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DATA VIRTUALIZATION PACKED LUNCH
WEBINAR SERIES
Sessions Covering Key Data Integration Challenges
Solved with Data Virtualization
Cloud Modernization and Data as a Service
Mitesh Shah
Senior Cloud Product Manager, Denodo
Agenda1. Data - Cloud Modernization - Data Services
2. Data Virtualization & API Management
3. Customer Case Studies & Demo
4. Q & A
4
Poll Question:
What is your familiarity with Data Virtualization as a means to data integration?
Data – The Final Frontier!
6
Data – Like Oil – Is Not Easy To Extract and Use
Although If Not Properly Managed, Can Lead to Waste!
7
But the Data is Somewhere in Here…
8
The Scale of the Problem…
A Typical Cloud Journey – Why data services matter even more!
Interesting Dimensions of Data in your Cloud Journey!
Yes, but..
 New data silos
 Security
 Latency
Your Sources in the Cloud
 SaaS apps: SFDC, Social Media,
etc.
 Cloud RDBMS: Amazon RDS,
Azure SQL Database, etc
 Cloud Analytics: Snowflake,
Amazon Redshift, SparkSQL
Why?
 More flexible
 Access from Anywhere
 Lower Cost of Operations
Challenges
• Data is in many locations, data formats,
Cloud, on-premise, SaaS..
• Simple tasks become more challenging
as the data gets more dispersed
• How do users know what data is
available? find and access the data?
11
Poll Question:
What is your top challenge when it comes to integrating data in the cloud ? (check all that apply)
Cloud Modernization
Cloud Modernization & Key Initiatives in the Cloud?
Source: Denodo Cloud Survey 2020
Why Cloud Modernization and How Does Data as a Service fits in?
Modernize Your Applications, Drive
Growth and Reduce TCO, by migrating
them to the cloud to maximize the use
of cloud infrastructure scaling
capabilities and cost structure.
Enable companies to leverage data as
an API services layer to accelerate the
development of the cloud native
microservices architecture
Driving continuous & agile business
transformation to derive faster and
valuable insights in form of Analytics
and ML/AI in the Cloud
Data as a service (DaaS) - hybrid data management strategy that leverages cloud to deliver data storage,
integration, processing, and/or analytics services over the cloud backbone.
15
Data Virtualization – Realtime – Simplified Integration
Real-time Data Integration
Consume
in business applications
Combine
related data into views
Connect
to disparate data sources
2
3
1
DATA CONSUMERS
Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users, IoT/Streaming Data
Multiple Protocols,
Formats
Query, Search,
Browse
Request/Reply,
Event Driven
Secure
Delivery
DATA CONSUMERSAnalytical Operational
Web
Services
DISPARATE DATA SOURCES
Databases & Warehouses, Cloud/SaaS Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word...
Less StructuredMore Structured
SQL,
MDX
Big Data
APIs
Web Automation
and Indexing
DATA VIRTUALIZATION
CONNECT COMBINE CONSUME
Agile Development
Performance
Data Services
Resource
Management
Data Catalog
Governance
& Metadata
Security and
Data Privacy
Lifecycle
Management
“Data virtualization
integrates disparate
data sources in real
time or near-real
time to meet
demands for
analytics and
transactional data.”
– Create a Road Map For A
Real-time, Agile, Self-
Service Data Platform,
Forrester Research, Dec 16,
2015
Data Virtualization in the API Ecosystem (Enabling DaaS)
APIs(Application Programming Interface) – Building Blocks of Digital Transformation
APIs are the foundations of digital transformation
 Enable the integration of diverse IT systems, building
more collaborative and self-service IT environments
 Enables exposing data and processes to other
business units and/or partners
 Create revenues from existing assets, and support
creation of new products and business models
These initiatives have created an API Economy
18
Data Services Layer (Data API)
A data access layer that abstracts underlying data sources and exposes them as
discrete services to form a ‘data API’
 Different users and developers across the enterprise can access data in a secure and managed
fashion and share a common data ‘model’
 Provides secure and managed access to data across the enterprise
 Provides consistency of data & hides complexity, format, and location of actual data sources
 Supports many consumption protocols and patterns
Example: Single data access layer for all development teams to avoid ‘hunting down
and interpreting data differently by project’
Data Virtualization in the API Ecosystem
Data virtualization platforms like Denodo
can play a significant role in an API
ecosystem without writing NEW CODE
Let’s review three common architectures:
1. Data Virtualization as a Data Service
provider
2. Data Virtualization as an abstraction
data layer for Microservices
3. Data Virtualization as an API
Management tool
19
20
API Ecosystem: Create Complex Data Services in Minutes
• Create data services - no code…..…………………….
• Host services (aka ‘Services Container’)………….
• Multiple protocols/formats APIs SAOP REST…….
• API Developer Porta…………………………………………..
• Leading Security Standards………………………………
• Complex security policies………………………………….
• Co-ordinate services………………………………………….
• API discovery (Open API )…………………………………
• Quotas and workload management………………….
• API Lifecycle, versioning, retirement………………..
• Usage stats and analytics………………………………….











Denodo
Platform










21
Denodo abstracting SaaS APIs – As API Consumer
SQL Enable any kind of SaaS API
 SaaS-to-SQL: DV abstracts the SaaS API (usually
REST services) as part of a relational model
 Real Time access: avoids replication of Cloud
data back into the data center
 Unique relational approach to cloud data
integration
 Different from most flow-based iPaaS vendors
SQL
API
MART
22
Ways to maximize Data Virtualization in a DaaS model
Data Service provider Abstraction data layer for Microservices API Management Tool
23
Denodo as a Data Service Provider
• Connect – Combine - Publish: {Rest}
one-click REST web services
deployment, establishing the REST
practices
‒ Protocol: Denodo’s REST format, OData 2.0
and OData 4.0, GraphQL
‒ Payload: XML, JSON, GEOJSON, RSS and
HTML
‒ Authentication: Basic HTTP, SPNEGO
(Kerberos), OAuth, (SAML)
‒ Documentation: OpenAPI (i.e. Swagger)
24
Denodo API provider
Denodo as Service Container
 Create services - no code/low code
 Host services (aka ‘Services Container’)
 Expose services as APIs
 Support contract first architecture
GraphQL support:
 Used as an abstraction layer between UI and REST services
 Decreases number of API requests
 Removes orchestration from the UI
 Denodo can provide declarative execution
API Gateway
25
Data Virtualization in the Data Services / API ecosystem
Data Service provider Abstraction data layer for Microservices API Management Tool
26
Denodo as Integration Layer for Microservices
Simplify Composite and Backend for Frontend (BFF)
Microservices
Leverage Denodo’s data management services
 Caching, security, auditing, data cleansing, resource
management, …
Combine Data
 Transform and combine data from different sources
Better Usability
 Single point of entry
 Same protocol
 Global Data Catalog
27
Denodo as abstraction data layer for Microservices
Denodo can serve as an abstraction between the microservice implementation and the data access to
simplify its development
 It enables technology changes in the backend without affecting the code of the Microservice (e.g.
legacy system migrations, vendor switch, etc.)
Microservices principles avoid performing data integration at the Microservice itself
 Using DV as a backend enables the independence of the Microservice from the integration
techniques
 The integration logic is performed in the DV layer in the form of virtual views
Although potentially each Microservice could have its own DV backend, a logical separation per
microservice (a schema) is usually a more realistic architecture
28
Data Virtualization in the Data Services / API ecosystem
Data Service provider Abstraction data layer for Microservices API Management Tool
29
Denodo as an API Management Tool
Since external APIs and web services can be registered in Denodo as data sources, Denodo’s
capabilities can act as a sort of API gateway:
 Centralized authentication and authorization
 Monitoring and access auditing
 Resource allocation policies (e.g. max 10 queries per hour for user A to service)
 Unified catalog
 API integration
However, keep in mind that is not an API gateway per se, and there are capabilities in API gateways
that don’t have an equivalent in Denodo (Network Security, Load Balancing…)
30
Denodo API Gateway
Denodo as API Gateway
 Expose services as APIs
 API discovery
 Mediate protocols
 Manage, secure, & monitor services and APIs
 Usage stats and analytics
Protect the sources
 Data in Motion – secure channels
 Data at Rest – secure storage
 Resources Management rules
31
Hybrid/Multi-Cloud Integration with centralized security /semantic access
Hybrid Data Hub
Common access point for both
internal and external sources
▪ Access to all sources as a single
schema with no replication:
Virtual data lake
▪ Enables combination of data
across sources, regardless of
nature and location
▪ Allows definition of common
semantic model
Active
Directory
Data CenterCloud
32
Read-Write Data Services – driving Call Center and Customer Portal
R Cable: Data Services for Single View of Customer
Business Need Solution Benefits
33
Drillinginfo Delivers Rapid Time-to-Market with Data
Virtualization
Drillinginfo is the leading SaaS and data analytics company for energy exploration
decision support, helping the oil and gas industry achieve better, faster results.
Drillinginfo services more than 3,200 companies globally from its Austin, Texas-based
headquarters.
▪ Business growth driving need to
develop new tools and models.
▪ Rapid time-to-market is crucial.
▪ Conventional Enterprise Data
Warehouse fed by ETL was not fast
enough for the data needs of the
development team.
▪ Needed a cost-effective solution to
reduce time to value.
▪ Raw data in the Data Warehouse and
refined data in MDM are virtually
connected using Denodo.
▪ Data Virtualization Layer combines the
views and exposes them as RESTful
services to the Analytics and Decision
Support applications internally.
▪ Provided search indices for external
clients that were building their own
apps based on these services.
▪ So far built 24 services around 11
core line of business entities.
▪ Response time cut to hours. Earlier it
took 2-3 days for ETL process to finish
and 2 more days to build data
interface.
▪ Now just 1 developer managing the
entire virtualization process.
▪ Saved Drillininfo precious time and
resources to achieve the primary
benefit of rapid time-to-market for
their products.
33
Shared Data Services Reused in Multiple App Dev –
Global Asset Management company
34
Data
Connectivity
Data Modeling
Layer
Unified
Semantic Model
Product Demonstration
35
Mitesh Shah
Senior Cloud Product Manager.
36
What’s the scenario – Exposing summary data across integrated view as a service
Note: We are exposing the data source as an API and managing the API via Denodo
Sources
Combine,
Transform
&
Integrate
Consume
Base View
Source
Abstraction
 Modernizing Data Warehouse in the Cloud
 Denodo providing DV, security & DaaS
(API)
▪ Multi Sources & APIs
▪ Data Linage / Management
▪ Realtime Visualization
▪ Data Story Telling
Demo
37
38
Summary / Takeaways - Data as a Service using Data Virtualization
The Foundation for the Data Services Layer
 Optimized for data services development
 Point-and-click configuration, zero coding, Rapid development and time-to-value
 Wider source support (on premise, cloud, SaaS)
 RDBMS, SOAP, REST, JSON, XML, Files, Legacy applications, NoSQL, etc.
 Supports multiple delivery styles (Industry most common)
 Real-time/right-time, batch/file, catching, multiple protocols support SQL, Web Services)
 Data architecture is key to addressing business needs.
 Denodo Platform can be that ray of light in your complex, heterogenous, multi-cloud landscape to bring back insights
in real-time
Try the 14 day Free Trial in the Cloud!
Cloud Modernization and Data as a Service Option
40
Next Steps
Try the 14 day Free Trial in the Cloud
GET STARTED TODAY
• Choice: Hosted by Denodo or under your cloud account
• Support: Community forum or remote sales engineer
• Optional: 30 minutes free consultation with Denodo Cloud
specialist
Thanks!
www.denodo.com info@denodo.com
© Copyright Denodo Technologies. All rights reserved
Unless otherwise specified, no part of this PDF file may be reproduced or utilized in any for or by any means, electronic or mechanical, including photocopying and microfilm,
without prior the written authorization from Denodo Technologies.
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Cloud Modernization and Data as a Service Option

  • 1. DATA VIRTUALIZATION PACKED LUNCH WEBINAR SERIES Sessions Covering Key Data Integration Challenges Solved with Data Virtualization
  • 2. Cloud Modernization and Data as a Service Mitesh Shah Senior Cloud Product Manager, Denodo
  • 3. Agenda1. Data - Cloud Modernization - Data Services 2. Data Virtualization & API Management 3. Customer Case Studies & Demo 4. Q & A
  • 4. 4 Poll Question: What is your familiarity with Data Virtualization as a means to data integration?
  • 5. Data – The Final Frontier!
  • 6. 6 Data – Like Oil – Is Not Easy To Extract and Use Although If Not Properly Managed, Can Lead to Waste!
  • 7. 7 But the Data is Somewhere in Here…
  • 8. 8 The Scale of the Problem…
  • 9. A Typical Cloud Journey – Why data services matter even more!
  • 10. Interesting Dimensions of Data in your Cloud Journey! Yes, but..  New data silos  Security  Latency Your Sources in the Cloud  SaaS apps: SFDC, Social Media, etc.  Cloud RDBMS: Amazon RDS, Azure SQL Database, etc  Cloud Analytics: Snowflake, Amazon Redshift, SparkSQL Why?  More flexible  Access from Anywhere  Lower Cost of Operations Challenges • Data is in many locations, data formats, Cloud, on-premise, SaaS.. • Simple tasks become more challenging as the data gets more dispersed • How do users know what data is available? find and access the data?
  • 11. 11 Poll Question: What is your top challenge when it comes to integrating data in the cloud ? (check all that apply)
  • 13. Cloud Modernization & Key Initiatives in the Cloud? Source: Denodo Cloud Survey 2020
  • 14. Why Cloud Modernization and How Does Data as a Service fits in? Modernize Your Applications, Drive Growth and Reduce TCO, by migrating them to the cloud to maximize the use of cloud infrastructure scaling capabilities and cost structure. Enable companies to leverage data as an API services layer to accelerate the development of the cloud native microservices architecture Driving continuous & agile business transformation to derive faster and valuable insights in form of Analytics and ML/AI in the Cloud Data as a service (DaaS) - hybrid data management strategy that leverages cloud to deliver data storage, integration, processing, and/or analytics services over the cloud backbone.
  • 15. 15 Data Virtualization – Realtime – Simplified Integration Real-time Data Integration Consume in business applications Combine related data into views Connect to disparate data sources 2 3 1 DATA CONSUMERS Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users, IoT/Streaming Data Multiple Protocols, Formats Query, Search, Browse Request/Reply, Event Driven Secure Delivery DATA CONSUMERSAnalytical Operational Web Services DISPARATE DATA SOURCES Databases & Warehouses, Cloud/SaaS Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word... Less StructuredMore Structured SQL, MDX Big Data APIs Web Automation and Indexing DATA VIRTUALIZATION CONNECT COMBINE CONSUME Agile Development Performance Data Services Resource Management Data Catalog Governance & Metadata Security and Data Privacy Lifecycle Management “Data virtualization integrates disparate data sources in real time or near-real time to meet demands for analytics and transactional data.” – Create a Road Map For A Real-time, Agile, Self- Service Data Platform, Forrester Research, Dec 16, 2015
  • 16. Data Virtualization in the API Ecosystem (Enabling DaaS)
  • 17. APIs(Application Programming Interface) – Building Blocks of Digital Transformation APIs are the foundations of digital transformation  Enable the integration of diverse IT systems, building more collaborative and self-service IT environments  Enables exposing data and processes to other business units and/or partners  Create revenues from existing assets, and support creation of new products and business models These initiatives have created an API Economy
  • 18. 18 Data Services Layer (Data API) A data access layer that abstracts underlying data sources and exposes them as discrete services to form a ‘data API’  Different users and developers across the enterprise can access data in a secure and managed fashion and share a common data ‘model’  Provides secure and managed access to data across the enterprise  Provides consistency of data & hides complexity, format, and location of actual data sources  Supports many consumption protocols and patterns Example: Single data access layer for all development teams to avoid ‘hunting down and interpreting data differently by project’
  • 19. Data Virtualization in the API Ecosystem Data virtualization platforms like Denodo can play a significant role in an API ecosystem without writing NEW CODE Let’s review three common architectures: 1. Data Virtualization as a Data Service provider 2. Data Virtualization as an abstraction data layer for Microservices 3. Data Virtualization as an API Management tool 19
  • 20. 20 API Ecosystem: Create Complex Data Services in Minutes • Create data services - no code…..……………………. • Host services (aka ‘Services Container’)…………. • Multiple protocols/formats APIs SAOP REST……. • API Developer Porta………………………………………….. • Leading Security Standards……………………………… • Complex security policies…………………………………. • Co-ordinate services…………………………………………. • API discovery (Open API )………………………………… • Quotas and workload management…………………. • API Lifecycle, versioning, retirement……………….. • Usage stats and analytics………………………………….            Denodo Platform          
  • 21. 21 Denodo abstracting SaaS APIs – As API Consumer SQL Enable any kind of SaaS API  SaaS-to-SQL: DV abstracts the SaaS API (usually REST services) as part of a relational model  Real Time access: avoids replication of Cloud data back into the data center  Unique relational approach to cloud data integration  Different from most flow-based iPaaS vendors SQL API MART
  • 22. 22 Ways to maximize Data Virtualization in a DaaS model Data Service provider Abstraction data layer for Microservices API Management Tool
  • 23. 23 Denodo as a Data Service Provider • Connect – Combine - Publish: {Rest} one-click REST web services deployment, establishing the REST practices ‒ Protocol: Denodo’s REST format, OData 2.0 and OData 4.0, GraphQL ‒ Payload: XML, JSON, GEOJSON, RSS and HTML ‒ Authentication: Basic HTTP, SPNEGO (Kerberos), OAuth, (SAML) ‒ Documentation: OpenAPI (i.e. Swagger)
  • 24. 24 Denodo API provider Denodo as Service Container  Create services - no code/low code  Host services (aka ‘Services Container’)  Expose services as APIs  Support contract first architecture GraphQL support:  Used as an abstraction layer between UI and REST services  Decreases number of API requests  Removes orchestration from the UI  Denodo can provide declarative execution API Gateway
  • 25. 25 Data Virtualization in the Data Services / API ecosystem Data Service provider Abstraction data layer for Microservices API Management Tool
  • 26. 26 Denodo as Integration Layer for Microservices Simplify Composite and Backend for Frontend (BFF) Microservices Leverage Denodo’s data management services  Caching, security, auditing, data cleansing, resource management, … Combine Data  Transform and combine data from different sources Better Usability  Single point of entry  Same protocol  Global Data Catalog
  • 27. 27 Denodo as abstraction data layer for Microservices Denodo can serve as an abstraction between the microservice implementation and the data access to simplify its development  It enables technology changes in the backend without affecting the code of the Microservice (e.g. legacy system migrations, vendor switch, etc.) Microservices principles avoid performing data integration at the Microservice itself  Using DV as a backend enables the independence of the Microservice from the integration techniques  The integration logic is performed in the DV layer in the form of virtual views Although potentially each Microservice could have its own DV backend, a logical separation per microservice (a schema) is usually a more realistic architecture
  • 28. 28 Data Virtualization in the Data Services / API ecosystem Data Service provider Abstraction data layer for Microservices API Management Tool
  • 29. 29 Denodo as an API Management Tool Since external APIs and web services can be registered in Denodo as data sources, Denodo’s capabilities can act as a sort of API gateway:  Centralized authentication and authorization  Monitoring and access auditing  Resource allocation policies (e.g. max 10 queries per hour for user A to service)  Unified catalog  API integration However, keep in mind that is not an API gateway per se, and there are capabilities in API gateways that don’t have an equivalent in Denodo (Network Security, Load Balancing…)
  • 30. 30 Denodo API Gateway Denodo as API Gateway  Expose services as APIs  API discovery  Mediate protocols  Manage, secure, & monitor services and APIs  Usage stats and analytics Protect the sources  Data in Motion – secure channels  Data at Rest – secure storage  Resources Management rules
  • 31. 31 Hybrid/Multi-Cloud Integration with centralized security /semantic access Hybrid Data Hub Common access point for both internal and external sources ▪ Access to all sources as a single schema with no replication: Virtual data lake ▪ Enables combination of data across sources, regardless of nature and location ▪ Allows definition of common semantic model Active Directory Data CenterCloud
  • 32. 32 Read-Write Data Services – driving Call Center and Customer Portal R Cable: Data Services for Single View of Customer
  • 33. Business Need Solution Benefits 33 Drillinginfo Delivers Rapid Time-to-Market with Data Virtualization Drillinginfo is the leading SaaS and data analytics company for energy exploration decision support, helping the oil and gas industry achieve better, faster results. Drillinginfo services more than 3,200 companies globally from its Austin, Texas-based headquarters. ▪ Business growth driving need to develop new tools and models. ▪ Rapid time-to-market is crucial. ▪ Conventional Enterprise Data Warehouse fed by ETL was not fast enough for the data needs of the development team. ▪ Needed a cost-effective solution to reduce time to value. ▪ Raw data in the Data Warehouse and refined data in MDM are virtually connected using Denodo. ▪ Data Virtualization Layer combines the views and exposes them as RESTful services to the Analytics and Decision Support applications internally. ▪ Provided search indices for external clients that were building their own apps based on these services. ▪ So far built 24 services around 11 core line of business entities. ▪ Response time cut to hours. Earlier it took 2-3 days for ETL process to finish and 2 more days to build data interface. ▪ Now just 1 developer managing the entire virtualization process. ▪ Saved Drillininfo precious time and resources to achieve the primary benefit of rapid time-to-market for their products. 33
  • 34. Shared Data Services Reused in Multiple App Dev – Global Asset Management company 34 Data Connectivity Data Modeling Layer Unified Semantic Model
  • 36. 36 What’s the scenario – Exposing summary data across integrated view as a service Note: We are exposing the data source as an API and managing the API via Denodo Sources Combine, Transform & Integrate Consume Base View Source Abstraction  Modernizing Data Warehouse in the Cloud  Denodo providing DV, security & DaaS (API) ▪ Multi Sources & APIs ▪ Data Linage / Management ▪ Realtime Visualization ▪ Data Story Telling
  • 38. 38 Summary / Takeaways - Data as a Service using Data Virtualization The Foundation for the Data Services Layer  Optimized for data services development  Point-and-click configuration, zero coding, Rapid development and time-to-value  Wider source support (on premise, cloud, SaaS)  RDBMS, SOAP, REST, JSON, XML, Files, Legacy applications, NoSQL, etc.  Supports multiple delivery styles (Industry most common)  Real-time/right-time, batch/file, catching, multiple protocols support SQL, Web Services)  Data architecture is key to addressing business needs.  Denodo Platform can be that ray of light in your complex, heterogenous, multi-cloud landscape to bring back insights in real-time Try the 14 day Free Trial in the Cloud!
  • 40. 40 Next Steps Try the 14 day Free Trial in the Cloud GET STARTED TODAY • Choice: Hosted by Denodo or under your cloud account • Support: Community forum or remote sales engineer • Optional: 30 minutes free consultation with Denodo Cloud specialist
  • 41. Thanks! www.denodo.com [email protected] © Copyright Denodo Technologies. All rights reserved Unless otherwise specified, no part of this PDF file may be reproduced or utilized in any for or by any means, electronic or mechanical, including photocopying and microfilm, without prior the written authorization from Denodo Technologies.