The document presents a framework for managing cloud data costs using FinOps, which emphasizes team ownership and central best practices. It advocates for a logical data management architecture through tools like Denodo, enabling efficient integration and governance across distributed data landscapes. Key benefits include streamlined operations, cost reduction, and improved data visibility, essential for effective FinOps implementations in complex cloud environments.

1. Mastering Cloud Data Cost Control:
A FinOps Approach
Felix Liao
Director of Product Management APAC

2. 2
Good News - Cloud Benefits
Learn Cloud Economics - Value of Cloud - Cloud ROI Framework – AWS (https://aws.amazon.com/economics/)

3. 3
Bad News – Managing Cloud Spend

4. 4
Managing Cloud Data and Analytics
Workload Costs is HARD!

5. 5
FinOps is a cultural practice. It’s
the way for teams to manage their
cloud costs, where everyone takes
ownership of their cloud usage
supported by a central best-practices
group
What is FinOps?
FinOps Foundation Technical Advisory Council
https://www.finops.org/introduction/what-is-finops/
“ Good idea.
But How?

6. 6
Why Denodo? - Embrace a distributed data landscape
Embrace a distributed data landscape
Embrace the fact that data resides in multiple locations or systems – on-
prem, hybrid, multi-cloud. 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, that can enforce
security and governance requirements
6
Adopt AI to simplify and automate
Learn from usage and leverage Large Language Models to automate
tedious repetitive tasks

7. 7
3rd Party
Connectors
Data Science / Prep Tools
Why Denodo? – Extensive Technology Ecosystem Support
MDM & DQ Tools
Data Governance Tools
Cloud Service
Providers
Big Data/NoSQL Sources
HDInsight
BI & Reporting Tools
Data Modeling Tools
Security & Privacy
Traditional Data Sources
SaaS/Cloud Applications
Cloud Data Warehouses
API Management / ESB

8. 8
Why Denodo - FinOps support via a Logical Data Fabric Layer
Implementing a FinOps
program for data and
analytics requires data
that is best collected
from the logical data
fabric layer.

9. 9
Data Virtualization: The Foundation of a Logical Data Management
Architecture
Agile Data
Integration
Logical Data Abstraction
Smart Query
Acceleration
Advanced
Semantics
Automation &
Recommendation
Unified Security & Governance
Data Catalog
AI/ML
Hybrid/Multi-Cloud
Data Integration
Self-Service BI
Data Governance
3600 View of
Entities
FinOps
Data Science
Enterprise
Data Services
Data Fabric/Data
Mesh
6 Key Capabilities of Logical Data Management Differentiated Use Cases

10. 10
Inform: Logging and tracking queries and data transfers
Denodo
Platform
Warehouse
Mobile Apps
Operational
RDBMS
Data Source Traffic
• Cloud provider and region
• SQL statements
• Execution time
• Results row transferred
• Results size transferred
Marketing
Data Science
Notebooks
On-prem
tools
.
BI Tools
Operations
Data Science
Notebooks
On-prem
tools
.
BI Tools
Data Source Compute
• Database type and
technology
• SQL statements
• Execution time
• Estimated table scanned at
source
End user Query Traffic
• User name/ID
• Cloud provider and regions
• SQL statements
• Execution time
• Total rows count
• Total result transfer size

11. 11
Inform: Easy Integration with third party dashboarding Tool

12. 12
Inform: Denodo Dashboards

13. 13

14. 14

15. 15

16. 16

17. 17
• Denodo Platform can orchestrate and optimize the user
queries in multiple ways to reduce cloud cost
• The Denodo Query Optimizer was built from day one to
minimize compute and traffic and supports a wide variety
of optimization query control techniques
• Push Down Optimizations
• Intelligent Caching/Replication
• Smart Query Acceleration
• Query scope control
• All with minimum disruption to the end users!
Optimize & Operate: The Logical Layer to the Rescue

18. 18
• Intelligent Caching/Replication
• Use cache or alternative/cheaper compute technology
• Smart Query Acceleration
• Leverage pre-cached summary table
• Limit execution time or size of the result set
• E.g. Force query re-write to limit results time horizon
Optimize: Reduce Data Source and Table Scan Costs

19. 19
• Intelligent Query push-down
• Automated joins push-downs
• Intelligent Caching/Replication
• Use cache or alternative/cheaper compute
technology
• Smart Query Acceleration
• Leverage pre-cached summary table
Optimize and Operate: Reduce Cloud Egress Charges

20. 20
Why Denodo - Proven in Large Enterprise Scale Deployments
✓ 2,000+ APIs in production
using over 300+ data
sources
✓ 2+ Million queries/day
✓ 7 years in Production –
0 Downtime
✓ Deliver data 90% faster
E N T E R P R I S E –
A L L B U S I N E S S L I N E S
200k users (int. & ext.)
✓ 20k+ views / 1k+
sources / 1.5K+ services
✓ Logical data fabric for
enterprise governance &
security / 10 years in
✓ 1/6th time to build
compared to ETL
✓ Data services run 2X –
10X faster
N U C L E A R W E A P O N S
C O M P L E X
10 sites / 200k users
✓ 34K views – Inventory of
all data assets 100+
sources
✓ Single access layer
✓ 1K+ APIs in production
using over
✓ 6 years in Prod - 100%
ROI in first 2 years
✓ $1MM+ savings / year
E N T E R P R I S E – A N A LY T I C S
& R E P O R T I N G
50k users
✓ 2K+ Views - eliminated
1k+ point to point
connections
✓ 98% faster processing
- 1 day vs. 60 days
✓ 2 years in Production
✓ $40MM savings –
eliminating physical data
replication & storage
E N T E R P R I S E – S C A L E
D E P L O Y M E N T

21. 21
• Multi-cloud/Hybrid cloud and increasingly complex data landscape
is increasing the complexity of FinOps implementations
• A logical data fabric layer can simplify and accelerate the
implementation of FinOps initiative and strategies
• Start with a solid foundation that improve visibility in a robust and
scalable way!
Key Take Aways

22. 22
Next Steps
Access Denodo Platform in the Cloud!
Take a Test Drive today!
www.denodo.com/TestDrive
GET STARTED TODAY

23. Q&A

24. Thanks!
www.denodo.com info@denodo.co
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