Dell hans timmerman v1.1

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  2. 2. 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. 3. 3 Copyright 2016 Dell Inc.3 A few words about Dell EMC Hans Timmerman CTO Dell EMC The Netherlands
  4. 4. 4 Strategically Aligned Businesses Dell Technologies Dell Inc. Client Solutions Group Global ServicesInfrastructure Solutions Group Dell Technologies - Worlds largest privately controlled Tech Company 74 B$ revenue 140.000 team members - 20.000+ patents - $4.5 billion on R&D/year
  5. 5. A data driven organisation . . . in a data driven world . . . Copyright 2017 Dell Inc.
  10. 10. INFRA As a Service Realtime RISK management 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 REALTIME Organization 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. 11. 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. 12. 12 Copyright 2017 Dell Inc.12 Changing value of data over time Value Time us 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
  13. 13. 13 13 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
  14. 14. 14 14 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.
  15. 15. 15 15 But when data masses differ . . . (1) Data Typical 2nd platform behaviour Large Applications billion lines of code Small data sets Data Data Data Data Data Data Data Application Application Centric Architectures STRUCTURED Non movable application Application is critical about the data to be presented . .
  16. 16. 16 But when data masses differ . . . (2) Application App App App App App App App Data Typical 3rd platform behaviour Big Datalakes billion bytes Small applications micro services Data Centric Architectures Non movable data Copyright 2017 Dell Inc.
  17. 17. 17 But when data and app shrink. . . (3) ApplicationData Typical 4th platform behaviour Fast streaming data Intelligent micro services movable data Copyright 2017 Dell Inc. movable services The Internet of Things Application Application
  18. 18. 18 Dawn of a new era Copyright 2017 Dell Inc.18
  19. 19. 19 Copyright 2017 Dell Inc.19 The cycle of the cloud Central 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
  20. 20. Copyright 2017 Dell Inc.20 The internet of things Edge intelligence Fog Computing Mist Computing
  21. 21. 21 Copyright 2017 Dell Inc.21 7 billion connected people 44 zettabytes of data 30 billion connected devices Scale magnitudes modernized Software driven
  22. 22. 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 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 Turing,Tesla,Morse 2014 Industrial Internet Consortium 2017 8.4 Billion Connected Things in use worldwide (world population: 7.5 Billion) Gartner EdgeX Foundry vendor-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
  23. 23. 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 gesoleerde 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. 24. 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. 25. 25 Now a new class of problems emerge . . .
  26. 26. 26 To one lake, or to multi-lake . . .
  27. 27. The perfect data i-mobility storm IoT effect Migration to the edge Regulatory compliance Bandwidth contraints Legacy data
  28. 28. 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. 29. 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. 30. 30 Copyright 2017 Dell Inc.30 Computing nodes become virtual nodes in a virtual computing cluster at scale Connecting clusters at the analytics layer WWH World Wide Herd YARN Hadoop framework Virtual Computing Cluster
  31. 31. 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. 32. 32 Copyright 2016 Dell Inc.32 Joint Data Management, GRC and Analytics Intelligence metadata IaaS PaaS SaaS iPaaS Link to the architecture intelli gence Worldwide analytics admin Master Data Management legal Governance Risk Mgt & Compliance
  33. 33. 33 Copyright 2016 Dell Inc.33 World wide, integrated, open sourced iPaaS solutions SaaS SaaS SaaS SaaS iPaaS workbench Boomi admin WWH intelligence Archer legal Meta data Orient Decide Observe Act OODA cycle Saas execution Distributed data environments or zones users IaaS IaaS IaaS IaaS IaaS
  34. 34. 34 Let the transformation begin . . .
  35. 35. 35 Twitter: @hansdellemc blog: