# 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

<br>

## 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)](https://apsportal.ibm.com) - 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)](https://apsportal.ibm.com)

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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

<br>

## Liz Herbert

from Forrester

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fin

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###### tags: `miia` `cape town`