR Mathematics
Graduate
Diploma
Master of
Data Science
School of Information Technology & Mathematical Sciences
Program structure
Partnership with SAS
• Benefits:
– Licence to use SAS software in a number of courses.
– SAS certification for graduates of the Master program.
– Eligibility for placement in the final semester through
SAS Work Placement Program.
• Approximately 20 placements a year across Australia.
• A good final year student in the Master of Data Science should
have a good chance of obtaining a placement, but it cannot be
guaranteed.
School of Information Technology & Mathematical Sciences
Data Science Professional Development
Program Student Demographics
• Variety of backgrounds, mainly technical
– Engineers, Mathematicians, Computer Scientists,
Finance specialists, Marketers
•
•
•
•
•
•
•
Mostly part time/online;
2/3 ‘Out-of-State’;
2/3 Male;
Median Age 39;
Mostly employed in similar role (mainly BI);
Highly motivated;
Already in demand.
School of Information Technology & Mathematical Sciences
Download