Data Visualization in Business Analytics

Visual Analytics on Public Sector
Open Access Data
Dr. Andreas S. Maniatis
Commercial Manager / Head of BI
CyberStream LTD
Big Data and Business Analytics: Theory and Practice
Wednesday, October 24th 2012
AUEB – Athens, Greece
CyberStream LTD
The human face of technology …
Systems Integrator
Established in 2000
Strong software
Digital
engineering skills
Signage
Focus on development
of custom & reusable
solutions
Partner relationship with
established technology E-Learning
companies
Involvement in ΒΙ/BS
since 1997
Business process
automation
Unified
communications
Enterprise
networking
Portals
Issues to be discussed
• What Business Analytics are …
• Key usability differentiators for Business
Analytics
• Data Visualization concepts
• Visual Analytics as a key differentiator for
Business Analytics
What Business Analytics are …
• «Business Analytics» refers to the Exploration of
Business Data to improve Decision Making
• Business Analytics answer sophisticated questions,
such as «Why ?» and «What next ?»
• No real «Business Intelligence» without «Business
Analytics»
• Basis for «Predictive Analytics»
You don’t get Analytics with BI
Analytics is Understanding. BI is Presentation.
Visual Business Analytics
Traditional BI
Solves problems
Delivers reports
Unrestricted data exploration
Pre-determined questions
Imports from spreadsheets for answers
Export to spreadsheets for “analysis”
User-driven
IT constrained
Data on demand
Pre-determined dimensions and
measures
Fully integrated, extensive statistics
Limited KPI’s
Events and process-driven
Database dependence
“Solutions” & “Analytic Applications”
“Reports” & “Dashboards”
Trends in Business Intelligence
• Trends in BI are towards analytics
and visualization
– “By 2012, 70 percent of Global 1000
companies will turn to in-memory
analytics as the dominant performance
layer, and they will move away from
building aggregates and summaries and
cubes.”
– Kurt Schegel, Gartner
• Self-service BI, Mobile BI, SaaS, realtime analytics dominate the 2011
agenda
– James Kobielus, Forrester Research
• Trends driven by the fact that current
BI systems do not meet the
operational needs of business users
in a rapidly changing environment.
The importance of senses
•
•
•
•
•
•
Seeing
Hearing
Touching
Smelling
Tasting
6th Sense …
83 percent
11 percent
3 ½ percent
1 ½ percent
1 percent
?
Source: Oklahoma State University
http://www.oces.okstate.edu/washita/uploaded_files/4h_Learning_Styles.doc
The importance of context
Visual Analytics: A Definition
“... the science of analytical reasoning
facilitated by interactive visual interfaces …”
Relative Terms:
• Visual Analysis
• Visual Data Analysis
• Visual Data Mining
Illuminating the Path: Research and Development Agenda for Visual Analytics
James J. Thomas, Kristin A. Cook
IEEE Press, 2005
The Scope of Visual Analytics
Source: http://www.visual-analytics.eu/faq/
Research Fundamentals for Visual
Analytics
Source: http://www.visual-analytics.eu/faq/
The Visual Analytics Process
Source: http://www.visual-analytics.eu/faq/
The Visual Analytics Mantra
Analyze
Show the Important
Zoom, Filter, Analyze Further …
Details on Demand
Visual Analytics: Scope and Challenges
Daniel A. Keim, Florian Mansmann, Jorn Schneidewind, Jim Thomas, and Hartmut Ziegler
Visual Data Mining, pages 76 – 90, Springer-Verlag Berlin, Heidelberg © 2008
Trends in Interactive Dynamics for
Visual Analysis
Interactive dynamics for visual analysis
Jeffrey Heer, Ben Shneiderman
Communications of the ACM , April 2012, Volume 55 Issue 4
Current Challenges in ExtremeScale Visual Analytics
1.
2.
3.
4.
5.
6.
In-situ Analysis (In-memory Analytics)
Interaction and User Interfaces
Large-Data Visualization
Databases and Storage
Algorithms
Data Movement, Data Transport, and Network
Infrastructure
7. Uncertainty Quantification
8. Parallelism
9. Domain and Development Libraries, Frameworks, and Tools
10. Social, Community, and Government Engagements
The Top 10 Challenges in Extreme-Scale Visual Analytics
Wong, Pak Chung
Computer Graphics and Applications, IEEE, July-Aug. 2012, Volume: 32 , Issue: 4
Key usability differentiators for
Visual Analytics
• Factors demanding for usability differentiators:
– Flood of data
• Social Networks, Media (Facebook, Twitter,
LinkedIn etc.)
• Search engines (Google etc)
• Variety of new data types / streams
– Faster cycle times
– New devices (Smartphones, Tablets etc.)
– The introduction of Analytics by itself
– Involve more power users in exploratory data analysis
The Two-seconds Advantage
First to insight; first to action.
“A little bit of the right information, just a
little bit beforehand – whether it is a couple
of seconds, minutes or hours – is more
valuable than all of the information in the
world six months later… this is the twosecond advantage.”
— Vivek Ranadivé,
Founder, CEO, Chairman TIBCO Software
The Power of Visual Analytics
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Dimension-free Data Exploration
Freely explore data without the need for
IT tasks such as creating complex queries,
modeling dimensions, or defining
navigational paths.
Data Mashup
Combine data from disparate sources to
gain a comprehensive view of the
business & make better decisions faster
Predictive Analytics
Spotfire blends powerful models &
predictive analytics into analytic
dashboards & guided apps
Predicted
Outcomes
“What-If”
controls for
users
Predictive
Analytics “under
the hood”
Event-Driven
Contextual Collaboration
SPONTANEOUS AND FREEFORM TEAM
DISCOVERY - SHARED “DECISION SPACES”
DECISIONS WITHIN DEFINED WORKFLOWS
& PROCESSES - ANALYTICS IN PROCESS
THE INDSTRY’S MOST COMPREHENSIVE COLLABORATIVE ANALYTICS
SOLUTION LEADS TO BETTER DECISIONS AND BUY-IN
Enterprise-class
Easy for Everyone, Adaptable for anything: Front Line &
Information Workers, Business Analysts, IT, Developers,
Managers, Executives, & Statisticians
A single, highly-scalable analytics platform empowers a broad spectrum of
business & technical users enterprise-wide.
Mobile
o Ease of use features for
Executives and Business
Managers
o Apple Store download
o Enable Social features
o Expand to Android
based Tablets –
Samsung Galaxy Tablet
Turning a legacy reporting example …
… into an exemplary Visual Analytics paradigm
New Skills for the Data Analyst
• Data Scientist, Analyst or Statistician?
–
–
–
–
–
Technical Skills
Teamwork Skills
Communication Skills
Business Skills (with a little bit of empathy)
Tool Mastery
• StoryTeller?
Institute for Advances Analytics
http://http://analytics.ncsu.edu/
A Visual Narration
Thank you!
Dr. Andreas S. Maniatis
Commercial Manager / Head of BI
[email protected]
http://www.linkedin.com/in/andreasmaniatis
www.cyberstream.eu