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2© Copyright 2017 Dell Inc.2
Building a data driven organisation
Hans Timmerman
CTO Dell EMC The Netherlands
Data is zowel de olie als het goud voor een organisatie:
• olie als smeermiddel,
• goud wanneer die data waarde en bescherming nodig heeft.
Die twee tegenstrijdige waarderingen moeten gelijktijdig in een data-architectuur worden geborgd.
Net zoals Big Data en Fast Data daarin een plaats moeten krijgen.
3© Copyright 2016 Dell Inc.3
A few words about Dell EMC
Hans Timmerman
CTO Dell EMC The Netherlands
4
Strategically Aligned
Businesses
Dell Technologies
Dell Inc.
Client Solutions
GroupGlobal ServicesInfrastructure
Solutions Group
Dell Technologies - World’s largest privately controlled Tech Company 74 B$ revenue – 140.000 team members - 20.000+ patents - $4.5 billion on R&D/year
A data driven organisation . . .
in a data driven world . . .
© Copyright 2017 Dell Inc.
6
FEEDING 9 BILLION PEOPLEBY 2050
7
THE PRECISION FARMING REVOLUTION
8
THE NEW OPPORTUNITY…
Product DATA About
The Product
INTENT
CONTEXT
REAL-TIME
9
MULTI-SOURCE DATA NEEDSDELIVERING ACTIONABLE INSIGHT IN REAL-TIME
WEATHER FORECASTING
SOIL ANALYSIS MACHINE DATA
$100 MORE PROFIT/ACRE$43K INCREASE IN ANNUAL PROFIT
20% GREATER YIELD
REAL TIME OPERATIONS
INFRAAs a Service
Realtime
RISKmanagement
Realtime
Enterprise
SERVICES
Flash/vSAN/vLANHyper Converged Infrastructures
Hyperscale Elastic Cloud Services Software Defined
Enterprise-grade Hybrid Cloud
Analytics
Mobile / Apps
Cloud based
Agile DevOps
Micro services
Distributed/compartmented
Real time Analytics
Intelligence
Quick response
Transparency
REALTIMEOrganization Collective and Prescriptive Intelligence
Become Digital (always on, anywhere, anytime)
Drive Change (disrupt instead of being disrupted)
Ecosystem & Alliance versatility
Realtime Customer Engagement
Automated
Shared, open, reliable data
BUSINESS IMPERATIVE #1
11
Back Office Front Office
System Centric User/device Centric
Systems of Record• IT driven, Robust
• Transactional oriented
• Data centric
• Safe & secure
• Structured
Systems of Insight• Data Governance
• Analytics
• Big Data
• Business
Intelligence
Systems of Engagement• Interaction oriented
• Contact & collaboration
• User experience
• Mobile
• Unstructured
Shared Data
Shared, open, reliable data . . . .
. . . demand well organized data management
BIG DATA SMART DATA FAST DATA
SUPPORTED BY HYBRID CLOUD PLATFORMS (as a utility)
12© Copyright 2017 Dell Inc.12
Changing value of data over time
Value
Timeus sec minms dayhr yearmonth decade
Value of
data sets
Value of
the collected
data sets
Big DataFast Data
• Processes
• Models
• Logics
• Algoritms
• Trends
Challenge is
combining them
Predictive Capability
Real Time Analysis
on collected
Intelligenge
1313
Growth acceleration of the digital universe
The essence of Data Gravity
© Copyright 2017 Dell Inc.
Data and applications are attracted to each other . . .
An application eats data
1414
Data gravity with equal data mass
Data Application
Data and applications are attracted to each other . . .
Data is nothing without an application
An application is nothing without data
© Copyright 2017 Dell Inc.
1515
But when data masses differ . . . (1)
Data
Typical 2nd platform behaviour
Large Applicationsbillion lines of code
Small data sets
Data
Data
Data
Data
Data
Data
Data
ApplicationApplication Centric
Architectures
STRUCTURED
Non movable
application
Application is critical about
the data to be presented . .
16
But when data masses differ . . . (2)
Application
AppApp
App
App
App
App
App
Data
Typical 3rd platform behaviour
Big Datalakesbillion bytes
Small applications
micro services
Data Centric
Architectures
Non movable data
© Copyright 2017 Dell Inc.
17
But when data and app shrink. . . (3)
ApplicationData
Typical 4th platform behaviour
Fast streaming
dataIntelligent
micro services
movable data
© Copyright 2017 Dell Inc.
movable services
The Internet of Things
Application
Application
18
Dawn of a new era
© Copyright 2017 Dell Inc.18
19© Copyright 2017 Dell Inc.19
The cycle of the cloudCentral
Local
Mainframe
Closed
Source
Client Server
Cloud
Edge Intelligence
Open
Source
Deep
learning
Machine
learning
Fast Data
Big Data
Product(HW + SW)
Service
Terminal
use
Smart
device
Big
Applications
© Copyright 2017 Dell Inc.20
The internet of things
Edge intelligence
Fog Computing Mist Computing
21© Copyright 2017 Dell Inc.21
7 billionconnected people
44 zettabytesof data
30 billionconnected devices
Scale magnitudes modernized
Software driven
22
22
IOT: HISTORY & DEVELOPMENT
1969
1966
In just a few decades, computers
will be embedded into almost every
industrial product.
Karl Steinbuch (Cybernetic Engineer)
Arpanet
1984
DNS
1991
WWW
online
1993
Coffee pot in the University of
Cambridge computer lab
1998
1999
Kevin Ashton from MIT uses the term
"Internet of Things" for the first time
LG announces first
online refrigerator
2008
IoT Conference
Zurich
2011
IPv6
2005
Arduino
Open source
platform for
microcontrollers
Nest
Sources: MIT, Gartner, PostScapes
2000 2010
Tu
rin
g, T
esla
, M
ors
e
2014
Industrial
Internet
Consortium
2017
8.4 Billion Connected “Things”
in use worldwide
(world population: 7.5 Billion)
Gartner
EdgeX Foundryvendor-neutral open source project
hosted by the Linux Foundation.Building a common open framework
for Industrial IoT edge computing.
The Industrial Internet Consortium publishes the First industrial
internet connectivity framework
NIST definition*)publicatie 800 – 191
‘Fog computing is een horizontaal, fysiek of virtueel resourceparadigma dat
zich bevindt tussen slimme end-devices en traditionele cloud- of datacenters.
Dit paradigma ondersteunt verticaal geïsoleerde en latency-gevoelige applicaties
door een alom vertegenwoordigde, schaalbare, gelaagde, gefedereerde en
gedistribueerde computing, storage en netwerkconnectiviteit.’
Kort gezegd is fog computing een cloud-gebaseerd-ecosysteem dat
slimme end-devices in gekoppelde netwerken kan ondersteunen.
Mist computing is een lichte variant en rudimentaire vorm van fog computing.
*) NIST (US National Institute for Standards and Technology)
24
And at the beginning there was one lake…
Centralization
As the traditional approach to
gain analytical insight from data
in disparate sources
Batched data gathered in a single
repository or cloud in preparation
for analysis
25
Now a new class of problems emerge . . .
26
To one lake, or to multi-lake . . .
The perfect datai-mobility storm
IoT effect
Migration
to the edge
Regulatory
compliance
Bandwidth
contraints
Legacy
data
28
Technologies enabling distributed architectures
Machine Learning at the Edge
Deep Learning in the Cloud
Fast Data
Big Data
© Copyright 2017 Dell Inc.
Smart Data
Because the Future is Federated
29© Copyright 2017 Dell Inc.29
Where some common denominators exist
Meaningful data sets cross data zones
Cloud
SDDC
SDN
Application
Array
User space
Edge
In a multi-cloud world
30© Copyright 2017 Dell Inc.30
Computing nodes become virtual nodes in a virtual computing cluster at scaleConnecting clusters at the analytics layer
WWHWorld
Wide
Herd
YARN
Hadoop
framework
Virtual Computing Cluster
31
Select relevant
Datasources
(Sensor)
source
node
Datazone
(locked)Edge gateway
functionality
Open source
Edge software
IoT Fog
Metadata
datasources
repository
Data
source
Datasource
Datasource
Datasource Datasource
Datasource
Datasource
Analytic needs
Push analytic
microservices
result
Retrieve distibuted
analytic results
IoT
node
Provides
small amount
of intelligence
or analytics
at the edge to
provide early
(edge) detection
capability
Challenge of Edge Gateways is to address key
Interoperability where “south meets north”
in a distributed IoT architecture
analytic
engine
Industrial Clouds
Compliance
IoT Fog
Master Data Management
© Copyright 2017 Dell Inc.
Datasource
32© Copyright 2016 Dell Inc.32
Joint Data Management, GRC and Analytics Intelligence
metadata
IaaS
PaaS
SaaS
iPaaS
Link to the
architecture
intelligence
Worldwide
analytics
admin
Master
Data
Management
legal
Governance
Risk Mgt &
Compliance
33© Copyright 2016 Dell Inc.33
World wide, integrated, open sourced iPaaS solutions
SaaSSaaS
SaaSSaaS
iPaaS workbench
Boomi
admin
WWH
intelligence
Archer
legal
Meta
dataOrient
Decide
Observe
Act
OODA
cycle
Saas execution
Distributed data environments or zones
users
IaaS IaaS IaaS IaaS IaaS
34
Let the transformation begin . . .
35 Twitter: @hansdellemc blog: www.datacentered.nl