Watch full webinar here: https://bit.ly/2zdlULt
A l’ère de la transformation digitale et de l’adoption rapide de nouvelles solutions, les équipes IT sont amenées à traiter un volume croissant de sources de données disparates et à un rythme de plus en plus soutenu pour satisfaire les besoins Métiers. Les techniques d’intégration traditionnelles présentent des limites pour répondre à ces défis, car elles délivrent les données par lots programmés et ne peuvent pas prendre en charge les nombreux types de données riches et complexes actuels.
La data virtualization constitue alors une approche moderne d’intégration des données. Cette technologie agile d’intégration, d’abstraction et de services de données en temps réel permet un accès unifié à un large éventail de sources, sans répliquer ou déplacer les données, afin d’en créer une couche unique virtuelle. Elle permet ainsi une réduction des coûts, des ressources et du temps alloués aux opérations IT.
Les experts de Denodo et Govarch vous proposent ce webinar en français pour comprendre comment exploiter la data virtualization afin d’optimiser votre stratégie globale d’intégration de données et ainsi vous aligner sur les objectifs Métiers.
Agenda :
- Les défis actuels de l’intégration des données et les limites des techniques d’intégration traditionnelles
- Comment déployer la couche de virtualisation dans une architecture IT pour bénéficier d’un accès unifié aux diverses sources des données
- Une démo live de la solution Score One, pour évaluer l’applicabilité de la virtualisation des données à des cas d’usage concrets.
GenAI y el futuro de la gestión de datos: mitos y realidades
Optimiser l’intégration globale des données grâce à la Data Virtualization
1. Comment positionner la
data virtualization dans une
stratégie d’intégration de
données globale ?
WEBINAR
Aly Wane Diene
Senior Solution Consultant
DENODO
Rachid Essahili
CEO & Fondateur
GOVARCH
13. 13
The Business Need
Ready Access to Critical Information to Support Business Processes
MarketingSales ExecutiveSupport
Customers
Invoices Products
Service Usage
Access to complete information: business
entities and pre-integrated views
Access to related information: discovery
and self service
Access in real-time from different apps and
devices
14. 14
The Challenge
Data Is Siloed Across Disparate Systems
Manually access different systems
Not productive – slows down response
times
IT responds with point-to-point data
integration
Database
Apps
Warehouse Cloud
Big Data
Documents AppsNo SQL
MarketingSales ExecutiveSupport
15. 15
The Solution
Data Abstraction Layer
Abstracts access to disparate data
sources
Acts as a single repository (virtual)
Makes data available in
real-time to consumers
DATA ABSTRACTION LAYER
“Enterprise architects must revise their data architecture to meet the demand for fast data.”
16. 16
What is Data Virtualization ?
A definition of a Data Virtualization
Data Sources
Data Consumers
Data Virtualization
Data Virtualization combines disparate
data sources into a single “virtual” data
layer that provides unified access and
integrated data services to consuming
applications in real-times (right-time).
17. 17
Denodo Architecture
Consume
in business
applications
Combine
related data into
views
2
3 DATA CONSUMERS
Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users, IoT/Streaming Data
Connect
to disparate
data sources
1 DISPARATE DATA SOURCES
Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word...
Less StructuredMore Structured
Multiple protocols,
formats
Linked data services
query, search, browse
Request/Reply,
event driven
Secure
delivery
Library of
wrappers
Web
automation
Any data
or content
Read
& Write
DATA VIRTUALIZATION
Design Tools
Optimization Engine
Data Discovery & Search
In-memory Fabric
Cache
Scheduler
DATA CONSUMERSAnalytical Operational
CONNECT COMBINE CONSUME
Share, Deliver,
Publish, Govern,
Collaborate
Discover,
Transform,
Prepare, Improve
Quality, Integrate
Normalized
views of
disparate data
Data Services (Real-time &
On-demand)
Data catalog / Metadata
Governance
Security
Management & Monitoring
18. 18
Six Essential Capabilities of Data Virtualization
4. Self-service data services
5. Centralized metadata, security
& governance
6. Location agnostic
1. Data abstraction
2. Zero replication, zero relocation
3. Real-time information
20. 20
Customer Centricity / MDM
✓ Complete View of Customer
Data Services
✓ Data as a Service
✓ Data Marketplace
✓ Data Services
✓ Application and Data Migration
Cloud Solutions
✓ Cloud Modernization
✓ Cloud Analytics
✓ Hybrid Data Fabric
Data Governance
✓ GRC
✓ GDPR
✓ Data Privacy / Masking
BI and Analytics
✓ Self-Service Analytics
✓ Logical Data Warehouse
✓ Enterprise Data Fabric
Big Data
✓ Logical Data Lake
✓ Data Warehouse Offloading
✓ IoT Analytics
Denodo ‘Horizontal Solution’ Categories
21. 21
Case Study : Single View of Customer
Business Need
• Business needed to differentiate themselves from their
competitors.
• Needed to provide better customer service.
• Existing contact center, with a CTI solution, required the
use of different systems and was complex.
• Large number of applications used by agents.
Benefits
• Increased their First Call Resolution by 5 points and reduces
client call times by 10%.
• Doubles their customer retention rate.
• Reduced back office workloads by more than 50%.
Solution
22. 22
Case Study : Data Access Marketplace
Business Need
• Business logic existed in multiple silos within IU
information system making it difficult to combine relevant
data to present meaningful information.
• Cycle time of information access was too long.
• Custom security solutions existed only in the Enterprise
Data Warehouse, making the rest of the information
system vulnerable to data breach.
Benefits
• Denodo has tremendously impacted information agility
across the University through instantaneous access of any
information.
• Business Logic has been centralized for reusability, which
improves efficiency and has significantly reduced TCO.
• The entire enterprise data at IU is now accessed securely
and with proper governance structure around it.
Solution
23. 23
Case Study : Logical Data Warehouse
Business Need
• Autodesk was changing their business revenue model from
a conventional perpetual license model to subscription-
based license model.
• Inability to deliver high quality data in a timely manner to
business stakeholders.
• Evolution from traditional operational data warehouse to
contemporary logical data warehouse deemed necessary
for faster speed.
Benefits
• Successfully transitioned to subscription-based licensing.
• For the first time, Autodesk can do single point security
enforcement and have uniform data environment for
access.
Solution
24. 24
Case Study : Advanced Analytics
Business Need
• Competitive pressure from low-cost Chinese manufacturers
• Needed a proactive approach to customer service to
differentiate
• Sought to improve equipment and services delivery
through predictive maintenance
Benefits
• Phased rollout systematically improved asset performance
and proactive maintenance
• Increased revenue from sale of services and parts
• Reduced warranty costs of parts failure
• Future – optimize pricing for services and parts among
global service providers
Solution
Dealer
Maintenance
Parts Inventory
OSI PI Hadoop Cluster
Tableau: Dealer / Customer Dashboard