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Bubbles | Data Brewery

Bubbles is a Python. Framework for data processing and data quality measurement. Basic concept are abstract data objects, operations and dynamic operation dispatch. Understandability of the process. Auditability of the data being processed (frequent use of metadata). Bubbles is performance agnostic at the low level of physical data implementation. Performance is assured by the data technology and appropriate use of operations. When you might consider using Bubbles? Learn more about unknown datasets.

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Bubbles | Data Brewery | bubbles.databrewery.org Reviews
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Bubbles is a Python. Framework for data processing and data quality measurement. Basic concept are abstract data objects, operations and dynamic operation dispatch. Understandability of the process. Auditability of the data being processed (frequent use of metadata). Bubbles is performance agnostic at the low level of physical data implementation. Performance is assured by the data technology and appropriate use of operations. When you might consider using Bubbles? Learn more about unknown datasets.
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7 data integration
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Bubbles | Data Brewery | bubbles.databrewery.org Reviews

https://bubbles.databrewery.org

Bubbles is a Python. Framework for data processing and data quality measurement. Basic concept are abstract data objects, operations and dynamic operation dispatch. Understandability of the process. Auditability of the data being processed (frequent use of metadata). Bubbles is performance agnostic at the low level of physical data implementation. Performance is assured by the data technology and appropriate use of operations. When you might consider using Bubbles? Learn more about unknown datasets.

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Bubbles | Data Brewery

http://bubbles.databrewery.org/index.html

Bubbles is a Python. Framework for data processing and data quality measurement. Basic concept are abstract data objects, operations and dynamic operation dispatch. Understandability of the process. Auditability of the data being processed (frequent use of metadata). Bubbles is performance agnostic at the low level of physical data implementation. Performance is assured by the data technology and appropriate use of operations. When you might consider using Bubbles? Learn more about unknown datasets.

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Bubbles | Data Brewery

http://bubbles.databrewery.org/documentation.html

Bubbles (Brewery2) - Operations. If you have any questions, suggestions or ideas, you can reach Bubbles developers and users here:. IRC: #databrewery at freenode.net. Bubbles Virtual Data Objects. And contributors. Brewery, Cubes and its documentation are licensed under slightly modified MIT license. Design by Andrej Sykora. Website generation by Pelican.

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Follow me on Github:. Is a collection of open-source data warehouse libraries and tools. Lightweight distributed online analytical processing ( OLAP. Framework and server. Used for analytical modelling and aggregated browsing. Serves as a foundation for reporting and analytical applications. Experimental data integration framework based on metadata composition of abstract data objects. Keeps the data in their natural. Various contributions to the GNUstep. San Francisco, CA, USA.

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Bubbles | Data Brewery

Bubbles is a Python. Framework for data processing and data quality measurement. Basic concept are abstract data objects, operations and dynamic operation dispatch. Understandability of the process. Auditability of the data being processed (frequent use of metadata). Bubbles is performance agnostic at the low level of physical data implementation. Performance is assured by the data technology and appropriate use of operations. When you might consider using Bubbles? Learn more about unknown datasets.

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