The document provides an overview of a briefing on data virtualization and its impact on enterprise software, emphasizing the significance of integrating data from various sources, including IoT and traditional data channels. It features insights from Cisco's Chief Technology Officer, David Besemer, regarding the evolution of data analytics and the importance of real-time streaming capabilities in managing distributed data. The session aims to engage vendors, analysts, and audience members in discussing innovative technologies and business opportunities arising from effective data management.

1. Grab some
coffee and
enjoy the
pre-show
banter before
the top of the
hour!

2. The Briefing Room
A Connected Data Landscape: Virtualization and the Internet of Things

3. Twitter Tag: #briefr The Briefing Room
Welcome
Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com
@eric_kavanagh

4. Twitter Tag: #briefr The Briefing Room
Reveal the essential characteristics of enterprise
software, good and bad
Provide a forum for detailed analysis of today s innovative
technologies
Give vendors a chance to explain their product to savvy
analysts
Allow audience members to pose serious questions... and
get answers!
Mission

5. Twitter Tag: #briefr The Briefing Room
Topics
March: BI/ANALYTICS
April: BIG DATA
May: CLOUD

6. Twitter Tag: #briefr The Briefing Room
An Inflection Point for Data
RETHINK your architecture
RECAST your opportunities
REDEFINE your business

7. Twitter Tag: #briefr The Briefing Room
Analyst: Robin Bloor
Robin Bloor is
Chief Analyst at
The Bloor Group
robin.bloor@bloorgroup.com
@robinbloor

8. Twitter Tag: #briefr The Briefing Room
Cisco
Cisco Systems is a known leader in the design,
manufacturing and sales of networking equipment
Through its acquisition of Composite Software, Cisco has
expanded its footprint in the data virtualization space
Cisco now offers infrastructure solutions to manage and
analyze streaming data

9. Twitter Tag: #briefr The Briefing Room
Guest: David Besemer
David Besemer is the Chief Technology Officer of
the Data Virtualization Business Unit (formerly
Composite Software) at Cisco. David works
directly with customers to guide their data
virtualization strategies as well as Cisco's
technology vision and roadmap. David joined
Composite as VP of Engineering in 2002, and
became the CTO in 2006. Before Composite he
was a venture capital CTO in residence, headed
software product marketing at NeXT Computer,
built program trading systems on Wall Street, and
researched natural language processing systems
at GE’s Corporate R&D center. David holds a BS in
Computer Science from Michigan State University
and an MS in Computer Science from Rensselaer
Polytechnic Institute.

10. The Connected Data Landscape
David Besemer
CTO
Data Virtualization Business Unit
March 3, 2015

11. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Business Opportunity:
As Data Grows, Leading Businesses Use it to Drive Better Outcomes
• Customer Profitability
• Faster Time to Market
• Cost Reduction
• Risk Management
• Compliance
• Overall Agility
Other
Businesses
Business
Leaders
BusinessOutcomes
Data
Business Outcomes

12. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Data Silos Proliferating: Data is Now Distributed Everywhere
Cloud Data
Sources
Big Data / IoT
Sources
Traditional
Data Sources
How Does the Business Leverage All the Data?

13. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Widely
Distributed,
Streaming,
Short
Shelf
Life,
Too
Big
to
Consolidate
“Most data will be
processed at the edge”
(mobile devices, appliances, routers)
Digital Enterprises See an Explosion of Data at the Edge
1230 respondents
Source: Cisco
Consul;ng
Services
Global
IoT
Study,
2014
37%

14. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Analytics 1.0 Analytics 2.0
Historically, Data has Been Moved, then Analyzed
Traditional Data
Warehouse
Traditional Data
Warehouse
Structured
Data
Unstructured
Data
Structured
Data
Big Data
Store
DV
Hours/Minutes/SecondsDays/Hours

15. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
The Key is Combining Data at the Edge with Data You Store
Data You Store
Big Data
Store
DV
Traditional Data
Warehouse
Data At
The Edge

16. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Most Valuable
Insight
The Key is Combining Data at the Edge with Data You Store

17. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
12.5 Billion
25 Billion
50 Billion
2015
2020
2010
Explosion of IoT Connected Devices

18. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
IoT World Forum Reference Model
Levels
Application
(Reporting, Analytics, Control)
Data Abstraction
(Aggregation & Access)
Data Accumulation
(Storage)
Edge Computing
(Data Element Analysis & Transformation)
Connectivity
(Communication & Processing Units)
Physical Devices & Controllers
(The “Things” in IoT)
Collaboration & Processes
(Involving People & Business Processes)
1
2
3
4
5
6
7
Sensors, Devices, Machines,
Intelligent Edge Nodes of all types
Center
Edge
Data
at
Rest
Data
in
Mo;on

19. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
1
2
3
4
5
6
7
Sensors, Devices, Machines,
Intelligent Edge Nodes of all types
Center
Edge
Levels
IT
OT
Query
Based
Event
Based
Data at
Rest
Data in
Motion
Non-real
Time
Real
Time
IoT World Forum Reference Model

20. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Operational ConsistencyData Mobility Optimized Form Factors
UCS Mini
UCS
Mini
UCS for
Enterprise
UCS for Hadoop
Nexus Family
ISR
APIC EM
APMS
CGR
IE
Video
Cloud Services
and Applications
Partner Clouds
Intercloud Core Data Center
Cisco Delivers the Connected Infrastructure You Need
to Reach from the Data Center to the Edge
Fog and Edge

21. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Levels
Application
(Reporting, Analytics, Control)
Data Abstraction
(Aggregation & Access)
Data Accumulation
(Storage)
Edge Computing
(Data Element Analysis & Transformation)
Connectivity
(Communication & Processing Units)
Physical Devices & Controllers
(The “Things” in IoT)
Collaboration & Processes
(Involving People & Business Processes)
1
2
3
4
5
6
7
Sensors, Devices, Machines,
Intelligent Edge Nodes of all types
Center
Edge
Data
at
Rest
Data
in
Mo;on
IoT World Forum Reference Model

22. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
• Mine (fetch)
• Analyze
• ReportUsage Data
!
Generate an
Actionable
Event
that is sent to the
Policy System,
Management
System, etc. to
allow immediate
control
Next Generation Analytics
Applies predicates, aggregations, and joins
with metadata tables and contextual data to
identify and match trends.
Querybase Waiting for Data
Store raw data or filtered data for
further mining.
Database Waiting for Queries
Store raw data for further mining.
Traditional Analytics Model
Store first, and query later.
Usage Data
• Mine (fetch)
• Analyze
• Report
Connected Streaming Analytics

23. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Make your data work for you
Make it actionable in real time
Make it scale without sacrificing latency
Integrate advanced predictive analytics and machine learning
Transparently combine both live and historic data
Value of Real-Time Connected Streaming Analytics

24. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Cloud Data SourcesBig Data / IOE SourcesTraditional Data Sources
AnalyticsBusiness Intelligence
Cisco Data Virtualization
Abstrac;on
Caching
Directory
Federa;on
Security
Governance
Transforma;on
Cisco Data Virtualization

25. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
On-demand
Access
Easier and
Faster
Up to 75%
Cost Savings
Cisco Data Virtualization
More AgileHigher Impact Less Expensive
Cisco Data Virtualization
Better Business Outcomes, Faster, for Less

26. ©
2015
Cisco
and/or
its
affiliates.
All
rights
reserved.
Cisco
Confiden;al
Analytics 3.0 Seconds/Milliseconds
Traditional Data
Warehouse
Big Data
Store
DV
Real-time/
Streaming
− Cloud
− Data Center
− Fog and Edge
Connecting Distributed Data from the Data Center to the Edge
Analytics 3.0 Requires a New Approach

28. Twitter Tag: #briefr The Briefing Room
Perceptions & Questions
Analyst:
Robin Bloor

29. Then the Data
Lake evaporated
into the Cloud
Moving
Stuff
Robin Bloor, PhD

30. The Architecture of Motion
Move the DATA to the processing
OR
Move the PROCESSING to the data
OR
Move the processing AND the data
OR
Shard and move

31. The Global Picture
u IoT (embedded)
u IoT depots
u Wearables
u Mobile devices
u Web sites (depots)
u Desktops
u Data centers
u Cloud (depots)
u The network(s)
All can be data creators, data
stores and processing points.
All should be state machines.

32. The Target(s)
These generalized targets are probably
universal
u The necessary or best
response time
u Appropriate availability
up to full fault tolerance
u Portability - distribution
u Affordable cost of
operation (for the
benefit delivered)

33. Distributed Processing
u The mechanisms for this are
caching and virtualization
u Sharding involves the caching
or virtualization of specific
fragments (imagine virtualizing
all or part of Hadoop)
u The management of this
requires the software to be
infrastructure-aware
u Service levels need to be
specifically defined
u It is made even more complex
by the reality that all these
resources are shared

34. Network-Aware Applications
Ultimately we will have
INFRASTRUCTURE-AWARE
software that distributes data and
applications

35. u I agree with the Cisco vision. But where has Cisco
applied this thus far? What use cases can you tell
us about?
u Traditionally Cisco is hardware and networking
infrastructure. Is the company going soft? If so, is
this just for the Big Data business?
u What are the security components that Cisco
brings to the game?
u Global directory?

36. u Which vendors are you actively partnering with
to deliver this vision?
u How easy is this? Can you discuss the nature of
a real-world deployment of these capabilities?
u Is the IoT reference model a blueprint for all
distributed infrastructure and supporting
software?

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Upcoming Topics
www.insideanalysis.com
March: BI/ANALYTICS
April: BIG DATA
May: CLOUD

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THANK YOU
for your
ATTENTION!
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