Initial Open Source release of Data Quality Profiler and Rules Engine

Provides the following:

• Data Profilers for large volume data profiling in Spark
• Assertion rule definitions and checking
• Reference data loading and joining
• Excel and CSV reference data parsing
• JSON output enriched with data quality markers/profilers
• Metrics and summary dataframe output
• Dimensional tagging of profiler outputs (additional identifiers)
• JSON flattener
• JSON and CSV loader, extensible to other formats
• Custom key pre-processor and custom parquet row reader functionality
• Comprehensive built-in assertion rules modules, extensible
• Built-in set of field-level profile masks
• Compound assertion rule definition (i.e. a set of sub-rules must all pass)
• Human-readable Data Quality and Assertion Rule Compliance report output