Zoek in diagram
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NameNotesPackage
Additional Big Data PatternsAdditional Big Data Patterns not linked in a compound patternBig Data Patterns
Analytical Sandbox Big Data Patterns
Appliance BDP-DWH ABBIn the appliance integration of a big data platform with DWH functionality the appliance acts like a black box in which all functionality is integrated in a (proprietary) solution. This solution is configured for optimal performance of transformation and analysis. Characteristics
  • Appliance is developed, configured and often maintained by an external supplier
  • It is introduced as a fully integrated solution therefore existing implementations of the DWH have to migrate to this solution
  • Appliances are often introduced when a cloud solution is selected for the data platform
BD-DWH Integration ABB
Application enhancement Big Data Patterns
Batch Data Processing Big Data Patterns
Big Data BlueprintLayered or tiered architecture fortransformation of data from sources to utilisation. It includes three architectural columns that influence all layersBig Data Blueprint
Big Data Mechanisms in Big Data BlueprintPlot of the described mechanisms on the Big Data BlueprintBig Data Mechanisms
Big Data Mechanisms overviewTechnology mechanisms represent well-defined IT artifacts that are established within an IT industry. Big Data Mechanisms
Big Data Overview Architecture/Solution Building Blocks
Big Data Pipeline Big Data Patterns
Big Data Processing Environment Big Data Patterns
Big Data Transformation Big Data Patterns
Big Data Warehouse Big Data Patterns
Consumers overviewOverview of internal and external consumers of the standardized datasets.Hourglass ABB
Data analytics en -science Data analytics and -science
Data analytics en -science main categories Data analytics and -science
Data filtering and selection Data filtering and selection
Data filtering and selection including components Data filtering and selection
Data processing Data processing
Data qualitiesThis is an overview of the DaMa data qualities. It can be extended with the implications for a specific projectData qualities
Data storage Data storage
Data storage NewSql implementations Data storage
Data storage NoSQL implementations Data storage
Data visualisations for business users Data visualisations
Definition Big Data Types Data types
Detailview interfacesSpecialized model of the various interfaces available for the consumers of the standardized datasets.Hourglass ABB
File transformation overviewOverview of the transformation from file based data to a data targetFile transformation ABB
General view hourglassThe hourglass model is a specific model for the transformation of data sources to a standardized model in a target datastore. It is the simplified implementation of a layered Big Data architecture. The hourglass model can be used to medel specific implementations of transformation of data in a pattern called the datapipe. In a number of other diagrams a detail view is given of these implementations in projects like Digital Transformation, TDP, MaxLimit and others. Hourglass ABB
Hadoop components Hadoop components
Online Data Repository Big Data Patterns
Operational Big Data Store Big Data Patterns
Parallel BDP-DWH ABBThe parallel integration is an extension of the DWH functiionality with the Big Data Platform. This extension makes it possible to use both functionalities side by side. Characteristics
  • Easy (incremental) introduction of the Big Data functionality
  • Integration of both functionalities requires attention for the introduction of the interconnect functionality because this can become a bottleneck in performance and configuration
BD-DWH Integration ABB
Poly Sink Big Data Patterns
Poly Source Big Data Patterns
Poly Storage Big Data Patterns
Random Access Storage Big Data Patterns
Realtime Data Processing Big Data Patterns
Relation transformation overviewOverview of the transformation from a relational database to a data targetRelational Transformation ABB
Serial BDP-DWH ABBSerial integration is implemented by introducing a big data platform for the transformation and extraction of unstructured and semi structured data as source for the EDWH functionality. Characteristics
  • Introduction of the big data platform is relatively easy since it is an extra layer added to the DWH functionality
  • Relative easy big data patterns are available because the source is always the datawarehouse
  • Introducing big data solutions for other functionalities than DHW is not possible.
BD-DWH Integration ABB
Servicemodel ABBDetailed ABB for describing the logical service interface in combination with extra governance functionalitiesServicemodel ABB
Software qualitiesThis is an overview of the Quint 2 software qualities. It can be extended with the implications for a specific projectSoftware qualities
Streaming Access Storage Big Data Patterns
Transformation detailviewIn the context of TDP is the logical application of transformation of data a characteristic pattern.. This pattern includes aspects like extract data from the source, transformation of the model or the protocol and selection of the source and the target model. Transformation exists at two levels in the hourglass. The first is transformation from the source data to the target data in a standardized model. The second is the transformation of the generic model to a specific model in use by the consumer. The last one is not explicitly modeled in the hourglass model because this is considered as an implementation of the consumer.Hourglass ABB
Transformation generic ABBDescription of the generic aspectis of the transformation application function. This has the following elements
  • Data sources
  • Transformation functions
  • Data targets
  • Data or object modeling functions
Transformation ABB/SBB
Unstructured Data Store Big Data Patterns
Virtualisation BDP-DWH ABBThis integration pattern has a close relation with the parallel integration, however there is an extra layer introduced for the virtualisation and standardisation of data extraction to consumers of the data. Characteristics
  • Virtualisation layer encapsulate the internal confuguration of the two platforms
  • The virtualisation layer requires a standardized data or objectmodel for the extraction by the consumers
  • The virtualisation can become a bottleneck in a number of qualities like performance, integratability e.g.
BD-DWH Integration ABB
XML transformation overviewIn this diagram a description of the datapipe from an (webservice) or XML file source to the target datamodel is described. This is based on the transformation of a XML model to an intermediate tabular or relational model and this is then processed in an ETL process to transform the source data model in a number of steps to the required target model.XML transformation ABB