Architecture de l'information glossaire : bigdata, nosql, datawarehouse, cloud, mdm

Un super glossaire reprenant les thèmes de la gestion de l'information moderne : Data, Information, and Knowledge. Data Formats : Structured, Unstructured, Semi-Structured. Data Domains : Operational, Content,System, Authoritative (Master and Reference Data), Analytical, Metadata Data Classification. Data Persistance : Relational Database, Disk File System, Multi-Dimensional, In-Memory Database,In-Memory Data Grid, Distributed File Systems, NoSQL (Key-Value,Columnar,Document,Graph) Data Partitioning ; Relational and Distributed data partitioning Data Streams / Events Data Modeling : Relationship Modeling (Conceptual,Logical,Physical) , Dimensional Modeling and NoSQL Modeling Data Processing : OLTP, OLAP, Big Data Processing (Volume, Velocity, Variety, Value) 1Information Stores : ODS, Data Mart, Data Warehouse 1Governance : Data Quality, Information Lifecycle Management, Governance for Big Data 1Business Intelligence & Business Analytics. 1Information Architecture : User Experience (UX) and Enterprise Architecture Common Information Management Standards Data Modeling : UML,IDEF1X, Crow’s Feet Data Representation & Interoperability : XML, XML Schema, RDF, UDEF, JPA, JSON Data Query & Transformation : SQL, SPARQL, CQL, MDX, XMLA, XQuery, XLST Regulatory : Sarbanes-Oxley (SOX), Third Basel Accord (Basel III) Connectivity and Access : ODBC, JDBC, CMIS, JSR-170, Repository Connectivity Architecture Principles Treat All Data as an Asset Multiple Data Formats. Standards Based Information Management. Separation of Concerns Volume and Velocity Information Accessibility. Unified View of Information. Information Abstraction. Consistent and Complete Information 1Quality Data. 1Retention of Data 1Flexible and Agile. Conceptual View Data Processing : Batch, In-Database, Real-Time, In-Memory, Continuous / Stream Processing Data Movement : Bulk Data Movement, ETL, E-LT, Logical Data Movement,Parallel Copying, Incremental Data Movement (Change Data Capture (CDC), Data Stream Capture), Data Repplication Information Governance : Data Quality Management (Profiling and Validation, Cleansing, Standardization, Enrichment, Match and Merge, Exception Management, Data Remediation, ILM Historical Data Management : Atomix / Process Neutral, Consolidation, Normalization, Versioning Analytical Data Management : Aggregation & Navigation (Multi-Dimensional Representation, Aggregation and Summaries, Exploratory Processing (Unification, Enrichment, Simulation) Authoritative Data Management : Multi-Entity Management, Common Authoritative Data Model, Relationship Management, Entity Consolidation, Entity Lifecycle Management,Entity Publication Enterprise Content Management : Repository, Document, Digital asset, Web Content, Imaging, process and Information Rights Mamangement Metadata Management : Introspection, Impact Analysis, Data Lineage Data Virtualization : Federation, Caching, Mediation, Routing, Policy Enforcement,Search ,Connectivity 1Information Access 1Information Services : Data Services, Analytical Query Services, Content and Spatial Services 1Provisioning Services : Data Ingestion, Analytical, Data Quality and Repository Services 1Information Modeling. Logical View Information Consumption : Virtualization, Information as a Service Information Acquistion : Ingestion with Latency,Topologies, Mechanism (Data Integration, Parallel Batch Processing ,Change Data Capture, Event Processing, Messaging Bus/Hub), Ingestion Patterns (Point to Point, Hub and Spoke); Replication and Synchronization Information Organization: Areas of Responsibility (Staging Area,Foundation Area,Access and Performance Area, Content Area, Discovery Area), Big Data Processing, Enterprise Master Data Management (Operational MDM, Analytical MDM, Multi-Entity, MDM Patterns with Virtual Hub, Centralized Hub, Consolidated Hub or Hybrid Hub) Data Warehouse : Active Data Warehouse, Areas of Responsibility (Staging Area,Foundation Area,Access and Performance Area, Content Area, Authoritative Area,Content Area ), Patterns ( Conforming Data Marts, CentralizedHub and Spoke, Federated and Distributed) Oracle Product Mapping View

Matière

Business Intelligence

Niveau

Confirmé

Langue

Anglais

Auteur(s)

Stephen G. Bennett, Dave Chappelle, Oracle Corporation

Origine

Oracle Reference Architecture (E26368-03)

Date de parution

juillet 2013

Format

PDF · 208 pages

Taille

6,5 Mo (6 778 162 octets)

Publié sur le site

4 avril 2014