EIM Intro - Information Architectures

8/9/2019 EIM Intro - Information Architectures

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RFCorsello

Research

Foundation

Enterprise Information ManagemInformation Architectures


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Introduction

Information architecture is the set of practices and processes us Define the appropriate data models

Define the mechanisms for persisting and representing data

Structure data for the most effective use and reuse throughout theinformation lifecycle

Information architecture spans technology and the physical wo Not all things are in computers

Not all things outside of the computer can be omitted

Mechanisms and methods for resolving paper and computers


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ConcQuick Voc


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Terms

Enterprise - the collection of organizations within a given business domain that operate

Corresponds to business specific groups within multiple organizations that share common inform

It is about how information is structured and managed to facilitate the sharing of data between oand divisions within an organization

Repository - data is stored in repositories

May be physically implemented as a database (such as Oracle or Sql Server)

May be any persistent mechanism (such as files)

Modern relational database management systems (RDBMSes) are the most commonly used pers

mechanism

Application a piece of software that runs on a computer

May or may not have a user interface (UI)

An RDBMS is an application that does not have a user interface, however there are applications (Toad) that provide a user interface to an RDBMS.


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Information Perspectives

An enterprise information architecture will consist of multiple

repositories

Each contains a subset of the data for that enterprise

Data must be structured based upon some consistent means to facdiscovery and use

Two primary considerations for evaluating the best strategies fo

enterprise data:

Management strategy

Implementation strategy


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Information Models

A model is a logical representation of a phenomenon in the rea

A data model is a model for a data entity that is the representat

real world phenomenon. A model comes in two parts:

Conceptual model

Instance model (realization)


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Management Strategies

Data management is based upon some strategy for organizing the dbeing managed

The selection of an appropriate strategy is not trivial and is based uuse of the data once persisted

If there are many uses for a data element that spans business practicesbe most efficient for human productivity to adopt multiple strategies

There are three primary strategies:

Project oriented

Topic oriented

Entity oriented


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Project Oriented

All data is grouped, collected and managed by the project(s) it i

associated with

Each organizational project (such as a specific otolith study) gets a

repository or partition (directory in a file system sense)

Data generated and used within that project is stored within the p

repository based upon data models used for that project

Projects may adopt centralized models, or define project specific m

for any given data domain


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Project Oriented Scorecard

Benefits

Good for data collection and general field activityprojects

May have minimal structure and little need for datamanipulation

People are responsible for maintaining the flow ofinformation within their project and must push dataout to make it available to others

People can be highly efficient as they have minimalconstraints to slow down human efforts

Only data that is used by a project needs to betransformed for use

Costs

Data can become unusable or undiscovprojects

There is no central source for a given ty

Once data is acquired from another proprocessing may be required to make it

Data may be in multiple formats whichunusable over time

Data sets will have to be transformed tfor every project reusing the data

Modeling must be performed for each any gaps from existing models

Overall Score

Poor

Limited use in very specialize domains

Good for client deliverable (turn-key) w


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Topic Oriented

Divides repositories by business topic (domain) area

Each topic has a unified model that is used within that topic are

If multiple topics use a common data entity (real world thing), ea

area may have a distinct model for that entity

The models may be entirely different and incompatible


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Topic Oriented Scorecard

Benefits

Good for businesses with very few domains that do notinteract with external organizations

All projects can interchange data freely as they are basedupon common models with shared repositories by topic

All data for an enterprise within a topic is in a usable format

Each topic may create models that accepted tools can usedirectly

Integration data sets may be created to ensure compatibilitybetween domains by sharing models at overlap points

Costs

Translation of data across topics may be cos

Integration of data across topics may be impcorrespondence between the domains is nobeforehand

Each topic may be incompatible for anothetools

Data integration costs may be high, and ten

Modeling must focus on an entire business on commonly used aspects of the topic

Overall Score

Moderately poor

Allows for solid models of specific topics ac

Commonality between domains are commo

Good for highly specialized organizations an


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Entity Oriented

Most beneficial and most complex form of management

All real-world entities used within the enterprise must be ident

and modeled separately

Each entity becomes an atomic data repository that can be shared

The primary goal is to adequately identify the entities and model t

the greatest level of detail required

Determining which perspectives of the real-world entities should b

modeled is complex


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Entity Oriented Scorecard

Benefits Data sharing is free due to the unified

entity models throughout the enterprise

Across organizational boundaries onlyagreement that is necessary is for the actualentities those organizations share

Applications may be built to effectivelyconsume and reuse data across projects andtopics based upon the entity model

Interactions between entity models may bemodeled separately

Modeling may be performed in phasesbased upon use

Software tools can be reused as componentsand integrated in different ways

Costs

Modeling takes more time and e

Software tools will nearly alway

Overall Score

Good

Overall, cost and time are the odrawbacks

If entity model becomes standavendors may likewise build toolsmodels


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Hybrid Approaches

In many cases, it is advantageous to combine: Project-oriented strategy for the data capture portion of the lifecycle

Entity-based strategy for long-term persistence in enterprise repositori

This enables the implementation of the project strategy to facilitatecollection efforts while the entity modeling and implementation effunderway for the enterprise repositories

This hybrid strategy yields long-term flexibility for field staff performdata collection as well

Still has longer timelines and greater short-term cost

Cost savings in the long-term is based upon many factors such as data s


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Implementation Strate


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Software Implementations

There are several forms of software application architectures in Thick Client

Client-Server

Three-Tier

N-Tier

Cloud

Each implementation strategy provides certain pros and cons

N-Tier and cloud seem to hold the greatest promise moving forwar


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Thick Client

The most straightforward implementation strategy for a softwa

solution is the client application or thick client

Data and processing are local to the software and all operations

on the user computer

Common example of this architecture is the traditional word-

processing application such as Microsoft Word or Corel WordPe


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Client-Server

Moving to multi-user concurrent usage capabilities starts with the addition o

server-based component to the software solution

The most basic form is the client-server strategy

There are exactly two deployment components to the overall application, onon the user computer (the client) and the other runs on a remote server

A common example of this is the database enabled application

The most prevalent form of the client-server architecture is a basic web site

The client-server architecture is simple, efficient and

Client-server architectures do not scale well for intense processing or large ubases


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Three-Tier

Three-tier architecture consists of:

Client application

Business processing server

Data storage tier

The three-tier architecture is a common implementation strateg

basic business web applications


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N-Tier

An evolution of the three-tierarchitecture is the N-tier,

where any N, or number of

tiers, exist to support the

application

Modern web based

applications frequently use an

N-tier approach, especially

where service oriented

architectures (SOA) are applied


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Cloud and Distributed

Any form of application that is run in part on multiple machines isdistributed

Formally, a distributed system partitions the work across multiple machjust separating user interface from logic

N-Tier applications are distributed applications

Cloud computing is:

When a distributed application is based upon placing portions of thecomputation in separate locations requiring the Internet for communic

Often, this separates storage from computing over the Internet

E.g. using Flikr to store images, Amazon S3 for disk storage and Microsoft Azcomputation all in one web application


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Capability Partitio


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Partitioning

Trade-offs are made to ensure:

Performance

Scalability

Maintainability

To provide any capability, there is a minimum cost and timeline

An effective solution will always be in excess of these minimums

Strategies for reuse, integration and partitioning are effective at minimizing realized costs by distributing the costs

Partitioning allows for resource sharing in any of several areas:

Conceptual reuse ideas, designs and algorithms are applied to multiple projects

Source reuse software source code is reused on multiple projects

Library reusecompiled libraries of code are reused as-is on multiple projects

Hardware reuse multiple applications are hosted on a single physical server

Service reuse software service(s) are reused by multiple applications (such as SOA)

Data reuse a single authoritative data repository is reused by multiple applications


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Partitioning Targets

Trade-offs to provide capabilities at reduced costs generally involve

partitioning strategies Each of the primary computing areas for a software application ma

subject to partitioning

These primary computing areas are:

Repositories of data the full corpus of data may be partitioned into doentity specific repository models

Processing engines or capabilities computational portions may be sepinto reusable analytical components for reuse

User presentation (GUIs) may be partitioned away from an application there is no business logic associated with the display of information


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Repositories

Software is designed to process data in some form

The repository is a conceptual store from which software will access and pro

There are several strategies for partitioning repositories across an enterprise

Enterprise centric the entire enterprise centralizes all data into a single marepository

Application centric each application has a dedicated repository

Domain centric each business domain has a dedicated repository that allapplications using that domain data must connect to

Entity centric each entity is modeled and a repository exists for that entity

All applications using an entity are connected to that entity repository


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RepositoStore t


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Enterprise Centric

The approach of centralizing all data into a master integrated

repository is only effective for small repositories with limited gr

The definition of small in this context is fluid as a function of c

providing a hardware infrastructure to support such a repositor

In general, this is not a recommended approach in most circumsta


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Application Centric

Each application gets a dedicated repository

If multiple applications require access to thesame data, that data is maintained in bothrepositories

This solution provides the greatest level ofperformance for a single application, but comesat the additional cost of data duplication andissues of consistency for rapidly changing data

For small organizations with static data sets, theapplication centric approach may be quite effective

In many cases, the application centric approachwill be sub-optimal in all areas due to the effortinvolved in establishing the data synchronizationmechanisms and the cost of data duplication

This is the most natural form of partitiothe isolation of repositories for each ap

In this form, developers of a solutiofocus on the local problem alone

May lead to lower development coapplication at the cost of poorer fitcapability required


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Domain Centric

Domain centric partitioning ensures each domain within the enterprise has a

master repository Tends to have similar pros and cons to the application centric model

Application developers are required to have a reasonable understanding of business domains affected by the application

Each application may be required to communicate with more than one repo

Data integration across repositories may result in the need for additional joelements to be added to repositories

The key limitation is the potential for data duplication and the reconciliationsameness of entities between domains

If domains each model person for their repository, the person models maydifferent and thusly incompatible


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Entity Centric

Entity centric repositories are the most data efficient

Also most design costly

Each data entity has an isolated repository with identified linkages between repo

Example:

A single people repository of all human beings known throughout the enterprise

Contains people information for employees, customers, suppliers, contractors, etc

People repository only contains the information that describes the people notion of thindividuals

The modeling of entities drives the repository boundaries, and the integration of across repositories happens within one of the repositories participating in the int


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Processing and DisComputational Logic And User In


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Processing Engines

A large part of computationally intensive applications involves generic proce

functions

Separating processing capabilities into reusable structures can yield great coin multiple areas including long-term supportability

The primary cost associated with these reusable structures is designing themfor reuse

The isolation of these computational units can take on different forms:

Reusable libraries such as a statistical analysis library

Reusable frameworks provide a collection of common capabilities that may across applications

Reusable services such as data processing web services are increasing in avaand form the basis of most SOA implementations


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Hybrid Processing

In developing software for an enterprise, all three partitioning

strategies may be used together for maximal effectiveness and

operational longevity

Component based development extends from software into dat

partitioning data effects software and vice versa


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User Presentations

The user interface of an application is responsible for the presentation of data and cont

application user Often called the presentation layer and ideally contains no functional logic for the application

When properly designed and partitioned, the GUI is completely independent of the functional poapplication

The GUI itself can be partitioned into components that can be reused across applications

There are two different aspects of the GUI that can be partitioned for an application:

Partitioning of the GUI from the capability logic

Partitioning of the GUI itself into GUI components

The most significant area of reuse comes from the first area of separating the GUI from business logic

This should be the default development pattern for application development

This is often not followed in practice to reduce development and planning time


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Conclusions

Architecting information solutions for an organization is a complex set of practice

trade-offs to maximize capabilities while minimizing cost Given that information solutions take a great deal of time and care to construct, proper p

required well in advance of need to ensure solutions are available by the time the need awithout wasted efforts

Various strategies exist for planning information repositories, software implemenand user facing applications

Planning for reuse of repositories and software back-end components and services is of gimportance

Stakeholders involved with information strategies need to understand the difference betrepositories containing data, back-end software and the user interfaces that present data

The separation of these concepts in the minds of those involved in planning can yield grelong-term cost savings and capabilities realized


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Quest

Documents

EIM Intro - Information Architectures