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Jean-Michel Franco
Principal
jmfranco@audacity.com
The data-driven enterprise is shaping…
… but long is the road
92,1%
report measurable
business benefits
26,5%
Established a
data-driven
organization
Source : Data and AI Leadership Executive Survey 2022 – New Vantage Partners
73,7%
named a
Chief Data Officer
or equivalent
Facilitate collaboration
and teamwork
between data teams
and consumers
Make data easily
findable, accessible,
interoperable and
reusable
Foster sharing, break
down silos, put data
at the heart of the
digital transformation
Establish the
guidelines and
controls to ensure
organization,
protection and
consumption
Operationalize
data usage
consistently
throughout the
company
The challenges
Democratization Accessibility Simplification Quality and trust Scalability
The Three Pillars of Success
Organization
Architecture
Governance and Quality
Organization/Step 1: Establish the
business discipline with the Data Office
Create
value from
data and
analytics
Promote
the data
culture
Define
the data
strategy
Spark
innovation
with data
Develop
processes,
platforms
and know-how
Insure
governance and
data protection
The office
of the
Chief
Data
Officer
Organization/Step 2: Decentralize ownership
(data mesh)
65% consider that business domains have no data responsibilities
53% consider that business domains expertise in data & IT is insufficient
Domain-oriented,
decentralized data
ownership
self-service
platform
Federated
and computational
governance
Data
as a product
@
Source The future of data architecture 2022 – BARC
Architecture: focusing on self-service,
flexibility and use cases diversity
Data ingestion,
virtualization
and integration
Cataloging and
reference data
management
Gouvernanc
e,
privacy and
sécurity
Business
intelligence
and analytics
Quality
and
observability
Data lake
Data warehouse
Data Management & Operations
Raw
Data
Integrated
data
Reference
data
Analytical
models
Defining a framework for governance and
quality
Goals
1
Methods
Roles
Processes
Technologies
Culture
Reuse
Collaboration Crowdsourcing Communication Sharing
Sourcing Cataloging Preparation Analytics
Monitoring
Change Mgt Quality Inventory Measurement
Impact
Security Privacy & Compliance Integration Asset Management
Consumer
Sponsor Owner Steward Producer
Integration
Inspired by « the path to modern data governance » par Dave Wells/Eckerson Gro
Best Practices
Policies Guides Code of conducts Maps
1
1
1
1
1
Key takeaways from this data day
The planning journey
of Latecoere group
10:05
A data catalog within the
Domofrance group
11:00
A hybrid architecture for Bouygues
Construction
11:45
Data Mesh & Logical Data Fabric:
the value of decentralized
approaches
10:20
Real-time supply chain for
connected containers and wagons
11:00
Active Intelligence
with Qlik
11:45
Questions and ideas ?
KPC Data Day 2022, Paris
Jean-Michel Franco
Consultant indépendant
jmfranco@audacity.com

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A commonsense approach to data

  • 2. The data-driven enterprise is shaping… … but long is the road 92,1% report measurable business benefits 26,5% Established a data-driven organization Source : Data and AI Leadership Executive Survey 2022 – New Vantage Partners 73,7% named a Chief Data Officer or equivalent
  • 3. Facilitate collaboration and teamwork between data teams and consumers Make data easily findable, accessible, interoperable and reusable Foster sharing, break down silos, put data at the heart of the digital transformation Establish the guidelines and controls to ensure organization, protection and consumption Operationalize data usage consistently throughout the company The challenges Democratization Accessibility Simplification Quality and trust Scalability
  • 4. The Three Pillars of Success Organization Architecture Governance and Quality
  • 5. Organization/Step 1: Establish the business discipline with the Data Office Create value from data and analytics Promote the data culture Define the data strategy Spark innovation with data Develop processes, platforms and know-how Insure governance and data protection The office of the Chief Data Officer
  • 6. Organization/Step 2: Decentralize ownership (data mesh) 65% consider that business domains have no data responsibilities 53% consider that business domains expertise in data & IT is insufficient Domain-oriented, decentralized data ownership self-service platform Federated and computational governance Data as a product @ Source The future of data architecture 2022 – BARC
  • 7. Architecture: focusing on self-service, flexibility and use cases diversity Data ingestion, virtualization and integration Cataloging and reference data management Gouvernanc e, privacy and sécurity Business intelligence and analytics Quality and observability Data lake Data warehouse Data Management & Operations Raw Data Integrated data Reference data Analytical models
  • 8. Defining a framework for governance and quality Goals 1 Methods Roles Processes Technologies Culture Reuse Collaboration Crowdsourcing Communication Sharing Sourcing Cataloging Preparation Analytics Monitoring Change Mgt Quality Inventory Measurement Impact Security Privacy & Compliance Integration Asset Management Consumer Sponsor Owner Steward Producer Integration Inspired by « the path to modern data governance » par Dave Wells/Eckerson Gro Best Practices Policies Guides Code of conducts Maps 1 1 1 1 1
  • 9. Key takeaways from this data day The planning journey of Latecoere group 10:05 A data catalog within the Domofrance group 11:00 A hybrid architecture for Bouygues Construction 11:45 Data Mesh & Logical Data Fabric: the value of decentralized approaches 10:20 Real-time supply chain for connected containers and wagons 11:00 Active Intelligence with Qlik 11:45
  • 10. Questions and ideas ? KPC Data Day 2022, Paris

Editor's Notes

  1. La data est devenu une discipline à part entière dans l’entreprise, au travers des organisations. Mais la route est longue, bien plus longue par exemple que celle qui nous amené à la digitalisation/dématérialisation de nos vies personnelles et professionnelles. Car, il n’y a pas eu de Facebook, de LinkedIn, de Google, de Zoom ou de Slack qui ont imposé des nouvelles manières de travailler ou d’interagir. Il y a pourtant eu une très forte montée des compétences, à tel point que le métier de consultant data figure dans le top 25 des métiers les plus recherchés en France selon LinkedIn. On a vu tout un écosystème de spécialistes se créer, tant du côté des éditeurs et des cabinets de consultants et intégrateurs. L’innovation a été phénoménale, y compris en Europe. D’ailleurs, je me faisais la réflexion en voyant les partenaires de ces data days : Denodo est né à la Corogne, Qlik à Lund, Talend et la dimension analytique de SAP à Puteaux, Data Galaxy à Lyon, et même Snowflake tient ses racines de deux thésards de l’Université Paris VI. L’innovation est à portée de nos mains. Mais, jusqu’à preuve du contraire, il n’y a pas la place pour une solution universelle dans le domaine de la data car cela reviendrait à créer un silo, alors que l’on sait que les silos détruisent la valeur de la data Réussir son initiative data c’est donc savoir s’approprier cet écosystème pour mettre en place un système sociotechnique spécifique à votre entreprise. Mon constat est que beaucoup d’entreprises ont atteint un niveau de maturité suffisante pour la mise en place d’un tel système car il y a cette prise de conscience de sa valeur potentiel. Mais ce qui est beaucoup plus difficile, c’est de le pérenniser : la définition d’un système socio technique est qu’il doit favoriser les innovations qui sont cohérentes avec son fonctionnement et bloquer celles qui ne s’y intègrent pas. Or les innovations sont nombreuses: dans les 25 dernières années, on a vu se développer les concepts de data warehouse, de Businesss Intelligence, de Big Data, de data gouvernance puis tout s’est accéléré avec le Cloud, la data science, sans parler du tout dernier buzzword dont je reparlerais, le data mesh. Tous ces concepts sont de potentiels principes fondateurs mais c’est à vous, si vous vous partie de la task force data, d’en définir les enjeux, le cadre et les modalités d’adoption Prendre la data par la le bon sens : c’est cela qui rend notre travail passionnant, mais difficile --------------
  2. 73.7% vs 12% EN 2012 59,8% de ces organisations considèrent néanmoins que le rôle de Chief Data and Analytics Officer est encore naissant et 44,2% d’entre elles ont dû faire face à un turnover important sur ce poste. #3 / Les entreprises continuent de lutter pour devenir « data-driven » puisque seulement 26,5% d’entre elles déclarent avoir atteint cet objectif. #4 / Les obstacles culturels demeurent les plus critiques pour la mise en place d’une gestion stratégique de l’entreprise par la donnée, 91,9% des répondants estimant qu’il s’agit du principal défi à relever.
  3. Drive Industry Innovation Advanced Intelligence to transform customer engagement Brings together multichannel engagement, commercial content, customer data, and artificial intelligence to drive smarter, compliant interactions with all customers across all channels Leverage community Network with your peers Share best practices with global customers with users in 165 countries Develop new industry partnerships across sponsors, CROs, and sites. Opportunities: annual Commercial & Medical Summit – June 8-10, 2020 and a series of local community meetings in Boston, Philadelphia, Chicago, New Jersey in September 2019 Leverage expertise Enhance value through robust ecosystem of partners Implementation, managed services, and best practices with team of global subject matter experts
  4. Define and implement data & analytics strategy for the organization Oversight of data & analytics initiatives Data-driven culture change or change management Creating and implementing data and analytics governance Data & analytics center of excellence
  5. Sources Ingestion and transport Storage Query and processing Transformation Analysis and output
  6. 🎯 Atelier Denodo - Data Mesh & Logical Data Fabric : L’intérêt des approches décentralisées pour faciliter et accélérer les usages et le Data Management. 🎯 Atelier SAP - Retour d’expérience du groupe Latécoère sur l’implémentation de la solution SAP Analytics Cloud. 🎯 Atelier Snowflake - Présentation de la solution Snowflake et retour d’expérience de Traxens sur le processus de Supply Chain en temps réel pour les containers et wagons connectés. 🎯 Atelier DataGalaxy - Témoignage de Domofrance sur la mise en place d’une nouvelle stratégie de datacatalog au sein du groupe. 🎯 Atelier Talend - Retour d’expérience de Bouygues Construction sur la gestion des données de son architecture hybride avec la solution Talend. 🎯 Atelier Qlik - Illustration de l’Intelligence Active à travers une présentation et une démo Qlik.
  7. Drive Industry Innovation Advanced Intelligence to transform customer engagement Brings together multichannel engagement, commercial content, customer data, and artificial intelligence to drive smarter, compliant interactions with all customers across all channels Leverage community Network with your peers Share best practices with global customers with users in 165 countries Develop new industry partnerships across sponsors, CROs, and sites. Opportunities: annual Commercial & Medical Summit – June 8-10, 2020 and a series of local community meetings in Boston, Philadelphia, Chicago, New Jersey in September 2019 Leverage expertise Enhance value through robust ecosystem of partners Implementation, managed services, and best practices with team of global subject matter experts
  8. La data est devenu une discipline à part entière dans l’entreprise, au travers des organisations. Mais la route est longue, bien plus longue par exemple sde celle qui nous amené à la digitalisation/dématérialisation de nos vies personnelles et professionnelles. Car, il n’y a pas eu de Facebook, de Linkedin, de Google, de Zoom ou de Slack qui ont imposé des nouvelles manières de travailler ou d’interagir. Il y a pourtant eu une très forte montée des compétences, à tel point que le métier de consultant data figure dans le top 25 des métiers les plus recherchés en France selon Linkedin. On a vu tout un écosystème de spécialistes se créer, tant du côté des éditeurs et des cabinets de consultants et intégrateurs. L’innovation a été phénoménale, y compris en Europe. D’ailleurs, je me faisais la réflexion en voyant les partenaires de ces data days : Denodo est né à la Corogne, Qlik à Lund, Talend et la dimension analytique de SAP à Puteaux, Data Galaxy à Lyon, et même Snowflake tient ses racines de deux thésards de l’Université Paris VI. L’innovation est à portée de nos mains. Mais, jusqu’à preuve du contraire, il n’y a pas la place pour une solution universelle dans le domaine de la data car cela reviendrait à créer un silo, alors que l’on sait que les silos détruisent la valeur de la data Réussir son initiative data c’est donc savoir s’approprier cet écosystème pour mettre en place un système socio-technique spécifique à votre entreprise. Mon constat est que beaucoup d’entreprises ont atteint un niveau de maturité suffisante pour la mise en place d’un tel système car il y a cette prise de conscience de sa valeur potentiel. Mais ce qui est beaucoup plus difficile, c’est de le pérenniser : la définition d’un système socio technique est qu’il doit doit favoriser les innovations qui sont cohérentes avec son fonctionnement et bloquer celles qui ne s’y intègrent pas. Or les innovations sont nombreuses: dans les 25 dernières années, on a vu se développer les concepts de data warehouse, de Businesss Intelligence, de Big Data, de data gouvernance puis tout s’est accéléré avec le Cloud, la data science, sans parler du tout dernier buzzword dont je reparlerais, le data mesh. Tous ces concepts sont de potentiels principes fondateurs mais c’est à vous, si vous vous partie de la task force data, d’en définir les enjeux, le cadre et les modalités d’adoption Prendre la data par la le bon sens : c’est cela qui rend notre travail passionnant, mais difficile --------------
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