feat(ingest/great_expectations): support in-memory (Pandas) data assets #18502

Job	Run time
setup	32s
Build and Push DataHub GMS Docker Image	0s
Build and Push DataHub MAE Consumer Docker Image	0s
Build and Push DataHub Upgrade Docker Image	0s
Build and Push DataHub MCE Consumer Docker Image	0s
Build and Push DataHub Ingestion (Base) Docker Image	12s
Build and Push DataHub Elasticsearch Setup Docker Image	0s
Build and Push DataHub Frontend Docker Image	0s
Build and Push DataHub Kafka Setup Docker Image	0s
Build and Push DataHub MySQL Setup Docker Image	0s
smoke_test_matrix	1s
[Monitoring] Scan GMS images for vulnerabilities	0s
[Monitoring] Scan MAE consumer images for vulnerabilities	0s
[Monitoring] Scan DataHub Upgrade images for vulnerabilities	0s
[Monitoring] Scan MCE consumer images for vulnerabilities	0s
[Monitoring] Scan Frontend images for vulnerabilities	0s
Build and Push DataHub Ingestion (Base-Slim) Docker Image	8s
Build and Push DataHub Ingestion (Base-Full) Docker Image	14s
Build and Push DataHub Ingestion Docker Images	6m 25s
Build and Push DataHub Ingestion (Full) Docker Images	9m 55s
Run Smoke Tests (no_cypress_suite0)	22m 53s
[Monitoring] Scan Datahub Ingestion Slim images for vulnerabilities	2m 55s
Run Smoke Tests (no_cypress_suite1)	22m 47s
[Monitoring] Scan Datahub Ingestion images for vulnerabilities	3m 10s
Deploy to Datahub HEAD	0s
	1h 9m 12s

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