Use a single-stage ETL process to load all data into a data warehouse and then perform transformations and analysis.

Create a multi-stage ETL pipeline with intermediate data staging locations to handle the different data types and sources, and use Apache Spark to process the data in a distributed manner.

Only process structured data and ignore unstructured data due to the complexity of handling different data types.

Use a traditional batch processing approach to handle the data, as it is more cost-effective than using a distributed computing framework like Apache Spark.