This document discusses data warehousing over Hadoop and strategies for low-latency querying. It covers columnar formats like ORC and Parquet that provide optimizations for queries. It also discusses different query engines like Hive, Impala, Presto, and Spark SQL and their capabilities. The document notes that converting data to optimized formats during or after collection can help minimize latency conflicts between processing and query performance. Technologies like Sqoop, Hive ACID transactions, streaming ingest into Hive, and Flume can help convert or ingest data in optimized formats with lower latency.