edward.mcdonnell@ucd.ie

data analytics:evidence–based decision making

CeADAR: centre for applied data analytics

CeADAR is amarket-led centre

focussed on thedevelopment and

deployment ofbig data analytics

technology and innovation for the

competitive advantage

of its member companies

CeADAR: bridging the gap

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University CeADAR Enterprise

Basicprinciplesobserved

System proventhrough fullcommercialapplication

Technologyvalidated

in lab

Systemprototypedemo’ed

in operationalenvironment

• Basic research& technology creation

• Market push• Technology driven

Product developmentand commercialisation

• Application development& proof of concept

• Business-value driven• Market pull/need-driven

CeADAR offeringsadvisory

business seminars

demonstrators

collaborative work flagship projects

bespoke solutions

customer exploration tool

A data analytics tool to allow users, without significant data analytics expertise, to explore any customer segments that they have themselves manually defined in an ad-hoc manner, e.g. for a mobile phone operator, this could be how many women between the ages of 16-20 use their services?

real-time analytics of big fast data▪ High-throughput scalable clustering for data streams▪ Live data capabilities to advanced analytics tasks▪ Solution processes > 3M entities/minute (50K/sec)▪ Implemented on Apache Storm with commodity hardware

Applications: ▪ SPAM detection in networks▪ fraudulent behaviour detection▪ identifying emerging topics in

content streams▪ detecting new user behaviour

and patterns

contact centre analytics

Text stream

Issues and

alerts

Automatic speech-to-text transcription Topic modelling

▪ Automatic topic and issue extraction over large volume audio dialogue

▪ Alerting to new and trending topics and tracking of known topics

▪ Applications– contact centre data– online video transcription data– large-volume speech audio domains

CrowdTrack: location-based analytics

DocoPoolMarket needMany businesses store pools of information-richtext in their systems – such as reports,customer reviews, user comments. Insights can be uncovered by analysing these textsources to discover underlying hidden topics or trends.However manually examining such large corporais often prohibitive

Key features• Easy-to-interpret visualisations• Drill-down on document details for deeper

analysis of topics• Specialist or domain specific word exclusions • Flexible document upload (.txt, .pdf and .docx)• ‘Save’ facilities to allow revisiting of explorations

SmartAd: optimising marketingEach advertising channel has different characteristics of form, audience, and customer interaction data. Channels & campaigns interact. Businesses need to analyse these interactions to plan advertising campaigns

SmartAd fuses the information from all channels and creates a model of the system of mutual influences

SmartAd visualises the interactions between different influencer channels and a target channelThe importance of each channel is given by its size. The distance from the target e.g. site visits represents the confidence in the result

OverviewDevelops new techniques and methods to identify users across disparate social networks based on both network-based metadata and content-based features

Applications• Social fingerprinting: identifying

individuals across different networks for user validation, user profiling, fraud prevention etc.

• Identification of domain expertise e.g. for social recruitment or expertise discovery

social media analytics

Nudge Along: changing user behaviours

ApplicationsThis work benefits any company whichwishes to make sure that theircommunications with customersproduce the required or expectedoutcome. For example, the ability tochange user behaviour is of interest toany company that wishes to see theeffects of a marketing campaign, or acampaign to get staff to save energy intheir offices by switching off lights etc.

OverviewMeasuring the success of any analytics-driven project requires looking beyond the insights that are produced to ways in which these insights are communicated and delivered to ensure that behavioural change takes place

BlockChain: comparison of realisations

deep learning▪ traditionally, pattern recognition problems have

been solved using domain knowledge and feature engineering

▪ manual feature engineering is greatly challenged by big and diverse data sets

▪ deep learning is an unsupervised feature learning paradigm

▪ goal is to assist our industry members in understanding potential uses of deep learning and when this approach is best

Synthetic dataset generator

Logo recognition (Look And Learn)

Heineken

Coca-cola

Coca-cola

No-logo

• Track brand mentions• Improved sentiment analysis• Measure sponsorhip ROI• Find visual influencers• Identify moments of consumption

Beyond the DesktopVoice-controlled access to KPIs

www.ceadar.ie/outputs/our-demos/▪ customer analytics

▪ real time analyticsfraudulent behaviour detection

identifying emerging topics

detecting new user behaviour

▪ contact centre analytics

▪ social media analyticsSocial fingerprinting

Domain expertise

▪ text analytics

▪ Location-based analytics

▪ sentiment analysis

▪ video & image analytics

▪predictive analytics

▪deep learning

edward.mcdonnell@ucd.ie

data analytics:evidence–based decision making