You manage an Azure SQL Database supporting a reporting workload. A large fact table (2 billion rows) is queried almost exclusively with analytical scans that read wide ranges of rows; the table is rarely updated after nightly bulk loads. Storage costs are rising and you notice heavy I/O pressure during report execution. You want to reduce storage footprint and physical I/O while keeping CPU overhead acceptable for this read-mostly, scan-heavy pattern. Which data compression option should you apply to the fact table?