Question

(quinta/a) Explain what is an Enterprise Architecture Stack with examples.PLEASE write your answer in your own words!thanks

Answer 1

An enterprise architecture framework (EA framework) defines how to create and use an enterprise architecture. An architecture framework provides principles and practices for creating and using the architecture description of a system. It structures architects' thinking by dividing the architecture description into domains, layers, or views, and offers models - typically matrices and diagrams - for documenting each view.

it has been normal to divide enterprises architecture into four architecture domains.

· Business architecture,

· Data architecture,

· Applications architecture,

· Technology architecture.

Enterprise architecture domains and subdomains

                                 

The application and technology domains (not to be confused with business domains) are characterized by domain capabilities and domain services. The capabilities are supported by the services. The application services are also referred to in service-oriented architecture (SOA). The technical services are typically supported by software products.

The data view starts with the data classes which can be decomposed into data subjects which can be further decomposed into data entities. The basic data model type which is most commonly used is called merda (master entity relationship diagrams assessment, see entity-relationship model). The Class, subject and entity forms a hierarchical view of data. Enterprises may have millions of instances of data entities.

The Enterprise Architecture Reference Traditional Model offers a clear distinction between the architecture domains (business, information/data, application/integration and technical/infrastructure). These domains can be further divided into Sub domain disciplines. An example of the EA domain and subdomains is in the image on the right.

Many enterprise architecture teams consist of Individuals with Skills aligned with the Enterprise Architecture Domains and sub-domain disciplines. Here are some examples: enterprise business architect, enterprise documentational architect, enterprise application architect, enterprise infrastructure architect, enterprise information architect, etc.

Enterprise architecture reference architecture with sub domains

Examples:

Here is a list of architecture patterns, and corresponding software design patterns and solution patterns.

Sub-domain area	Architecture pattern	Software design patterns	Solution patterns	Related patterns
Data integration/SOA	· ETL (data extraction transformation and loading)	· Change data capture · Near real-time ETL · Batch ETL · Data discovery	· Error handling · Job scheduling · Data validation · Slowly changing dimensions load	· EAI · Master data hub · Operational data store (ODS) · Data mart · Data warehouse
· MFT
· EAI/ESB	· Publish/subscribe · Request/reply · Message exchange patterns	· One-way · Synchronous request/response · Basic callback · Claim check	· SOA
Data architecture	· Transaction data stores (TDS/OLTP) · Master data store · Operational data store · Data mart · Data warehouse	· Custom applications databases · Packaged application databases		· ETL · EAI · SOA
Analytics and business intelligence	· Transactional reporting · Operational analytics · Business analytics · Predictive analytics · Prescriptive analytics · Streaming analytics · Data science and advanced analytics · NLP	· Transactional reporting data access · Operational reporting data access · Analytical reporting data access · Analytical dashboard data access · Operational dashboard data access · Data mining	· Real-time dashboards · In-memory analytics · Statistical analysis · Predictive analytics	· ETL · EAI · TDS · Operational data store · Data mart
Master data management	· Master data hub	· Master data replication · Master data services · Master data synchronization		· Change data capture · EAI · STD
Data modeling	· Dimensional data modeling · E-R data modeling	· Modeling standards · Naming conventions
Artificial intelligence	· Decision management · Speech recognition · Text analytics and NLP · Natural language generation · Classic machine learning · Deep learning · Robotic process automation · Image and video analysis