What rule-based automation frameworks does Azure Blob Lifecycle Management employ to systematically transition data between hot, cool, and archive tiers? Furthermore, why is defining automated age-based deletion policies for massive, uncompressed object datasets the absolute best strategy to optimize cloud spend and minimize manual operational overhead?