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  • How to Data Mapping using ETL Tools in OpenERP/Odoo ?

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    The data mapping fixates on the powerful data between systems, It leads to more significant consistency, which results into preponderating productivity, reducing perpetual maintenance costs, amending readability of software and additionally making it more facile for developers to understand incipient code more expeditiously.
    There are different methods to import your data into OpenERP.

    ETL (Extract,Transform,Load)

    OpenETL (Open Source Extract, transform, and load) is a framework in python that implements ETL concepts for data import, export and withal performs some operations between import/export. Making importing even more facile along with making it more re-utilizable and less subject to errors is what EPL implementation is meant for. Data mapping encompasses the extract-transform-load (ETL) facilities utilized for bulk data kineticism. It additionally includes mechanisms to fortify perpetual kineticism of discrete records, rows between systems. Data mapping involves matching between a source and a target. For example, two databases that contain the same data elements but recognise them by different designations. A simple example of data mapping includes moving the value from a customer name field in one DB to a customer last name field in another DB. To do so, you have to define your ETL implement needs to ken that you optate to take the value from the source field customer name to the target field customer last name.

    Transformation

    OpenETL (Open Source Extract, transform, and load) is a framework in python that implements ETL concepts to import and export data and withal performs some operations between import/export. ETL implements are endeavoring to make importing even more facile and to make it more re-utilizable as well as less subject to errors. Data mapping encompasses the extract-transform-load (ETL) facilities utilized for bulk data kineticism. It withal includes mechanisms to fortify perpetual kineticism of discrete records, rows between systems.
    Data mapping involves matching between a source and a target. For example, Two databases that contain the same data elements but call them by different designations. A simple example of data mapping includes moving the value from a customer name field in one DB to a customer last name field in another DB. To do so, you have to define your ETL implement needs to know that you choose to take the value from the source field customer name, to the target field customer last name

    Load

    The load phase loads the data into the cessation target, conventionally the DW. Depending on the requisites of the organization, this process varies widely. Some data warehouses may overwrite subsisting information with cumulative information. As the load phase interacts with a database, the constraints defined in the database schema apply (for example, uniqueness, referential integrity, obligatory fields), which additionally contributes to the overall data quality performance of the ETL process.

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