# IBM InterConnect 2017 --- Disclaimer --- * 4.5 days * 2,200 session * 25,000 people ---  ---  ---  --- ## Focussed on * Cloud * Watson --- ## Neglected * IoT * Blockchain * Security --- ## Presentation agenda * IBM vision * IBM cloud platform * Personal takeaways --- # Keynote Speech <br> ## Ginni Rometty IBM CEO ---  --- ## IBM Cloud * Enterprise-strong * Data-first * Cognitive to the core --- ## Enterprise-strong --- Scale (50 data centres in 19 countries) --- Largest commercial IoT platform --- Public, but designed for industry --- Data sovereignty: choice and consistency * On- or off-premise * Level of privacy * Range of services and applications --- Support for hybrid solutions * Data layer * Application layer --- Secure --- Comprehensive innovation roadmap --- ## Data-first --- Value-adding strategy * Democratisation (Facebook, Google) * IP (IBM) --- Governance * Fine-grained access control * Public * Private * Licenced * Locality * Isolation --- ## Cognitive to the Core --- Range of data types * Text * Image * Voice * IoT sensors --- Range of capabilities * Analytics * Machine learning * Cognitive computing --- Prepackaged, curated domain knowledge --- # IBM Strategic Overview --- * Platform: Watson Data Platform (WDP) * Ecosystem: Watson Data Platform Partners * Methodology: DataFirst Method --- ## 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 ---  --- ## 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 --- [Data Science Experience (DSx)](https://apsportal.ibm.com) --- ## Ecosystem Partnering with third-party vendors (mostly open source-based) --- ## DataFirst Method * Briefing & vision * Discovery workshop * Design & validate * Implement * Run & Maintain --- # Takeaways --- ### IBM Weaknesses * IBM is internally fragmented * Watson's current capability ranges from weak to mediocre (evaluated against both marketing claims and competitor capabilities) --- Cloud is big --- API economy is big --- Deep learning is big --- DevOps is big --- Container technology is big --- Local industry lags by several years --- New generation of core analytics technology is exclusively open source --- IBM fully embraces and actively supports and contributes to open source --- IBM explicitly supports a mix-and-match approach to using cloud services --- IBM's strength is in integration and interoperability --- * IBM provides tools * Business partners * Build solutions * Market * Provide support --- Cloud migration is a process rather than an event --- IBM advocates and technologically supports hybrid architectures (on-premises cloud) --- Hybrid cloud architecture is complex and requires significant and varied skills --- Many, especially smaller, businesses are confused, uncertain, and apprehensive about cloud transition --- Solutions *have* to be designed around client needs --- Biggest cloud issues for clients * Security * Architecture * Migration strategy --- Cloud and cognitive strategy details are very sensitive to details regarding * Time frames * Costing --- # Cloud Strategy <br> ## Liz Herbert from Forrester ---  ---  ---  ---  ---  ---  --- fin --- ###### tags: `miia` `cape town`