20141111 Idiro_CeADAR_ Data Analytics Case Study_Aidan Connolly

Big Data Analytics

Edward McDonnell Centre Director

[email protected]

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

Copyright © CeADAR 2014 6

Aidan Connolly, CEO


Idiro’s Reach

Idiro have analysed over 12% of the world’s population.


Contagion


Dual-SIM users

● Dual-SIM usage is a major challenge for many mobile operators. ● Challenge: How can we identify dual-SIM users?


Who is spending with my competitor?

What type of

people have

dual/multi Sims?

Why?


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


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


CeADAR Solution: Idiro

By applying machine learning techniques over many different features could detect dual-sim vs. single-sim behavior with very good accuracy

?

Working with CeADAR

• Become a member

• Evaluate an existing

demonstrator

• Propose a new platform

technology project

• Commission bespoke work

• Contact: [email protected]

mailto:[email protected]

Thank you

Samsung users

Apple users

0

1000

2000

3000

4000

5000

6000

Operator Idiro

Marketing Campaign

Over 400% improvement

20141111 Idiro_CeADAR_ Data Analytics Case Study_Aidan Connolly

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