Introduction

Bubbles is a python framework for data processing and data quality measurement. Basic concept are abstract data objects, operations and dynamic operation dispatch.

Bubbles – Virtual Data Objects from Stefan Urbanek

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

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

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)