Meta Data Demo Cases | Demo Case DaMAcademy | Objects |

Objects

Versie	1.0
Creatie datum	23-12-2021

Packages

BIVP

• BIVP

Data qualities

• Data qualities

Elementen

• Trainer
• Employee
• Trainee
• Classroom training
• Registration
• Online training
• Training
• Person
• Training Session
• Big Data Introduction Utrecht 01-02-21
• Andy
• Moodle online training
• Bob
• Cindy
• Registration at 01-12-20
• Big Data Introduction

ApplicationComponent

• KA DWH
• Microsoft Dynamics
• AFAS HRM
• Moodle
• Consuiming systems
• AFAS
• Oracle Workflow and Scheduler (11)

ApplicationFunction

• Data Storage
• Data Protocol Transformation
• ERP
• Data Validation
• Register Data Consumption via Integration
• Data Publication
• Physical modeling
• Manual Data Validation
• Transform
• Register Data Consumption
• Register Data Production
• Data Registration
• Automated Data Validation
• Other Data Producers
• Data Processing
• Data Model Transformation
• Workflow management
• Modeling
• Register Data Consumption via User Interface
• Logical modeling
• Extract
• Master Data Modelling and Meta Modelling
• Data Register
• Geo
• Load
• Master Data Management and Governance

ApplicationInterface

• Export Office documents
• Geo viewer
• Forms and pages
• Views and materialized views
• Report
• Dashboard
• Change Data Capture
• JSon/REST
• Geo webservices to consumers
• File transfer
• Webservice
• Application integration for registration
• SOAP-XML webservices
• Graphs
• Fileshare
• Packages and stored procedures
• SOAP-XML webservices to consumers
• FTP
• GEO ETL
• Forms and reports
• Managed File Transfer
• SFTP
• Relational ETL to consumers
• Geo webservices
• Geo ETL to consumers
• Unmanaged File Transfer
• Import Office documents
• Relational ETL
• Data entry screens
• User Interfaces for Publication
• User Interfaces for registration
• Managed File Transfer to consumers
• Application integration for publication
• XML/SOAP
• Database link

ApplicationService

• Data Acquisition/Registration Service
• Register Data Publication and Integration Service

BusinessActor

• Backoffice
• Management
• Trainee
• Trainer

BusinessObject

• Classroom training
• Training Session
• Trainer
• Employee
• Trainee
• Person
• Training
• Online training
• Registration

BusinessProcess

• Register for training
• Training planning
• Trainer selection and accreditation
• Human Resource Management

BusinessRole

• Asset management
• Clients and Markets
• Sector representation
• System Operations
• Contractors
• Government agencies

DataObject

• DataMart Registration
• Training
• Data target
• XML based webservice
• XML File

Deliverable

• Introduce Geo extension in database
• Datatype evaluation relational database
• Map application datamodels to logical datamodel

Goal

• Trainer Satisfaction
• Complliancy with GDPR
• Quality of reporting
• Employee satisfaction
• Stakeholder satisfaction
• Compliancy with legislations
• Quality of registration
• Trainee satisfaction
• Quality

Principle

• Flexibility of integrating different parallel data sources and providing scalable real time data
• Data analytics based on data integration layer provides real-time performance and scalability next to batch processing
• Data ownership/stewardship and control of the data in the data integration layer.
• Scalability with the number of connected devices to provide a basis for real-time analytics
• Data is a valuable asset
• Functionalities plugged in on top of dedicated data integration layer
• Prioritized capabilities are incubated in a learning environment and OTAP
• Compliancy with privacy legislation (GDPR)
• Compliancy with law and legislation
• Flexible customizable analytics functions
• Virtualized infrastructure
• For all data entities is meta data available
• A central design authority governs the data sources and the data integration layers
• The functional data analytics layer and the data integration layer are coupled by a standard information model
• Distinguish and decouple classic BI, near real-time BI and real-time OI and prioritize OI real-time requirements.
• Data entities have a common definition
• Cloud and on-premise deployment options
• Processes are supported by data fit for purpose
• Data sources on heterogeneous environments
• Layered Architecture
• Customizable self-defined API to access platform services
• Functional modules and data integration layer can be hosted on different physical environments
• Dedicated access via authorization and authentication mechanisms on data integration layer
• Ability to abstract on the data sources via implementation of specific connectors

Requirement

• Helpfullness
• Fault tolerance
• Understandability
• Availability
• Maturity
• Tracability
• Time behaviour
• Interoperability
• Changability
• Stability
• Recoverability
• Testability
• Replacability
• User friendliness
• Compliance
• Learnability
• Operability
• Degradability
• Installability
• Resource behaviour
• Maintainability
• Explicitness
• Managability
• Analysability
• Portability
• Accurateness
• Efficiency
• Reliability
• Attractivity
• Clarity
• Usability
• Specific requirements
• Adaptability
• Security
• Conformance
• Generic requirements
• Suitability
• Functionality
• Reusability

Stakeholder

• Trainer
• Employee
• Legislator
• Trainee

TechnologyService

• Authentication
• Permission management
• Data Zone Protection
• Facility Monitoring
• Access Distribution
• Access Security
• Identification
• Authorisation

EAMatrixSpecification

• Data ownership
• Data Quality Score
• CRUD Matrix

table

• Online training
• DimTraining
• FactRegistration
• Employee
• Person
• Trainer
• DimTrainee
• Classroom training
• Registration
• DimTime

XSDcomplexType

• Person
• Registration
• Trainer
• Training Session
• Classroom training
• Employee
• Trainee
• Online training
• Training

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