Watch full webinar here: https://bit.ly/3WZwa0H The current complexities of the data landscape, often hybrid in location and distributed in nature, have catapulted the Data Fabric to the forefront of the data management industry. However, as a broad and strategic initiative, it is not always clear how to start and how to evolve it, what are the critical pieces that require more attention, and how to measure its progress and value. In this panel, we will: - Review the key concepts of this architecture - Discuss with Denodo customers the successes and challenges of their implementations - Highlight what to avoid and what to focus on first

1. Transforming Data Management
for the Cloud

2. Building a Data Fabric: Lessons from
the Field
Pablo Alvarez
Global Director Product Management
Denodo

3. 3
What is a Data Fabric

4. 4
What is a Data Fabric
Gartner: What Is Data Fabric Design? (ID G00748508)
By Analysts Robert Thanaraj, Mark Beyer, Ehtisham Zaidi

5. 5
Why? What Problems it Tries to Address?

6. 6
Data landscape is complex
• Organizations are distributed
• Use best tool for each task
• Technology evolution
Avg. of 400 sources used for analytics
in big organizations
Source: IDG, 2021
DATA
SOURCE
DATA
CONSUMER
Data
Governance
Tools
DB, DW &
Data Lakes
Files
BI Dashboard
Report and Tools
Data Science &
Machine Learning
Apps
Mobile &
Enterprise Apps
Microservices
Apps
Cloud DB
& SaaS
Streaming
Data & IoT
Cube

7. 7
Underutilization of Data and Analytics
Source: Denodo Global Cloud Survey 2022
62% 72%
Source: Improving the State of Analytics in Organizations (ventanaresearch.com)

8. 8
Lack of Agility in Data Initiatives

9. 9
Governance and Security are Challenging

10. 10
How to Build a Data Fabric

11. 11
What’s Denodo’s recipe?
Embrace a distributed data landscape
• Embrace the fact that data resides in multiple locations or
systems – on-prem, hybrid, multi-cloud
• Different data systems serve different data needs
• All data needs to be managed with consistency
Use a logical approach to manage it
• Consumers access data through a centralized semantic model,
decoupled from data location and physical schemas
• Can enforce security and governance requirements
• Agile, flexible data integration methods

12. 12
A Mora Tactical Approach
https://www.denodo.com/en/document/whitepaper/logical-data-fabric-whitepaper

13. Building a Data Fabric: Lessons
from the Field
Global Director of Product
Management, Denodo
Pablo Alvarez
CTO, IQZ Systems
Satish TK
Senior Vice President of
Architecture and Enterprise Data,
Primerica Insurance
James Barnes

14. Thank you!