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Introduction
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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.
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Priorities of the framework are:
* understandability of the process
* auditability of the data being processed (frequent use of metadata)
* usability
* versatility
Bubbles is performance agnostic at the low level of physical data
implementation. Performance should be assured by the data technology and
proper use of operations.
Uses
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When you might consider using bubbles?
* data integration
* data cleansing
* data monitoring
* data auditing
* learn more about unknown datasets
* heterogenous data environments – different data technologies
Modules
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The framework consists of several logical modules (not published as Python
modules):
* `metadata` – field types and field type operations, describe structure of
data
* `objects` – data object core
* `stores` – stores of data objects
* `core` – operation core, includes OperationContext
* `backends` – various backends such as SQL or text (CSV)