Big Data Analytics - ISIN · Big Data Analytics Edward McDonnell Centre Director...
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Transcript of Big Data Analytics - ISIN · Big Data Analytics Edward McDonnell Centre Director...
CeADAR: Centre for Applied Data Analytics Research
CeADAR is an industry-led
technology centre
for innovation and applied research
that accelerates the development,
deployment and adoption
of Big Data Analytics technology
CeADAR’s industry-defined themes
Visualisation & Analytic Interfaces
• ‘Beyond the desktop’
• Ease of interaction
• Changing user behaviour
• Passive analytics
Data Management for Analytics
• Reduce data management effort for analytics
• Data validation
• Relevance of events to relationships
• Data curation (determining useful data)
• Adaptive ETL (Extract, Transform, Load)
Advanced Analytics
• Causation challenge
• Live topic monitoring
• Social trending and contextualisation
• Continuous analytics
• Social Identity fingerprinting
Governance model: Industry Steering Board (ISB)
ISB is CeADAR’s main governing
body
Independent industry
chairperson
6 industry members
3 PIs
Platform research projects must be approved by ISB
Research projects require ≥ 2 industry member sponsors
ISB allocates resource from core
funding for an initial 6 months
After 6 months:
• The project is concluded •or • 3 month (max) extension
What CeADAR offers The Centre’s work focuses on
developing tools, techniques and technologies
that enable the use of analytics for better decision making
• Applied R&D addressed to specific industry challenges
• Senior R&D staff and software engineers
• Demonstrator rapid prototyping delivered in 6 months
• Demonstrators funded from CeADAR core funds
• Approx. 20 demonstrators per year
• Opportunities to trial existing CeADAR technologies
• Each project delivers: 1. State-of-the-art review 2. Technical specification 3. A demonstrator 4. Industry evaluated demonstrator performance
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Aidan Connolly, CEO
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Idiro’s Reach
Idiro have analysed over 12% of the world’s population.
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Contagion
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Dual-SIM users
● Dual-SIM usage is a major challenge for many mobile operators. ● Challenge: How can we identify dual-SIM users?
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Who is spending with my competitor?
What type of
people have
dual/multi Sims?
Why?
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CeADAR Platform Solution
Key approach: Develop detailed network features and predictive models that facilitate inference of node identity
Example network features: – How people are related in the social graph – Diversity of outgoing/incoming connections – Social influence
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CeADAR Solution: Idiro
Idiro required a solution that could leverage very faint signals in the data – E.g. prepaid.
– No demographic data
– No billing info
– Incomplete networks
Specific challenges:
– High volume telecoms data
– Ability to identify and exploit very faint signals and patterns to detect dual-sim users
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CeADAR Solution: Idiro
By applying machine learning techniques over many different features could detect dual-sim vs. single-sim behavior with very good accuracy
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Working with CeADAR
• Become a member
• Evaluate an existing
demonstrator
• Propose a new platform
technology project
• Commission bespoke work
• Contact: [email protected]
Thank you
Samsung users
Apple users
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Operator Idiro
Marketing Campaign
Over 400% improvement
