Introduction to our Client
The Manufacturing industry provides solutions and trusted insight accelerate innovations in electronic design, test, manufacturing, and optimization.
The Datawarehouse was Oracle DWH Reverse Engineering on the Data Trace was getting challenging day by day as there was no appropriate Data Model created at the design phase for instance, if there were issues addressed by users then tracing a Single Column back to source and mapping it to target took close to a week.
1. Oracle DWH was studied, and 2 Major Sales order tables were picked for Migration to Redshift
2. Data Model was built as part of this Study Phase
3. Columns 1-1 Mapping was performed
4. Data from Oracle in CSV format was pulled to AWS S3 data lake using AWS GLUE
5. Data Was catalogued using AWS GLUE
6. External Hive tables were created using GLUE
7. These External Tables were then Exposed to Athena for Ad-Hoc querying.
8. Data model was deployed on AWS Redshift which was designed in Step 2
9. Data from S3 was ingested to Redshift VIA AWS GLUE
10. Modern DWH was made available for Analytics and for downstream systems.
3. AWS RDS Postgress
4. AWS DMS
Move Legacy Datawarehouse to Modern Datawarehouse in AWS with appropriate Data Models and Mappings
Industry’s initial direction was TIBCO Spotfire for BI, however we did some comparison studies on functionalities, ease of use, support and Serverless with AWS Quick Sight and helped the team to Build their first Prod ready Dashboard on AWS Quick Sight
Management very well appreciated the AWS Cloud Journey. The End to end Project was completed in ~6 weeks