Objective
Enable the airline ingest the heterogeneous and diversified data sources into the newly designed data lake house and the EDW using Data-bricks technology, to meet the Enterprise Analytical needs for faster and robust business decision making.
Our Solution
- Design and development of the Data Lake house and the EDW on AWS Data bricks platform
- Data ingestion from heterogeneous sources like Greenplum, Oracle and reading different file types like csv, json, and fixed width (imp) etc.
- Delta and Hive table creation using spark and spark-sql.
- Designed 4 data layers vis – Bronze, Silver, Silver-derived, and Gold.
- De-dup, Cleansing and SCD implementation at Silver and Silver-derived level
- All required business use case implementation
- Visualization and Dashboard creation
- AdfarTech roles are implementation of the end-to-end solution – from setting up the AWS Data-bricks environment to Staging, Ingesting, Enriching, Curating to Publishing the data.
Impact
- Data Lake-house and Enterprise Data Warehouse for all Enterprise DSS needs
- Enterprise wide cleansed, de-duplicated and analytics ready data
- Managed data along with well managed history data
- Robust Data quality and Data Governance processes provided assurance and improved adoption of the platform
- Use Case driven actionable road map to achieve incremental benefits
- An enterprise wide futuristic, scalable and robust analytical workbench for impactful and robust business decision making
