Watch full webinar here: https://buff.ly/3OCQvGk
In this session, Denodo Sales Engineer, Yik Chuan Tan, will guide you through the art of delivering a compelling demo of the Denodo Platform with Denodo Demo Lite. Watch to uncover the significant functionalities that set Denodo apart and learn how to effectively win over potential customers.
In this session, we will cover:
Understanding the Denodo Platform & Tailoring Your Demo to Prospect Needs: By gaining a comprehensive understanding of the Denodo Platform, its architecture, and how it addresses data management challenges, you can customize your demo to align with the specific needs and pain points of your prospects, including:
- seamless data integration with real-time access
- data security and governance
- self-service data discovery
- advanced analytics and reporting
- performance optimization scalability and deployment
Watch this Denodo demo session and acquire the skills and knowledge necessary to captivate your prospects. Whether you're a seasoned technical professional or new to the field, this session will equip you with the skills to deliver compelling demos that lead to successful conversions.
2. AGENDA
● Data Management Challenges
● Denodo Platform Overview
● Introduction of Denodo Demo Lite
● Value Propositions of Denodo
● Demo
● Q&A
3. 3
Data Management Challenges
Data silos causing long delays in finding answers to
business problems, resulting in longer time-to-value
Hybrid/multi-cloud ecosystems complicate data
access
Complexity of data governance trying to enforce
consistent policies across many data sources
Data architecture costs continue to grow
Physically centralizing data creates bottlenecks
Data ecosystems are complex resulting in data
assets being underutilized
4. 4
BI Tools Data Science Tools
Denodo Platform Architecture
DATA CATALOG
Discover - Explore - Document
DATA AS A SERVICE
RESTful / OData
GraphQL / GeoJSON
SQL
CONSUMERS
Self-Service
Hybrid/
Multi-Cloud
Query
Optimization
AI//ML
Recommendations
Security
DATA
INTEGRATION
,
MANAGEMENT,
AND
DELIVERY
PLATFORM
SOURCES
150+
data
adapters
Apps Streaming
Data
Governance
SaaS
Files
OLAP
Hadoop
& NoSQL
Cloud
Stores
Traditional
DB & DW
INTEGRATE
disparate data in any location, format or latency
MANAGE
related data into views with universal semantic model
DELIVER
using BI & data science tools, data catalog, and APIs
5. 5
How Does It Work?
Development
Lifecycle Mgmt
Monitoring
& Audit
Governance
Security
Development Tools
and SDK
Scheduled Tasks
Data Caching
Query Optimizer
Mobile, Web, Users
Enterprise application, ESB Reporting, BI, Portals
Databases &
warehouses
Enterprise
applications
Cloud/SaaS
applications
XML, Excel,
Flat Files
Big data
NoSQL
Collaboration
Web 2.0
Data Source Layer
Derived View Derived View
Unified View Unified View
Unified View
Unified View
Customer360
View
Data Mart
View
Application Layer
Business Layer
Transformation &
Cleansing
J
J J
S J
A
J
U
JDBC/ODBC/ADO.Net SOAP/REST WS
Base View Base View Base View Base View Base View Base View
Abstraction
Base View
6. 7
1. Ease of use
Data Consumers have a single location to access any data.
A logical data layer that centralizes your data, enabling real-time access to all data.
2. Centralized security and governance
Access control and policy implementation are done consistently in a single location.
Facilitate compliance to audit requirement and data privacy laws.
3. Faster Time-to-Value
Building new data views and model logically can be done more quickly and hence shorten the time
to deliver to the right group of users
4. Future-proof
Decoupling from data location and schemas allows for technology evolution and infrastructure
changes.
Business Values of Denodo
8. 9
Main components and how they interact
Security label
Denodo VDP
- Data catalog
- Scheduler
- Design studio
Solution Manager
- License Mgr
- SM Server
- SM web admin
HOST ( i.e Your laptop –Running Windows 10/11)
Oracle VirtualBox: with Demo
LITE (VM)
Denodo Admin
Tool
Web Browser
9. 10
Demo Scenario
What’s the total amount of sales across each
store
▪ Sales Data stored in on-premise
Oracle Data Warehouse
▪ Store Data dispersed in a Post-gres
Database
▪ Need to Include date dimension
Sources
Combine,
Transfor
m
&
Integrate
Consume
Base View
Source
Abstraction
join
group and sum
Sales
(30 million rows)
Store
(300 rows)
Date_Dim
Data Catalog
Virtual Table (View)
Role Based Security
& Masking
Push Down
Optimization
& Caching
SaaS
App
Data Services
10. 11
Single Platform – Multiple roles
Denodo Developer
Business User
& BI Analyst
Data Scientist
Application-to-
Application
Administration &
Operations
Sales Manager “dcox”
User
“Admin”
Purchasing Manager “dburns”