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This data science "kit" was built to help data science teams get started with exploratory data analysis and algorithm development with a product architected with a service or microservice architecture. With such architectures, data is distributed across a number of isolated databases, SQL and non-SQL. This presents a challenge to developing analytics that require complex joins of data across the service databases. This data science toolkit solves this problem by providing programs to dump service databases as JSON row files, and then use those files as a unified Spark SQL data where big-data queries and map/reduce algorithms can be applied.

Home Page: https://github.com/jpictor/dskit

License: MIT License

Python 86.20% Shell 13.80%

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