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Atos vision & concrete examples to support your Big Data projects
Ascent – Journey 2018, the 3rd digital revolution, agility & fragility
Hadoop Self-Service
Industrial Data Analytics
The team for our today’s discussion
▶ Arnaud Bertrand, Group Senior Vice-President, Head of Big Data
▶ Guy Le-Roux, Service Line Big Data & Security, Solutions Manager
▶ Mathias Kluba, Service Line Big Data & Security, BigData Expert
▶ Pascal Pando, Head of Analytics Offerings
2
Agenda
▶ Ascent – Journey 2018, the 3rd digital revolution, agility & fragility – Arnaud Bertrand
▶ Hadoop Self-Service demo – Mathias Kluba & Guy Le-Roux
▶ Industrial Data Analytics – Pascal Pando
3
Introduction
▶ Digitalization is on every customer’s agenda
▶ One of the key objectives of Atos for 2015 is growth - which can only be obtained by differentiation
▶ Every year over 100 innovation workshops are organized with key customers - but still some clients are finding Atos not innovative enough
▶ Journey 2018 is the opportunity to go one step further by properly using unique content
▶ The content of Journey 2018 is not produced in isolation – it is the result of 5 years of work by 1 hundred members of the Scientific Community coming from all service lines and GBU’s, exposed in their day jobs with customers.
Siemens-Atos Alliance, a strategic partnership geared to generate significant joint innovation worldwide
Several of our major customers have agreed to share their vision with us. including the International Olympic Committee with Agenda 2020. Shell have also shared their IT Vision with us as part of our Strategic Relationship.
With Siemens we have launched several large R&D projects on remote service and Industrial Data Analytics and Smart Data to accelerate our progress in solving the key technological challenges you will find in Ascent Journey 2018.
Thierry Breton
Chairman and CEO, Atos
The 3 Revolutions in Digital Technology
Electronic Digital Computer
Improvement of accounting tasks, mainly using a printed format
World Wide Web
Instant access to information, on screen
Internet of Everything
© Atos
The 4 Mega-Trends
Economic Sustainability Energy shortages - renewable energies - smart grids - end of labour - debt reduction - sharing economy models - corporate social responsibility and governance - IT for free …
Trust Snowden disclosures - security and privacy - Heartbleed bug - taxation avoidance – open source/data/innovation/standards - patriot act …
Globalization The world’s center of gravity is shifting towards Asia-Pac - new business models – crowd funding - massification / tailored solutions - off/near/on shoring …
Demographics Africa growth - concentration in very large cities - aging population - social inequalities - Arab Spring - jobs of the future …
Journey 2018 The 3rd Digital Revolution
© Atos
© Atos
Journey 2018 Data Lifecycle
An “Economy of Data” organization targets potential users and providers of data to form a multi-sided market, building shared data
asset platforms to be used by the participating players
Economy of Data
Platform
SIDE
1 SIDE
2 Merchants (2) Users (1)
Payment System
Services
Data
© Atos
An “Economy of Data” organization targets potential users and providers of data to form a multi-sided market, building shared data
asset platforms to be used by the participating players.
Economy of Data
Margin Volume
Negative
Stage 1: Inception
Target growth on the platform at low or zero cost to user to drive adoption.
SIDE
1 SIDE
2
Margin Volume
Negative
Stage 2: Add new market
Tipping point reached where users see platform for first market as key; this attracts secondary markets.
Stage 3: Maturity
Margin Volume
Negative
Additional new markets and increased volumes help raise business margins.
© Atos
A new dimension of vulnerability introduced by other trends (external hosting/cloud, OT/IT convergence, the Internet of Everything etc.) and a new quality of (commercial) Cybercrime makes Security a top priority – boosting (invests into) the security market
and driving technical innovation as well as a new level of cross-party defense collaboration.
Digital Security
Some main trends:
Security analytics to detect threat patterns proactively based on Big data.
Application shielding (additional layers of defense).
Multi device authentication and distributed scoring engines (Adaptive authentication).
Trusted Information Brokers (secure exchange of information between organizations in a borderless environment).
Cyber ecosystems (automated collective action as a response to a vulnerability or threat)
Perimeter Security
2008
2018
1998
© Atos
Reactive Analytics Proactive Analytics
Impact of Decision Support
Change R
ate and Q
uantity of D
ata
low
high
© Atos
Analytics and Visualization
Some main trends:
Data processing tools
Visualization tools: data “movies”, 3D displays, interactive UIs
Scalable platform allowing management of sensitive data feeds
Security-by-design platform and trusted governance framework
Messaging and brokerage layers
Data scientists
Data analytics goes far beyond the mere aggregation, processing and reporting of large volumes of data. It identifies underlying structures and otherwise hidden
meanings across increasingly diverse and apparently disparate data sources using new visualization techniques to bring clarity to underlying complexity.
Adaption on Feed-
back Decision Impact Analysis
Prescriptive
Scenario Prediction
Fore- casting
Predictive
Statistical Analysis
Query Drill Down
Diagnostic
Standard Reports
Ad Hoc Reports
Descriptive
Take away
▶ Convergence happens right now
▶ Atos can help you to bridge
▶ example : From corrective maintenance to predictive maintenance
15
Thank you
16
Hadoop Self-Service Alien4Cloud
GeoLive
Guy Le-Roux, Service Line Big Data & Security, Solutions Manager
Mathias Kluba, Service Line Big Data & Security, BigData Expert
AUGMENT DATAWAREHOUSE
CAPABILITIES
STREAMLINE BIG DATA
DEPLOYMENTS
BOOST REAL TIME IT
RESPONSIVENESS
ACCELERATE INNOVATION
WITH HPC & HPDA
INCREASE CUSTOMER
ENGAGEMENT
ACCELERATE BUSINESS
REINVENTION
STRENGHTEN OPERATIONAL
EXCELLENCE
ENFORCE TRUST &
COMPLIANCE
What Business expects from IT Agility| Efficiency | SLA
18
We need flexible Hadoop
for a PoC or a Project
Actionable IT Service Catalog
On-Demand Portal
Hadoop Self-Service
Public Cloud Private Secured
Cloud
Business Users
Our budget is different
for a PoC or a Project
We need distinct SLA
for a PoC or a Project
We need analytics &
access to various data
Analytics, Machine Learning, Realtime
Data Lakes + API
Hybrid or Multi-Cloud
Service Segregation Data Segregation
What Business expects from IT A global Enterprise Benefit : Avoid shadow IT
19
Territory Data
Local only Exportable
SITE or Country#A
Territory Data
Local only Exportable
SITE or Country#B
GLOBAL IT 1. Local data exported at
global level
2. Local data aggregated by global IT
3. Aggregated data processed globally
4. Processed data remotely visualizable for analysis
Visualization Visualization
D a t a L a k e
More in-memory processing power
Mixed data (local + open)
More generated value
Valuable aggregated / processed / analyzed data
Aggregation Processing
Analysis
Aggregation Processing
Analysis
Hadoop Self-Service: BigData becomes accessible
# INDUSTRIALIZATION FROM GEEK TO ENTERPRISE APPROACH
#ECONOMIC REPLACE EXPERTIZE WITH STANDARD IT OPERATIONS
#CHALLENGES
#FASTER ROI RAPID INSTANTIATION OF NEW PROJECTS
#BUSINESS ENABLER FROM LEGACY IT PROCESS TO AGILE VALIDATION OF NEW BUSINESS TRACKS
#Big Data must be accessible and consumable by employees far beyond the walls of the IT department
Alien4Cloud : remove the shadow IT
▶ Accelerate development and deployment across the application lifecycle
– « Ready to use application » available in minutes (on VMs), or seconds (through containers infrastructure)
– Operational requirements embedded into components packaging
▶ Accelerate time to value & improve applications development lifecycle
– Innovation booster through self-service technologies onboarding
– Applications quality improvement from dev to prod
– More applications or more features handled with the same setup
▶ Ease enterprise norms adoption and applicative standards enforcement
▶ Reduce costs and move Applications faster to Cloud, and between Clouds
▶ Recover from shadow IT through Cloud self-service, yet managed approach
Develop Test Deploy
Monitor Repair, Scale
Update
Our today’s first demo Multiple data lake with TIBCO software
22
Our today’s second demo Hadoop Self-Service
23
Thank you
24
IDA : Industrial Data Analytics
Pascal Pando, Head of Analytics Offerings
26
20/03/2015
26
Data Analytics fueling business change
March 2015
Agenda
▶ Staying competitive in a fast-changing world
▶ Atos Big Data Analytics capabilities
▶ Big Data Analytics in action powered by Atos
▶ IDA Platform Services : value chain
▶ Why Atos
Data Analytics, Cloud & Mobility Key for the New Data Value Chain
Real-time Contextual Mobility
+
+
Retail
Manufacturing
Government
Healthcare
Telco
Financial
Energy
New insights and business opportunities due to three key factors
Analytics is the key enabler of change and the cloud helps to accelerate
Provision of the right services, at
the right moment to the
right person
Impact felt in every sector
Operational & decision
support
Digital transformation
Modernization of Information Management Environments
Cloud-based BI & Analytics
1
Driving the need to analyse and harvest
Customer Data
Citizen Data
Employee Data
Enterprise Data
Machine Data
Internet of Things
Personal data
economy
Open data
New business opportunities
Continuous optimization
Agility & Cost Optimization
Transport
Business Innovation
Value
Generation Data Analytics Data
Business Insights
28
2 3
4
How to Enable the Data Value Chain?
29
Business Innovation
Data
Analytics Data
Business Insights
Customer engagement
Business reinvention
Operational excellence
Trust & Compliance
Business Economics (CapEx, OpEx)
Streaming Data
(e.g. sensor)
Feed
Batch Data
(e.g. raw, historical)
Feed
Enablement of
Confidential / © Siemens AG & Atos 2013. All rights reservedPage 1
VS-Story: Services to minimize cost and
maximize utilization for our Industry customers
Optimized OEE
Improve quality
Improve speed
Improve uptime
Initial OEE
Depre-ciations
People
Mainte-nance
Energy
Optimized OPEX
Reduce maintenance
costs
Improv e energy
efficiency
Initial OPEX
Value proposition of VS serv ices
• VS provides services to address improvement levers for OPEX and OEE
• VS creates sustainable results trough long term customer relationships and in -depth vertical know-how
• VS enables the customer to cope with challenges in a rapidly changing environment
Minimize Input: Reduce costs of operations (OPEX)
Maximize Output: Improve overall equipment effectiveness (OEE)
• Transparency
• Optimized
assets
• Energy
management
• Transparency
• Condition
monitoring
• Predictive
maintenance
Achieved
utilization
• Training
• Maintenance
Processes
• Monitoring
• Simulation
• Analytics
• Process
optimization
• Decision
support
• Trans-
parency
• Stabilize
operation
• Trainings
Planned
downtime/
add.
potential
Machinery Assets in the Field
Business Improvements
Value Generation
Analytics Use Cases
Analytics Applications
Business Functions
D
riv
e
D
ete
rm
ine Prescriptive
Analytics what shall we do
Diagnostic Analytics
why did it happen
Descriptive Analytics
what is happening
Predictive Analytics**
what will happen
• Customer
• Country
• Market
• Competitor
• Operations
• Inst. base
• Product
• Process
• Financials
• Trends & Scenario
Implemented with
▶ Staying competitive in a fast-changing world
▶ Atos Big Data Analytics capabilities
▶ Big Data analytics in action powered by Atos
▶ IDA Platform Services : value chain
▶ Why Atos
Agenda
30
Data Analytics Framework
Workflow management
IT Infrastructure
Atos Industrial Data Analytics initiative scope
31
▶ Modular and service-oriented - Flexibility - No vendor-lock in
▶ Workflow-based - Module / service
orchestration - Optimal support for different
analytics use cases
▶ Multiple operation modes - Cloud (public, private,
hybrid) - On-premise
▶ Integrated security - Protection of data at rest and
in transit, during the whole lifecycle
- Protection of algorithms / models
▶ Compliance to industry standards - Device connectivity
Feed
Feed
Data Business
Innovation
Value
Generation
Data
Analytics Business
Intelligence
Data Integration
Ph
ysic
al D
ata
In
teg
ratio
n
Vir
tual D
ata
In
teg
ratio
n
Data Management
Data
Str
uctu
re m
od
el m
gm
t.
Str
eam
pro
cessin
g &
CE
P
Lo
w in
form
atio
n d
en
sity
/
Tim
e s
erie
s s
torag
e
Hig
h in
form
atio
n d
en
sity
sto
rag
e
Data Modelling & Analysis
An
aly
tical m
od
el m
gm
t.
Data
min
ing
/ m
ach
ine le
arn
ing
Natu
ral la
ng
uag
e p
ro
cessin
g s
earch
Reaso
nin
g /
Sem
an
tics
Op
timis
atio
n &
Rem
ed
iatio
n
Data Presentation
Vis
ual A
naly
tics
Rep
ortin
g /
Dash
bo
ard
s
Security Connectivity
Operations Management
Cloud / On-Premise
Data Capture ► Streaming (e.g. sensor) ► Batch (e.g. raw, historical)
And Acquisition (e.g. through CCP, an existing joint investment)
Data Analytics Solutions & Services Areas of Focus
32
Operational & decision
support
Digital transformation
Modernization of Information Management Environments
CPG/Retail
Manufacturing
Energy & Utilities
Telco
Creating Opportunities
and Triggering
Change
New business opportunities
Continuous optimization
Agility & Cost Optimization
Enabled by our Solutions and Services
IDA Data
& Analytics Platform
Suite
Cloud and
On-Premise
Digital Assistant
Manufacturing Excellence
Demand Analytics
Customer Analytics
Value based Network
Optimization
Theft & Loss Detection
Atos Big Data Analytics services
BDAP – Business Data Analytics Platform
Handcraft Beta
version
Open source products – beta versions
Proof of Value &
Consulting Services
MRT TMU Worldline
Busin
ess s
erv
ices
Pla
tform
serv
ices
On premise – Enterprise private cloud –Cloud
Batch – Speed – Turbo layer
Smart Products
Manufacturing Excellence
Demand Analytics
Customer Analytics
Value based Operations
Optimization in dev.
Theft & Loss Detection
beta
Agile platform enabling big data analytical services
(3 days time-to-market)
Generic and specific vertical
big data analytical
business services
360 CRM
in dev
Fraud management
in dev.
Universities Imperial, IIT, …
ASIST
Expected benefits of Atos Industrial Data Analytics –approach
34
The Data Analytics
framework
Architecture reusability
Technology reusability
Lower Cost
► Operational costs are reduced by up to 70% ► Capital investment reduced by up to 30%
Efficiency
► Reduces time to market ► Development cycles reduced by up to 20% ► Increased reuse and sharing of knowledge reduce onboarding time for new use
cases ► Ability to make use of algorithms and analytical solutions normally beyond the
reach of individual departments ► Improves scalability across geographies and in capacity terms ► More efficient use of scarce subject matter experts in data analytics
Integration
► Integrated security ► Integrated monitoring, reporting and billing ► Integration with the core communication platform
Reusability & Flexibility
► Reuse – already jointly agreed and financed projects / development, such as CCP and Data Analytics as a Service (DAaaS)
► Framework approach ensures future-proofing and allows plug and play of new technologies and software as they become available
▶ Staying competitive in a fast-changing world
▶ Atos Big Data Analytics capabilities
▶ Big Data analytics in action powered by Atos
▶ IDA Platform Services : value chain
▶ Why Atos
Agenda
35
Challenges
▶ Needed big data solution offering >99% availability
▶ Collect data every 3 minutes from every machine globally
▶ Terabytes of live telematics and external data
Key features of Atos Solution
▶ Consulting and implementation
▶ Cloud-aware architecture
▶ Real-time capability
▶ Open to new business models
Achievements
▶ 30-fold increase in data capacity
▶ 250,000 vehicles providing real-time data
▶ Shaping a new era of precision farming
Agricultural equipment manufacturer
Connected farming in action
36
Pursuit/
Strategy Predictive Maintenance of Logging While Drilling (LWD) tools
▶ Overall Problem: The EcoScope tool has a MTBF that client would like to upgrade significantly (> 100%).
In order to reduce the problem space and guide client engineers in detailed diagnosis of failure causes, a data driven approach could lead to a better insight of major environmental failure factors.
▶ First problem under consideration: In order to upgrade the MTBF, the (combination of) majors environmental factors (circumstances) within a single run that have an impact on the MTBF need to be determined :
– Primary goals:
• A preliminary diagnosis - the (combination of) majors environmental factors (circumstances) within a single run that lead to a failure occurring.
– Secondary goals:
• Explore data driven analytics approach for reliability improvement
• Prepare next steps
37
Siemens DF Plant Data Services: Innovative Industry 4.0 offerings operated by Atos/Canopy Cloud solutions
38
Siemens Digital Factory Plant Data Services Digitalized Siemens offering with high growth rate expectation and competitive advantage • Target data recording and informative analysis
with Energy Analytics • Condition Monitoring & increased reliability
through Asset Analytics Services enable status monitoring for running systems
• Comprehensive Security Solutions as part of Industrial Security Services
Atos/Canopy contribution Plant Data Services fully run on Canopy Cloud • Big Data and Analytics are provided as fully
managed services (PaaS) Hadoop Big Data Engine Analytics Engine
• Legacy applications run as managed IaaS Development & Test systems prepare for the next, Cloud native architecture • Cloud Foundry PaaS
▶ Staying competitive in a fast-changing world
▶ Atos Big Data Analytics capabilities
▶ Big Data analytics in action powered by Atos
▶ IDA Platform Services : value chain
▶ Why Atos
Agenda
39
IDA – an integrated set of services
To give customers access to best practice
Our Big data analytics Consulting approach
Milestones
Opportunity discovery
Deployment Proof of Value Exploitation Pilot
Identified use cases Validated initiatives Proven initiatives Deployed solution
Value & maturity assessment
Value verification
One day workshop
Benefits realization
Go/no go
IDA strategic alignment Solution
implementation Opportunity
scan
IDA Platform Services: moving up the value chain
Business Services
Analytics Services
Analytics tools
IT Infrastructure
Data Capture
IDA Platform Provider
IDA Analytics Platform Provider
Analytics Service Provider
Business Insight Partner
Servic
e S
co
pe P
ro
vid
ed
Infrastructure to Business services
▶ Value proposition
– Reduced cost plus CAPEX to OPEX
– Accelerated time to delivery
IDA Platform Services: moving up the value chain
Business Services
Analytics Services
Analytics tools
IT Infrastructure
Data Capture
IDA Platform Provider
IDA Analytics Platform Provider
Analytics Service Provider
Business Insight Partner
Servic
e S
co
pe P
ro
vid
ed
Infrastructure to Business services
▶ Value proposition
– Access to range of viable analytics tools to enable analysis, visualisation and modelling
– Access to best practice analytics
IDA Platform Services: moving up the value chain
Business Services
Analytics Services
Analytics tools
IT Infrastructure
Data Capture
IDA Platform Provider
IDA Analytics Platform Provider
Analytics Service Provider
Business Insight Partner
Servic
e S
co
pe P
ro
vid
ed
Infrastructure to Business services
▶ Value proposition
– Access to skills & experience scarce in market
– Access to Analytical Models & IPR
IDA Platform Services: moving up the value chain
Business Services
Analytics Services
Analytics tools
IT Infrastructure
Data Capture
IDA Platform Provider
IDA Analytics Platform Provider
Analytics Service Provider
Business Insight Partner
Servic
e S
co
pe P
ro
vid
ed
Infrastructure to Business services
▶ Value proposition
– Market expertise & dedicated specialists
– A partnership service
▶ Staying competitive in a fast-changing world
▶ Atos Big Data Analytics capabilities
▶ Big Data analytics in action powered by Atos
▶ IDA Platform Services : value chain
▶ Why Atos
Agenda
46
▶ Atos deep industry knowledge & experience to bring data into a business context needed to turn information into values
▶ Experienced in handling large volumes of data in real-time for Manufacturing, Retail and Transportation customers
▶ References supporting leaders to stay ahead of competition
▶ 3350+ experts in data management, business intelligence, analytics and business process integration, with a global reach
▶ Vendor independent, but strong partnerships with key technology vendors
▶ Capability to source and provide computing, storage and software for on-premise and managed Data Analytics environments through an attractive CAPEX/OPEX model
▶ Adherence to global security policies and standards
▶ Bull acquisition, creating an European global leader in Cloud, Cybersecurity, and Big Data.
Why Atos?
Atos Strengths
47
Thank you
48
Atos, the Atos logo, Atos Consulting, Atos Worldgrid, Worldline, BlueKiwi, Canopy the Open Cloud Company, Yunano, Zero Email, Zero Email Certified and The Zero Email Company are registered trademarks of Atos. March 2015. © 2015 Atos. Confidential information owned by Atos, to be used by the recipient only. This document, or any part of it, may not be reproduced, copied, circulated and/or distributed nor quoted without prior written approval from Atos.
Thanks
For more information please contact: [email protected]
