big data innovation
DESCRIPTION
Getting Value out of Big DataTRANSCRIPT
Getting The Most Out Of Big Data
Associate Professor Paul Hawking
“Can the amount of hype about Big Data be considered Big Data?”
What is Big Data?
1997 1998 1999 2001
Big Data is Not New
Cox & Ellsworth“Data sets are generally quite large, taxing the capacities of main memory, local disk and even remote disk. We call this the problem of big data”
Masey“Big Data… and the Next Wave of Infrastress.”
Bryson et al“Very powerful computers are a blessing to many fields of inquiry. They are also a curse; fast computations spew out massive amounts of data.”
Laney3D Data Management: Controlling Data Volume, Velocity, and Variety
Characteristics – V’s
Volume Velocity Variety Voldemort
Big Data
Voldemort – The dark side of Big Data
Data Sources
Big Data
Transactions
Machines
Humans
What is Big Data?
Danah Boyd & Kate Crawford (Microsoft)
Big data is “a cultural, technological, and scholarly phenomenon that rests on the interplay of: Technology: maximizing computation power and algorithmic accuracy
to gather, analyze, link, and compare large data sets. Analysis: drawing on large data sets to identify patterns in order to
make economic, social, technical, and legal claims. Mythology: the widespread belief that large data sets offer a higher form
of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity, and accuracy.
Why the increased interest?
The vendors
Prediction: Customers will leverage existing vendors’ technologies
Business Intelligence Process
1Identify
business issue
2
Formulate business question
3
What information
do I need
4
Where do I find the
information
5
Retrieve information
6Analyse
Information
7Report
answers
8Take
actions
Goals of Big Data
Big Data Analysis
Let’s act on it
What is the best that can happen?
What will happen next?
Why is this happening?
What actions are needed?
Where exactly is the problem?
How many, how often, where?
What happened?
Reports
Ad HocReports
QueryDrilldown
Alerts
StatisticalAnalysis
Forecasting
PredictiveAnalysis
Optimisation
Degree of Intelligence Maturity
Com
petit
ive
Adv
anta
ge
ProactiveDecisionMaking
ReactiveDecisionMaking
Leading Companies
Treacy & WiersemaThe Discipline of market Leaders
Core/Context Framework
Core Engage
Processes that create differentiation that wins customers
Context Disengage
All other processes
Big Data Value = Analysis + Context
Data
Information
Intelligence
Wisdom
Knowledge A contact associated to a Company and all back orders
A Contact
What the company has purchased, what other products they may purchase
Lifetime value of this customer and strategies to deploy to create loyalty
New business strategies, opportunitiesVa
lue
Measuring Success and Value
Overall Success
Implementation Success
User Success
Operational Success
Business Success
• Create a formal, continuous process for measuring success and value generated
• Identify and measure results of each initiative• Establish realistic goals and expectations based on
capability / maturity
• On-time, • On-budget
• User adoption• Usage tracking• User satisfaction
• Productivity improvements
• Process efficiency and effectiveness
• Return on investment• Economic value add• Revenue increases• Cost Savings• Customer / corporate
profits• Enables Business
Strategy and Completive Advantage
Valu
e C
reate
d
Who?
Data Quality
Data Integration
Master Data Management
Meta Data Management
Beware
Big Data
Gartner Hype Cycle
Topic:
Organized byUNICOM Trainings & Seminars Pvt. Ltd.
Speaker name:Email ID:
Paul HawkingAssociate ProfessorSAP Academic Programs DirectorCollege of BusinessTelephone: +61-3-99194031Mobile: +61-419301628Email [email protected]
Paulhawking #SAPVU
