digital transformation in action moving to a data-driven
TRANSCRIPT
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Emanuele BaldacciDirector Digital ServicesDIGITEuropean Commission
Digital Transformation in action
Moving to a data-driven organisation
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Expectations & Goals
Citizens, public and private organisations expect• Faster response cycles on events• Accessibility and transparency
Data is the lifeblood of our organisation• Real time, anytime, anywhere, once only • Borderless, multi-channel• For policy making
Our workforce should be • Digitally augmented knowledge workers • Able to network, collaborate and locate knowledge easily• Digital Workplace to work any time anywhere
We need a strategic vision and actions to tap into the potential of IT
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MAKE THE COMMISSION MORE EFFICIENT BY
TAPPING THE POTENTIAL OF INFORMATION
TECHNOLOGY
Commission as modern efficient partner
towards Member States, citizens, businesses
by 2022
A Commissionfurther transformed
user-focuseddata driven
EUROPEAN COMMISSION
DIGITAL STRATEGY
EC Digital Strategy
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EC Digital Strategy - Building Blocks
DIGITALWORKPLACE
DIGITAL TOOLS TO WORKANYWHERE, ANYTIME
DIGITALSOLUTIONS
A SET OF DIGITALSOLUTIONS TO BETTERSUPPORT ADMINISTRATIONAND POLICIES
DATA ECOSYSTEMA SET OF DATA REPOSITORIESFOR SHARING AND REUSE
REUSABLE SOLUTIONS PLATFORMA PLATFORM FOR EXPERTSWITH READY-MADE ANDRE-USABLE IT SOLUTIONS
DIGITAL INFRASTRUCTURE CORPORATE, CONSOLIDATED,SECURE, HYBRID CLOUD SERVICES
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EC Digital Strategy
Digital Commission User focusedData-driven
« It is a capital mistake to theorize before
one has data. Insensibly one begins to twist
facts to suit theories, instead of theories to
suit facts »
Sherlock Holmes
Arthur Conan Doyle, 1891
Where can I find data?
Who can help me extract
insights from
my data?What are the tools /
solutions I
can reuse?How do I
manage the
data I have?
What data can I find in
my own DG?
The Data Ecosystem is a system of
interconnected human and technological
resources, working together to extract value
from data and to use it for decision-making.
The
Data
Ecosystem
10 Strategic Objectives
8 Main Actions
21 Enablers
Identification
Access
Analytics
Infrastructure
Roles & Responsibilities
Labs
Skills acquisition
Literacy
Internal data management policies
Compliance with EU policies
Data Catalogue
Data Analytics
Data Platforms
Data Governance
Data Advisory
Data Skills
Data Trainings
Data Policies
Action Plan coordination
The Data Action Plan
Data Action Plan
Actions
Data Catalogue
Data Analytics
Data Platforms
Data Governance
Data Advisory
Data Skills
Data Trainings
Data Policies
Data inventory
(JRC)
Selecting solution
to support the
catalogue
Data Action Plan
Actions
Data Catalogue
Data Analytics
Data Platforms
Data Governance
Data Advisory
Data Skills
Data Trainings
Data Policies
Prototypes
DORIS
Data Action Plan
Actions
Data Catalogue
Data Analytics
Data Platforms
Data Governance
Data Advisory
Data Skills
Data Trainings
Data Policies
Linked data
intensive training
Data Action Plan
Actions
Data Catalogue
Data Analytics
Data Platforms
Data Governance
Data Advisory
Data Skills
Data Trainings
Data PoliciesMaster Data
Management
A data platform:
Towards data-driven organisations, evidence-based policy making, information sharing
EC Data Platform
Data Platforms
Actions
Data Catalogue
Data Analytics
Data Platforms
Data Governance
Data Advisory
Data Skills
Data Trainings
Data Policies
EC Data Platform
Big Data Test
Infrastructure for
the Member States
Why
A corporate enabler:
Avoid duplication
of effort by providing
a pre-configured
and customisable
technology stack
Economies of scale,
resource pooling
Offer analytics as a
service to close the
maturity gap among
different DGs and services
Deliverable of the Data
Action Plan agreed at
the IMSB level
Avoid procurement
efforts, usage of the
cloud FC
Leveraging on the
strengths of cloud
technology and of
linking data from
different sources
Data and algorithm/AI
communities of practice
1 2 3
85 6 7
Coordination,
reuse and standardization
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The EC Data Platform is a set of
services aiming at unlocking the
full potential of data: from
providing an easy way to find and
access data to enabling advanced analytics to extract insights.
Data
Sources
How
Co-design/production with users
Minimal Viable Product approach
Agile development
Perpetual beta
Design and implementationOur approach:
Data
Science
Lab
Analytics
Implementation
EC Data Platform
Reusable Data
Components
Data as a
Service
Analytics
Software as a
Service
Who are we doing it for?
Daniel
Data Scientist
Marta
Business Manager
Vincent
IT Architect
Franco
IT ManagerVincent
IT Architect
Myriam
Policy Officer
Daniel
Data Scientist
Myriam
Policy Officer
Data
Science
Lab
Analytics
Implementation
EC Data Platform
Reusable Data
Components
Data as a
Service
Analytics
Software as a
Service
We provide
you with an environment to experiment
with data using
advanced technologies
EC Data Platform Services
We
implement data analytics use cases for
you, from data gathering to
visualisation
We help you
build modern IT systems with advanced
data capabilities
We help you
find and access the data you need
for your decisions
We provide
you with ready-to-use online tools to
combine data, perform
analytics and create reports
Our blueprint
Data Preparation
Operational Data
Data Query and Processing
Services
Data Sources
Data Integration and Storage
Self-Service AnalyticsSolutions
Advanced AnalyticsSolutions
Models Catalogue
Data Catalogue
Not Part of the Data Platform
Part of the Data Platform
Existing DWH Master Data Documents External Data
Data Access (API access, ELT, ETL, DB replication, Virtualisation, etc.)
Corporate Data Lake
Data as a Service
Analytics as a Service
Data Science Lab
Analytics Implement.
Presentation Data Platform Portal
Corporate Search Engine
Local Data Lake Local Data Lake
Reusable Data Components
Security
Go
vernan
ce
Long term vision P
lan
ned
In
vestm
en
t
Time
Supporting services Impact of other actions
of the Data Ecosytem
Core Services: Data as a Service, Data Science Lab, Analytics Software as a Service
Supporting Services: Analytics Implementation, Reusable Data Components
Core services
Big Data Test
Infrastructure for
the Member Statesas part of the CEF "Data Value Chain"
The Big Data Test Infrastructure (BDTI) provides a
complete set of data and analytics services, from
infrastructure to tools and advisory, allowing European
organisations to experiment with Big Data
technologies and move towards a data-driven policy
making
Big Data Test
Infrastructure for
the Member Statesas part of the CEF "Data Value Chain"
A sandbox environment for the implementation of
data analytics pilot projects
Additional services facilitating the usage of the sandbox,
such as testing and onboarding services
A set of software solutions and sample
datasets to be easily downloaded or used in the sandbox
Built-in APIs for the ingestion of data coming from
different sources, for public administrations who prefer to
import their own data.
A Community Portal to foster the sharing of
knowledge in the Big Data field of expertise among the
public administrations.
provides
local innovation
corporate enablers
co-innovation
Co.innovation – enlarging
cooperations
CommissionEUIs and
agencies
Member States
workshops
PoCs ongoing
EP/Council/EC
PoCs ongoingproposals under preparation
ICTAC + concrete cooperation
EEAS
workshops
IDEATE SELECT DESIGN PROTOTYPE EVALUATE
The innovation
Process
PROTOTYPE PROJECT SERVICE
Prototype > Project > Service
Validating use cases,
technologies, tools
Lessons learnt
Assessing the potential to become
a corporate service
Integrating in the corporate
components
✓ ✓
Co.innovation Portfolio – European Commission
Title Actors Area Deliverables Status
Document reviewImpact Assessments
RSB, DIGIT, MicrosoftText mining, semantic search
Insights, smart search
Document review –submission of H2020 proposals
RTD, COMP, DIGIT, OrtecText mining, graph analysis, automaticclassification
Insights, classification, plagiarism, fraud detection
Document review –case management
COMP, RTD, DIGIT, SinequaText mining, graph analysis, automaticclassification
Insights, classification, plagiarism, fraud detection
Data validationGROW, ENER, CNET, DIGIT, JRC
Data analytics, predictions, estimation, data sources
Gap estimation, collection of different sources and machine-driven data wrangling
Data correlationGROW, ENER, CNET, DIGIT, JRC
Data analytics, data sources
Correlation patterns and links in different data sources
Co.innovation Portfolio – Agencies, EUIs, Member States
Title Actors Area Deliverables Status
Data lakes EFSA, ECHA, DIGIT Infrastructure Data lake
Speech to text EP, Council, SCIC, DIGITNational LanguageProcessing
Tools for speech to text
Chatbots,Virtual Assistants
EP, Council, DIGITChatbots, virtualassistans
Prototype for EUIs
Emotional analysis EP, Council, DIGITAdvanced sentiment analysis
Solution for the EUIs
Disinformation EEAS Detection - AI Tools for detection
AI for citizens - Aurora Member States AI
AI interface for citizens to consume government services
Chatbots, Virtual Assistants
Member StatesChatbots, virtualassistant
Prototype for citizens
Data Science experimentation - ProjectsTitle Actors Area Deliverables Status
MFF programmestatements
BUDG, DIGIT BIProgramme StatementReport - prototype
Talent discovery HR, DIGITAdvanced Search, smart algorithms
Prototype for HR on Contractual Agents
Big Data Test Infrastructure
CEF, CNECT, DIGIT Big data, infrastructure Sandbox platform
EU Open Call Portal REGIO, DIGIT Linked data Proof of Concept portal
EU Results GROW, COMM, DIGIT Data lake Working platform
Market place analysis– dangerous products
JUST, DIGITBig data, web scraping, image-text recognition
Working tool
Management Plan, Annual WorkProgramme
SG, DIGIT BI, AIMP and AWP insights, report
Innovation portfolio
Big Data TextInfrastructure
EU Results
EC Programme Statements
Impact Assessments
Annual Work Plans
Document Review
Data Correlation
Data Cleaning
Skill discovery
Data, Information, KnowledgeMonitoring
Web Analytics
EU Open Calls Portal
Linked Data
AI for Staff
Market Place Analysis
Review of Scientific Clinical Articles
Audio and VideoTranscripts
Resource Forecastingand Invoicing
ESIF monitoring
Victory
Blue Indicators
Doris
Thank you
Q&A