The document discusses the significance of IoT integration and how Denodo supports it through data virtualization, enhancing analytics and operational efficiency. It highlights the exponential growth in IoT devices and provides insights into IoT monetization strategies and use cases. A customer case study exemplifies how Denodo's data virtualization can improve asset performance and create new business opportunities.

1. O C T O B E R 1 8 , 2 0 1 6 S A N F R A N C I S C O B A Y A R E A , C A
#DenodoDataFest
RAPID, AGILE DATA STRATEGIES
For Accelerating Analytics, Cloud, and Big Data Initiatives.

2. The Role of Data Virtualization in IoT
Integration
Lakshmi Randall
Head of Product Marketing, Denodo
Twitter: @LakshmiLJ

3. Agenda
1.What’s so important about IoT Integration?
2.How does Denodo support IoT Data Integration?
3.Customer Case Study
3

4. IoT is invading our kitchen!
4

5. What’s so important about IoT
Integration?
5

6. The Importance of IoT Integration
 Investment in IoT devices is soaring
 IoT is proliferating across all business and
consumer sectors
 Data generated in the IoT offers a Data
Monetization Model
6

7. IOT Investment
 2016: IoT hardware purchases surpass
$2.5 million per minute.
 2021: one million IoT devices procured
and installed per hour.
IoT Proliferation
 2018: 6 billion connected devices
require support.
 2020: >21 billion connected devices
in operation.
 2020: industry-specific devices number
2.9 billion (nearly 200% growth since
2015).
IoT Investment & Proliferation Milestones
7
Source: Gartner 2016

8. IoT Monetization
 Enhance traditional products with sensors
and connectivity
 Offer bundled services for connected things
(e.g., connected cars)
 Collect, Aggregate, Anonymize and
Monetize.
8

9. IoT Use Cases
9
Preventative &
Proactive
Maintenance
Data Monetization
(information-
oriented products
& services)
Customer
Satisfaction &
Retention
Operational
Efficiency (asset &
equipment
optimization)
Safety Security
Fraud Detection
Real-time
Analytics
Patient care

10. IoT Endpoints for 2020 by Sector
10
Source: Gartner, April 2016

11. How does Denodo support IoT
Data Integration?
11
Data-in-transit and Data-at-rest

12. Big Data Connectivity
BigData and Cloud Databases Connectivity
■ Hadoop Ecosystem:
■ SQL on Hadoop: Hive, Impala, Presto,…
■ HDFS, Parquet, Avro, CSV…
■ Execution of map/reduce Jobs
■ Certified with major Hadoop distributions
■ In-memory platforms: Apache Spark, Presto DB, HANA,…
■ Parallel DWs and Appliances: Vertica, Impala, Teradata, Greenplum,…
■ Cloud RDBMS: Redshift, Snowflake, DynamoDB,…
■ NoSQL (MongoDB, CouchDB, Neo4J, Redis, Oracle NoSQL, Cassandra, etc.)
■ Streaming data (Spark streams, Splunk, IBM Streams, Kafka,…)
12
Enhanced Adapters for Big Data ecosystem

13. 13
Request-Response:
Named adapters for stream
services:
 Kafka
 IBM Streams
Streaming:
Extend current JMS support
with:
 Enhanced support for
temporary windows
 Support for MQTT
Enhanced Integration with IoT - Streaming
Enhanced Adapters for the Internet of Things Ecosystem
JMS
MQTT
JMS
MQTT

14. Data Ingestion
■ Batch, On-demand and Streaming Data
Ingestion
■ Simultaneously supports Batch and
Streaming data integration
■ Learns to extract structured data from
semi-structured content using Machine
Learning
■ Ingest the data in a schema-agnostic way
including schema-on-read and multiple
schemas
14
Batch, On-demand and Streaming Data Ingestions

15. Enrich Machine Data and Combine with Other Data
Ingest, Integrate & Deliver
Persisted
(In-memory, Hadoop)
Streams
(specific time window)
Message Queue
Machine-generated/Event data Alerts
Workflows
Operational
Processes
Analytical
Processes
Consumers
Visualization
Data Virtualization
Enrich and Combine IoT
Data with Other Data
Historians
Streams
ERP/SCM
DW
Analytical
DB
MDM
Apps
Data
Marts
Hadoop NoSQL

16. 16
Security
Data in Motion – secure channels
• Using SSL/TLS
• Client-to-Denodo and Denodo-to-source
• Available for all protocols (JDBC, ODBC, ADO.NET and WS)
Data at Rest – secure storage
• Cache: third party database. Can leverage its own encryption mechanism
• Swapping to disk: serialized temporarily stored in a configurable folder that can be encrypted by the OS
Encryption/Decryption and Data Masking
• Support for custom decryption for files and web services
• Transparent integration with RDBMs encryption
Authentication and Authorization
• LDAP/AD, Kerberos support, Granular data security,
Securing data

17. Customer Case Study
17

18. Leading Construction Manufacturer - Telematics &
Predictive Maintenance
Dealer
Maintenance
Parts Inventory
OSI PI Hadoop Cluster
Tableau: Dealer / Customer Dashboard

19. Business Benefits
 Improved asset performance and proactive maintenance.
 Reduced warranty costs due to proactive maintenance of
parts preventing parts failure.
 Optimized pricing for services and parts among global service
providers.
 New Business Model opportunities based on real-time
analysis of detailed sensor data.

20. Data Virtualization Benefits
Implement a Single Logical Data Lake Using Data Virtualization
Improves the
enterprise func-
tionality of data
lakes by
combining one or
more physical
data lakes with
other enterprise
data
Provides a way to
access data from
separate systems
through an
abstraction layer
that makes it
appear as if the
data were in a
single data lake
Improves an
organization’s
ability to govern
and extract more
value from its
data lakes by
extending them
as logical data
lakes
20

21. Key Takeaways
 Identify if and how IoT data will benefit your organization
 Identify your potential IoT Data sources
 Employ Data Virtualization to combine IoT data with other data to
enhance the use and value of data assets
 Employ a Logical Data Lake/Logical Data Warehouse architecture to
eliminate the cost of storing information in multiple places, to
govern IoT data access, and to prevent IoT data from becoming
siloed.
21

22. Q&A

23. Thank you!
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O C T O B E R 1 8 , 2 0 1 6 S A N F R A N C I S C O B A Y A R E A , C A
#DenodoDataFest