Turn your information into a competitive advantage

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Jonas Linders 04.10.2015 (dato)

Turn your information into a competitive advantage

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Jonas Linders

Experience in

• Strategy and Governance: Helping clients with the governance and strategy aspects of their BI initiatives since 2009

• Business Analysis: Engageing in early stages of BI Initiatives facilitating the clients SME’s to articulate objectives and demands since 2005.

• BI Architecture: Designing Data Warehouse and Business Intelligence solutions for our clients since 1998

Education Role Industries

M.Sc Informatics Solution Area Manager

BI & Big Data Analytics

•Manufacturing •Transport & Logistics •Utilities •Telco •Retail •Government •Health •Banking

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Agenda

Big Data Definition

BI Scenarios

Driving Forces

Data to Diamonds

Big Data Lab

Q & A

1

2

3

4

5

6

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Big Data Analytics is strategic

300 600 400 250 1160 900 240 350

• Big Data makes it possible to know, predict

and influence events that determine the

success of your organization

• Using data to help our clients gain insights into

the people and things important to them

• Use those insights to improve business

processes

4000 Members in the Data Management, Business Intelligence and Analytics space

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The BI Scenarios

Harmonization

Integration

High

Low

High

Domain

Applications

Performance

Management

Information

Discovery

Enterprise

Reporting

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Big Data Analytics – Information Areas

Business

Things

People

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Source: CGI Voice of Our Clients (2015)

Four key “change” initiatives emerges as priorities

41%

Integrating data

across silos to

enable

“360

views” of

customers,

facilities, and

other elements

360 ◦

Enterprise

Views

34%

Using data from

sensors (IoT) to

improve

operational

effectiveness, e.g.,

predictive

maintenance

Harnessing the

Internet of Things

15%

Monetizing data

by bringing new

and innovative

information

services to market

Monetization

(New data-based services)

62%

Improving

“digital

customer

experience”

using insights

from customer

data

Digital Customer

Experience

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Consumers have changed !

Consumers infidelity 61% of 18-24 year olds say they change more often brand than a

few years ago

Consumers opinions 62% of Consumers have already given up buying a product after learning of online

opinion.

Social networks influence 91% of users "share" on the internet at least once a week

Real time obsession

•247 billion emails •16 billion SMS

•90 million Tweets sent per day worldwide

Individualization of the consumption

Multi-devices and multi-connected consumers

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New opportunities, and challenges, are growing fast

Internet of Things

Manage, optimize,

and monetize

sensor and machine

data

Cloud

Step-function

increases in

efficiency and

flexibility

Mobility

Deliver dashboards

and analysis where

people need them

Predictive

Analytics

Improve business

processes with

sharper predictions

of human and

machine behavior

Self Service BI

Power in the hands

of business

Hadoop and

noSQL

Managing huge

complex data

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Data about Things

•

ThyssenKrupp Elevators wanted to find ways to monitor their install base of 1.1 million elevators world wide.

•

Later generation of elevators provided a rich varity of sensors.

•

Internet of Things platform handles the collection of data, processing of events and classification of alerts for monitoring

•

Analytics provice the train and refine the predictive models

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Data about People

•

Liseberg wanted to use the Mobile Channel to have a dialogue with their customers

before, during and after the visit to the theme park.

•

Liseberg wanted to facilitate the visit to the park by giving assistance to the visitors about direction, attractions, queue-times and the location of family/friends

•

Beacon Analytics provide insights on

•

Number of visits and visitors

•

Queue time and durations

•

Movements and paths

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D2D Methodology Framework

Vision

Shape

Change

Deliver

Maturity & Quality Scan

Roadmap & Blueprint

Scan Project Scan Service Scan

•Strategy Study •Feasibility Study •Business Case •Requirements Analysis •Architecture Design •Build IM Foundation •Build BI & Analytics •Test & Transition

•Application Mgmt. •Data Resourcing •Information Delivery Strategy Assessment Roadmap & Blueprint

Assessment Compliance Audit Service Evaluation

Plan Do Check Act

BI Management

BI Governance

Control Funding Define Vision Manage Programs Develop User Skills Methodology Leadership Technology Blueprint Establish Standards

“The CGI Data to Diamonds Framework is the most comprehensive BI methodology I have seen, after meeting lots of BI vendors and systems integrators worldwide.” - Nikolaus Walkowsky, DHL Express Global BI Manager

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A Data to Diamonds proposition

CGI Big Data Lab

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The Challenge

•

Articulated idea of the value

•

Available data

$

•

ROI

•

Resources requirements

•

Tech and analytical competencies

•

Technical environment and tools

•

Proof of Value

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Technical Environment and Tools

File Sources Database Sources Real-Time Streaming Sources Data Lake (Hadoop + RDMS) Decision Engine MDM Party, Product, References EDW Integrated Structured Enterprise Data Data Marts Reporting & Analytical Operations Insights Mart Information Access Dashboards, Reporting, Analytics, Mobile Visualization, Operational Access Business Integration

Data Governance Metadata, Data Quality, Lifecycle Management Data-Driven Business Insights

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Competencies

Big Data Lab

AUTOMOTIVE TELCOS FINANCE

Consumption Ad Hoc Analysis Root Cause Analysis Multi-Device Provision

Methods / Insight Generation

Descriptive Analytics Predictive Analytics Behavioral Analytics Data Management Multiple Source Acquisition Data Integration Data Quality Assurance Data Sources 3rd Party Data Providers Unstructured Data Structured Data Streaming/ Voice Data

User Experience Leads

Big Data Designers

Industry Experts

Data Scientists

Data Architects, DBA‘s ETL Designer / Developer

Data Integration Experts

Data Architects, DBA‘s ETL Designer / Developer

Data Integration Experts

… S ol uti on & T ec hn ic al A rc hi tec ture P e rf o rm a n c e E ng ine er

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Delivering valuable Insights from Data

• Collaboration – combine understanding of

the business domain, and the technical side of data and systems.

• Evolutionary approach – leveraging Big

Data opportunities, whilst safeguarding investments made in the past.

• User experience – users will adopt what

they can use and what brings them value. • Agility - highly adaptive to changing

business environment and user needs. • Sustainability – ensure service levels

beyond business expectations against affordable cost levels

Business understanding Data understanding Data preparation Modelling Deployment Evaluation Data

SYSTEM ≠ INSIGHTS

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Examples

Improved diagnosis,

leveraging health

device analytics

Finding the influencers to attract new customers

Dynamic pricing in

the on-line store

Influence driver

behavior, improving

safety and saving fuel

Localize and predict

water leakage

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Ministry of Infrastructure

• Prior to a renovation of the Velsertunnel the Ministry of Infrastructure wanted to

investigate if it was possible to develop a model that predicts traffic flow by using Big Data technologies and a combination of internal and external data sources.

• Collaborating with customer SME’s utilizing our Big Data Lab and using Proof of Value methodology.

• Resulted in a predictive model for traffic in a road network based upon 2 years of internal and external data covering +50 variables allowing both Basic Trend Forecast for traffic intensity and predicting impact of external factors.

• Next steps are to increase quality and availability, augmenting by new datasets and developing new tools for computing traffic intensity on a route.

Predicting traffic congestions

Dataset Lusdata A22 L Lusdata A22 R Lusdata A9 L Lusdata A9 R Lusdata N246 L Lusdata N246 R Lusdata N197 L Lusdata N197 R Incidenten KNMI Griep Google trends NS Matrix Feestdagen AEX

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Vitens

• Water supply companies in Europe invest 20 billion euros annually to maintain the reliability of their networks.

• Leaks present problems for customers and have a major impact on the operations.

• Vitens wanted to explore how to leverage available data to better predict and localize leakage in the network.

• Collaborating with customer SME’s utilizing our Big Data Lab and using Proof of Value methodology to Identify predictive indicators for leakage detection.

• Resulted in a predictive model that enables leak detection within a 2.5km radius in 50% of cases (was 20km).

• Enabling better customer service and saving millions in preventing interruptions.

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Wrap up

$

• CGI Big Data Labs available in

 Netherlands

• IBM • Microsoft

 France

• Amazon • Cloudera

 Germany

• Teradata

 Czech republic

• Open Source

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Jonas Linders

Solution Area Manager, BI & Big Data

Mobil: +46 733 983305

E-mail: jonas.linders@cgi.com

Vil du vide mere?

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Data and Analytics at CGI

Hundreds of successful projects across all industry sectors and

functions

Improve the customer experience

Create business value from data about

Things and People

A $900 Million Business in 2014 Reduce the costs and complexity of managing ever-growing volumes of data A proven Big Data,

analytics and BI delivery methodology called Data2Diamonds Improve citizen safety and security

A global practice team, and practice leadership council

Over 4,000 Members

skilled in delivery Embedded in many of CGI’s IP products,

including Advantage, HERO, Collections360, Trade360 and Strata

Improve patient care