This is the material for Gartner Summit 2018 -Customer Experience- on Feb 20, 2018 as sponsor session from Microsoft in Tokyo Shinagawa.
This Session covers innovative customer experience in the future using Azure AI, Cognitive Services, and other Azure technologies.
JPC2016Area: デジタルトランスフォーメーションを支えるクラウド選定の新基準MPN Japan
Big Data、IoT、FinTech や AdTech など最近話題のデジタル トランスフォーメーションを支える IT 基盤としてクラウドの活用が本格化しています。本セッションでは、グローバル規模での事業展開を支えるクラウド基盤の選定基準と日本企業がクラウドを活用したデジタル トランスフォーメーションを展開するうえでのヒントを国内外の事例を交じえてご紹介します。
This is the material for Gartner Summit 2018 -Customer Experience- on Feb 20, 2018 as sponsor session from Microsoft in Tokyo Shinagawa.
This Session covers innovative customer experience in the future using Azure AI, Cognitive Services, and other Azure technologies.
JPC2016Area: デジタルトランスフォーメーションを支えるクラウド選定の新基準MPN Japan
Big Data、IoT、FinTech や AdTech など最近話題のデジタル トランスフォーメーションを支える IT 基盤としてクラウドの活用が本格化しています。本セッションでは、グローバル規模での事業展開を支えるクラウド基盤の選定基準と日本企業がクラウドを活用したデジタル トランスフォーメーションを展開するうえでのヒントを国内外の事例を交じえてご紹介します。
Why we should consider Open Hybrid Cloud.pdfMasahiko Umeno
I am talking about four key points, Application Architecture, Development method, Organizations and Cooperation, Operation and Maintenance, to consider in legacy modernization and what the end result should be.
We think you'll understand why you should consider Red Hat's "open hybrid cloud" approach. Please take a look.
Rhf2019 how totackle barriersofapplicationmodernization_ap16_enMasahiko Umeno
This is a translated presentation at Red Hat Forum Tokyo 2019.
Every company are facing some problem in Application Modernization, and all of them have same issue. I told about 3 things, Application Architecture, Granularity and Development method.
Here is also a message of what we have to do before containerize.
Red Hat Forum Tokyo 2019 にて講演したセッションの資料です。
レガシーなシステムを脱却してApplication Modernizationに取り組んでいるお客様は多数いらっしゃいますが、驚くほど同じような障壁をお持ちで、その解決策を見出だせずに前進できていないように思えます。本講演ではこれらの障壁にどう取り組むべきかを解説し、Red Hatの製品群とサービスでどうご支援できるかも含めて、推進のヒントとしていただければと思います。
Next generation business automation with the red hat decision manager and red...Masahiko Umeno
Red Hat offers the Decision Manager and Process Automation Manager to enable next generation business automation. The key pillars of their solution are application modernization, robotic process automation, IoT, AI, and business optimization. For successful application projects, companies should focus on the application architecture, organizing rules and processes, and using an iterative software development methodology. The Process Automation Manager supports business process management with capabilities like case management, while the Decision Manager is used for managing rules.
If you understand the rule engine, especially how works RETE algorithm, You may use this for Machine Learning. This slide used at Red Hat Forum Tokyo 2018 session.
To make a good work-life balance, you may be necessary optimization of task scheduler or something. Improvement of job quality may give us more happiness life.
1) The document discusses Japan's investments in artificial intelligence (AI) technologies through several government ministries and agencies. It provides details on amounts invested and goals for each ministry.
2) The document outlines different areas of AI like machine learning, deep learning, planning, and search. It explains techniques within machine learning like clustering and Bayesian methods.
3) The document discusses Red Hat products that can be used to support AI systems, including tools for data collection, analysis, learning, inference, and decision-making.
This document discusses application architecture and provides examples of how to properly structure applications using rules, processes, and data. The key points are:
1) Rules should represent business logic and processes should manage workflow and status. Data should not drive processes or contain logic.
2) Case studies demonstrate how to separate concerns - using a rule engine for calculations and decisions, a process engine for workflows, and a database for data storage.
3) Integrating systems through shared memory (e.g. JBoss Data Grid) and rules can enable high-performance big data processing and integration across different business units and systems.
6. Copyright 2022 Red Hat K.K.
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