- Integrate sources
- Manipulate data
- Read log files, social media
- Read to Apache Hadoop, Google Cloud
- NoSQL connectors
D-Hub – Content Hub
Establish a “single source of truth” for your data
Administrate your data within hours, not weeks.
D-Hub contains all necessary tools
Enterprise Service Bus
- Combine data channels
- Route data
- Synchronize data, with source and target
- Compliance to company and industry standards
- Structure data
- Enrich data using reference data
- Create web-based reports
- Read data in realtime or batch mode
- Read local sources or Cloud sources
- Read grid systems
Master Data Management
- Create a unified data model
- Handle multiple domains
- Track master data using tasks
Business Process Management
- Model current processes
- Create human interactive processes
- Create application based processes
ESB, MDM, MAPPING – ?
Acronym used for data management will need an explanation
DATA MANAGEMENT ANNO 2016
The discussions of data management starts with using a number of expressions. ESB, MDM, Mapping, WebService etc. Bottom line of the discussions are that data from different sources and with different formats can today be combined without any classical programming. Data management is now done with help of interactive tools. We use a set of tools we call D-Hub.
An enterprise service bus (ESB) is simply a software architecture model. Usage is for designing and make communication available between different applications. The ESB translates each message to the correct message type needed for each producer and customer service. Unfortunately there is no global standard for ESB concepts or implementations. One implementation of an ESB is the network design of the Internet (World Wide Web).
The expression master data management (MDM) refers to an enterprise reference data and analytical data that supports decision making. MDM is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference. Creation of MDM data can simplify the process of handling data in multiple system architectures and sources.
Data mapping is the process of creating data elements between two different data models. Example can be the data model for customer data in one ERP system and the data model of customer data in PEPPERI. Data modelling always includes manual work and can be very time consuming.
Transform data in real time or in batch mode. It can be both operational data or statistical data. Data integration can be used as an ETL process (Extract Transform Load) or as a process using a mediated schema (virtual schema) against which users can run queries. Web applications tend to use the mediated schema concept as this this solution offers the convenience of adding new sources by simply constructing an adapter.