IBM InterConnect 2017

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Disclaimer

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• 4.5 days
• 2,200 session
• 25,000 people

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Focussed on

• Cloud
• Watson

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Neglected

• IoT
• Blockchain
• Security

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Presentation agenda

• IBM vision
• IBM cloud platform
• Personal takeaways

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Keynote Speech

Ginni Rometty

IBM CEO

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IBM Cloud

• Enterprise-strong
• Data-first
• Cognitive to the core

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Enterprise-strong

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Scale (50 data centres in 19 countries)

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Largest commercial IoT platform

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Public, but designed for industry

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Data sovereignty: choice and consistency

• On- or off-premise
• Level of privacy
• Range of services and applications

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Support for hybrid solutions

• Data layer
• Application layer

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Secure

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Comprehensive innovation roadmap

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Data-first

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Value-adding strategy

• Democratisation (Facebook, Google)
• IP (IBM)

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Governance

• Fine-grained access control
  • Public
  • Private
  • Licenced
• Locality
• Isolation

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Cognitive to the Core

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Range of data types

• Text
• Image
• Voice
• IoT sensors

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Range of capabilities

• Analytics
• Machine learning
• Cognitive computing

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Prepackaged, curated domain knowledge

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IBM Strategic Overview

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• Platform: Watson Data Platform (WDP)
• Ecosystem: Watson Data Platform Partners
• Methodology: DataFirst Method

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Watson Data Platform "Experiences"

• Data Connect - data engineers
• Watson Analytics - business analysts
• Data Science Experience (DSx) - data scientists
• Bluemix - app developers

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DSx Value Proposition

• System administration
• Best practices and staying current
• Collaboration
• Sharing (internally and wider community)
• Documentation
• Governance
• Granular access control (management and security)
• Auditing
• Model deployment and integration
• Scaling

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Data Science Experience (DSx)

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Ecosystem

Partnering with third-party vendors (mostly open source-based)

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DataFirst Method

• Briefing & vision
• Discovery workshop
• Design & validate
• Implement
• Run & Maintain

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Takeaways

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IBM Weaknesses

• IBM is internally fragmented
• Watson's current capability ranges from weak to mediocre (evaluated against both marketing claims and competitor capabilities)

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Cloud is big

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API economy is big

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Deep learning is big

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DevOps is big

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Container technology is big

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Local industry lags by several years

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New generation of core analytics technology is exclusively open source

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IBM fully embraces and actively supports and contributes to open source

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IBM explicitly supports a mix-and-match approach to using cloud services

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IBM's strength is in integration and interoperability

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• IBM provides tools
• Business partners
  • Build solutions
  • Market
  • Provide support

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Cloud migration is a process rather than an event

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IBM advocates and technologically supports hybrid architectures (on-premises cloud)

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Hybrid cloud architecture is complex and requires significant and varied skills

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Many, especially smaller, businesses are confused, uncertain, and apprehensive about cloud transition

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Solutions have to be designed around client needs

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Biggest cloud issues for clients

• Security
• Architecture
• Migration strategy

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Cloud and cognitive strategy details are very sensitive to details regarding

• Time frames
• Costing

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Cloud Strategy

Liz Herbert

from Forrester

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fin

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tags: miia cape town