Explain the high‑level data flow when accessing data from a CRM system: from database extraction, file ingestion, raw storage, to data curating.

The high‑level flow starts with extracting data from the CRM database, typically using a scheduled SQL query or an API call that pulls records into a staging area. The extracted data is then exported to flat files (CSV, JSON, or Parquet) and placed in a raw storage layer such as an S3 bucket or a distributed file system. From there, an ingestion job—often orchestrated by Airflow or a similar scheduler—reads the raw files, performs initial validation (schema checks, null handling), and writes the data into a curated layer, such as a data lake or a data warehouse.

During curating, we apply transformations: standardizing field names, normalizing values, and enriching with reference data. We also enforce data quality rules, flag anomalies, and generate lineage metadata. Finally, the curated data is made available to downstream analytics, BI tools, or machine learning pipelines. Throughout the process, we monitor job status, capture logs, and alert on failures to ensure reliability.