Dell hans timmerman v1.1

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Transcript of Dell hans timmerman v1.1

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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.

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A few words about Dell EMC

Hans Timmerman

CTO Dell EMC The Netherlands

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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

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A data driven organisation . . .

in a data driven world . . .

© Copyright 2017 Dell Inc.

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FEEDING 9 BILLION PEOPLEBY 2050

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THE PRECISION FARMING REVOLUTION

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THE NEW OPPORTUNITY…

Product DATA About

The Product

INTENT

CONTEXT

REAL-TIME

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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

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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

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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)

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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

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Growth acceleration of the digital universe

The essence of Data Gravity

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Data and applications are attracted to each other . . .

An application eats data

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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

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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 . .

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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.

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But when data and app shrink. . . (3)

ApplicationData

Typical 4th platform behaviour

Fast streaming

dataIntelligent

micro services

movable data

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movable services

The Internet of Things

Application

Application

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Dawn of a new era

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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

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The internet of things

Edge intelligence

Fog Computing Mist Computing

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7 billionconnected people

44 zettabytesof data

30 billionconnected devices

Scale magnitudes modernized

Software driven

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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

Google

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

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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)

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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

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Now a new class of problems emerge . . .

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To one lake, or to multi-lake . . .

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The perfect datai-mobility storm

IoT effect

Migration

to the edge

Regulatory

compliance

Bandwidth

contraints

Legacy

data

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Technologies enabling distributed architectures

Machine Learning at the Edge

Deep Learning in the Cloud

Fast Data

Big Data

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Smart Data

Because the Future is Federated

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Where some common denominators exist

Meaningful data sets cross data zones

Cloud

SDDC

SDN

Application

Array

User space

Edge

In a multi-cloud world

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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

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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

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Datasource

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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

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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

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Let the transformation begin . . .

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35 Twitter: @hansdellemc blog: www.datacentered.nl