Enterprise Architecture
10.3 Enterprise Architecture
Enterprise architecture is a strategic framework that captures the current state of the enterprise business and supporting IT, and outlines an evolutionary path towards the future state of the business and IT (Delic, 2002b ). It is a very hard challenge to provide synchronised development of business and IT in dynamic and unpre- dictable market conditions. Thus, having a sound enterprise architecture that charts evolutionary change over 3–5 years is an important, competitive advantage. In sim- plistic terms, enterprise architecture is a model depicting the evolution of business, infrastructure, applications and data landscapes over 3–5 years. Each artefact of the enterprise architecture has a very high monetary value, a strong proprietary nature, and a vital importance for the future of the enterprise.
In a simplistic fashion, these artefacts can be represented in an hierarchical man- ner, implying the type of models appropriate for each layer, characteristic entities and key metrics (Fig. 10.3 ). Enterprise architecture can be viewed as a global strate- gic plan which will synchronise business evolution with IT development and ensure that future needs are properly addressed. As such, enterprise architecture represents the most valuable strategic planning item for enterprise executives and management: business can plan underlying technology changes after observing forthcoming tech- nology shifts (Zachman, 1999 ). Such technology changes will critically improve or cripple business performance, and mature businesses should keep those plans private, current and sound.
The expanded landscape shown in Fig. 10.4 indicates some characteristic opera- tional figures for the very large, global business enterprise, and illustrates the scope, scale and complexity of operations (Delic, 2002a ). It is intuitively clear that such
a complex environment contains several points of inefficiency and structural weak- ness which could be best dealt with via deployment of KM techniques. A more developed enterprise landscape (e.g. Delic, Greene, & Kirsch, 2010) will also con- tain data points, indicate the dynamics and spread of data flows, and show the key technological, business and market indicators.
10 Enterprise Knowledge Clouds 243
Key Performance
Key Enterprise Artifacts
Indicators
Characteristics
Enterprise Entities, Objects
Zachman
Revenue, Framework Profit, Market
Share, Size
Policies
Scope
Customers, Clients,
Impact
Accounts, Analytic
Business
ITSM
Speed, Support Cost/Item, Effort
Tools
Processes
Cases, Transactions,
CIM/DTMF RM-ODB
Cost, Value,
Data
Models
Volume, Speed
Events, Notifications,
Information Warnings, Alarms
Accuracy
Quality
Stratified Enterprise Architecture
Delic: Copyright 01/03.
Fig. 10.3 Simplified enterprise/business/IT artefacts
Alarm Suppression
ENTERPRISE BUSINESS
Event Correlation Heavy Coding &
Users Enterprise
Help Desk Services
T echnicians Engineers
First Line
Enterprise Network Reporting
Network Servers
Web Server
Access Devices
Database Server
Security
Application
Operational Center
Infrastructure
Server
ENTERPRISE IT/IS FABRICS ENTERPRISE IT/IS DEPARTMENT
Fig. 10.4 Simplified enterprise/business/IT architecture landscape
244 K.A. Delic and J.A. Riley As an example, for an enterprise business to efficiently handle in the order of
100 million calls per year, it should capture and deploy knowledge about callers, encountered problems and solution procedures. Similarly, to configure, manage and maintain in the order of 40,000 network devices, an enterprise business needs deep and reliable knowledge about network topology, fault behaviours and overall traf- fic flows. For each domain, knowledge will have different capture paradigms and technology, and will have a different impact on internal IT performances and cost.
Parts
» Cloud Computing Model Application Methodology
» Cloud Computing in Development/Test
» Cloud-Based High Performance Computing Clusters
» Case Study: Cloud as Infrastructure for an Internet Data Center (IDC)
» Case Study – Cloud Computing for Software Parks
» Case Study – an Enterprise with Multiple Data Centers
» Service-Management Integration
» Cloud Deployment Models and the Network
» Latency, Bandwidth, and Scale – The Span
» Security, Resiliency, and Service Management – The Superstructure
» Network Architecture for Hybrid Cloud Deployments
» Characteristics of Data-Intensive Computing Systems
» Related Work on DS Scheduling
» Scheduling Issues Inside Service Oriented Environments
» Scheduling Through Negotiation
» Prototype Implementation Details
» Basics of Grid and Cloud Computing
» Service Orientation and Web Services
» Scheduling, Metascheduling, and Resource Provisioning
» Interoperability in Grids and Clouds
» Security and User Management
» Modeling and Simulation of Clouds and Grids
» Enterprise Knowledge Cloud Technologies
» NC State University Cloud Computing Implementation
» Computational/Data Node Network
» Integrating High-Performance Computing into the VCL
» Large Scale Workflow Applications
» Overview of SwinDeW-G Environment
» SwinDeW-C System Architecture
» History on Enterprise IT Services
» Remote Sensing Geo-Reprojection
» Singular Value Decomposition
» System Model for Auction in CACM
» Multi-objective Genetic Algorithm
» Anagram Based GrADS Data Distribution Service
» Hyrax Based Five Dimension Distribution Data Service
» Design and Implementation of an Instrument Service for NetCDF Data Acquisition
» A Weather Forecast Quality Evaluation Scenario
» Implementation of the Grid Application
» Overview of Amazon EC2 Setup
» DGEMM Single Node Evaluation
» Data Clouds: Emerging Technologies
» Cloud Architecture as Foundation of Cloud-Based Scientific Applications
» Emergence of Cloud-Based Scientific Computational
» Setup and Experiment on Tiny Cloud Infrastructure
» On Economical Use of the Enterprise Cloud
» Toward Integration Of Private and Public Enterprise Cloud Environment
» Brief Discussion of Medical Standards
» Objective 1: A Service Oriented Architecture for Interfacing Medical Messages
» Objective 4: A Globally Distributed Dynamically Scalable Cloud Based Application Architecture
» Distributing Multidimensional Environmental Data
» Enabling the NetCDF Java Interface to S3
» The NetCDF Service Architecture
» NetCDF Service Deployment Scenarios
» Evaluation of S3- and EBS-Enabled NetCDF Java Interfaces
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