What are the Key Concepts of Talend ETL? PDF Print E-mail
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What are the Key Concepts of Talend ETL?
Data migration
Data synchronisation & replication
ETL for Business Intelligence & Data Warehousing
Data Profiling
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Data Synchronisation and Replication

In many organisations, large or small, it is often the case that data is managed separately by multiple applications and/or databases, yet there is a need for that data to be kept consistent across all instances. This requirement for data synchronisation can be permanent involving day-to-day operational systems or temporary as in the phase of a migration. To ad complexity, this synchronisation may not be simply mono-directional but require bi-directional flows.

 

Typically data synchronisation is described as including all the processes that maintain data alignment between the applications and databases and there are many challenges to implementing an efficient and reliable solution.

 

Data synchronization often involves processes which tend towards operating in a real time environment and it is therefore critical to manage data effectively to reduce processing time. Additionally, the environments involved tend to be heterogeneous often combining legacy systems, packaged applications, RDBMS, mainframes, files, etc. across which data structures vary widely but still need to be maintained in sync. These differences can entail complex mappings between sources and targets, as well as aggregations, calculations, etc. Moreover, when conflicts of data occur, they must be managed and resolved taking into account record update precedence.

 

Talend’s data integration solutions are optimized for enterprise-scale data synchronisation and are designed to navigate you through the key areas of design, development, execution and maintenance of data synchronisation processes: 

 

 

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    • Business-oriented process modeling ensuring consistency in the migration of business data and processes
    • Fully graphical development environment that improves productivity, facilitates maintenance and reusability of data mappings and transformations
    • Scalable and fast execution platform with a grid approach that enables the processing of data close to its source and target for shorter downtimes
    • Broad depth of connectivity to support all source and target systems

 

 

 



 
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