Data Gravity Data Gravity Dell EMC Hans Timmerman

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Data Gravity

Data Gravity

Data Gravity Dell EMC Hans Timmerman

Data Gravity Dell EMC Hans Timmerman

Agenda • • Wie is Dell EMC? Wat is data gravity? Wat is het

Agenda • • Wie is Dell EMC? Wat is data gravity? Wat is het interessante van dit begrip? Wat betekent het voor data architecturen?

Dell EMC is ontstaan op 7 september 2016 Op die dag werd EMC door

Dell EMC is ontstaan op 7 september 2016 Op die dag werd EMC door Michael Dell en investors voor 67 B$ van de beurs gehaald.

Dell Technologies Strategically Aligned Businesses Dell Inc. Client Solutions Group Infrastructure Solutions Group Global

Dell Technologies Strategically Aligned Businesses Dell Inc. Client Solutions Group Infrastructure Solutions Group Global Services 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

The origin of Data Gravity Massa’s trekken elkaar aan. . . Dat geldt ook

The origin of Data Gravity Massa’s trekken elkaar aan. . . Dat geldt ook voor data. . .

The origin of Data and applications Gravity and services Application th wi d n

The origin of Data and applications Gravity and services Application th wi d n Ba n o y& ati nc r e t ele La cc A Mass of Data Es ca pe Service Ve loc ity

Maximum speed when all data is together Data, applications, services etc. Typical 1 st

Maximum speed when all data is together Data, applications, services etc. Typical 1 st platform behaviour Hardware Centric Architectures Application Data Service Terminal Velocity

Same gravity with equal data masses Separated data and applications are attracted to each

Same gravity with equal data masses Separated data and applications are attracted to each other. . . Data Application

But when data masses differ. . . (1) Data Typical 2 nd platform behaviour

But when data masses differ. . . (1) Data Typical 2 nd platform behaviour Application Centric Data Architectures Data Application Data Small data sets Large Applications billion lines of code

But when data masses differ. . . (2) Typical 3 rd platform behaviour App

But when data masses differ. . . (2) Typical 3 rd platform behaviour App Data. Application Centric Architectures App Big Datalakes billion bytes Small applications micro services App

The Origin of Data Gravity What is Data? And can lead to Which again

The Origin of Data Gravity What is Data? And can lead to Which again Itcreates becomes We needaction to add knowledge as best. . knowledge context! practise Degrees Fahrenheit Today 32 Is Temperature, Cold for people, Water Because of this, I will wear a coat freezes, Creates Ice, This. just meaningless data Data Information Knowledge And is decribed as new information and written down as new data Action

The Origin of Data Gravity Data is the foundation for decision cycles Plan Data

The Origin of Data Gravity Data is the foundation for decision cycles Plan Data Observe SHRINK Do Application Orient Check Interface Decide Action Act Knowledge Action REDUCE TIME Data Information

The Origin of Data Gravity A wide variety of data and workloads Systems of

The Origin of Data Gravity A wide variety of data and workloads Systems of Record Systems of Engagement Traditional Cloud Native 2 nd Platform 3 rd Platform One Infrastructure

From Computing Centre to Data Centre Computing Centre Data Centre Compute and network are

From Computing Centre to Data Centre Computing Centre Data Centre Compute and network are verbs and utilities. They compute or transport data based upon applications. Data and application are nouns and assets. They have intrinsic value, IP, privacy, intelligence and kept in vaults. Thus: cloud computing is totally different from cloud data ! Utilities should be large and cheap; assets should be safe and durable

A wide variety of data System Centric Back Office Systems of Record • •

A wide variety of data System Centric Back Office Systems of Record • • • IT driven, Robust Transactional oriented Application centric Safe & secure Structured data BIG DATA User Centric Intelligence Systems of Insight • • Data Governance Analytics Big Data Business Intelligence Front Office Systems of Engagement • • • Interaction oriented Contact & collaboration User experience Mobile Unstructured data SMART DATA SUPPORTED BY A HYBRID CLOUD PLATFORM (as a utility) Shared Data FAST DATA

It takes time and money to move data • The theorem of Nyquist and

It takes time and money to move data • The theorem of Nyquist and Shannon: The notion of maximum channel capacity. . . • The law of Moore: Processor and flash capacity still double every 18 months. . . • The law of Einstein: Speed of Light is constant. . . • Actual situation: Broadbandwidth is doubling each 5 year, but Creation of data and processor capacity grows faster than bandwidth. . .

Data Lakes will reside for ever. . . • Large data stores (PB+) cannot

Data Lakes will reside for ever. . . • Large data stores (PB+) cannot be moved easily • Large data stores and data lakes attracts (micro-) services • Distributed large data warehouses need distributed analytic tools • Distributed Hadoop solutions might bring next years relieve • Hybrid clouds demand well organized data management • Data Clouds might be a ‘Hotel California’, no check-out available.

Hans Timmerman, CTO Dell EMC The Netherlands • • • Bedrijfsnaam: Dell EMC Nederland

Hans Timmerman, CTO Dell EMC The Netherlands • • • Bedrijfsnaam: Dell EMC Nederland Adres: Edisonbaan 14 b Nieuwegein Telefoonnummer: 030 -630. 5000 E-mailadres: hans. timmerman@dell. com Blogs: www. datacentered. nl Twitter: @hansdellemc