Indeed, there a few different dimensions to consider when planning to scale your BI environment. For instance,...
there is the "mixed workload" factor -- query processing versus ETL. Adding additional processing power and memory is the most effective means of addressing incremental growth of data. It's important to realize however, that there's a point at which the physical table structures -- not to mention the physics of disk I/O -- will prevent the linearity of queries (e.g., in order to support x percent new data, add x percent new storage and CPU). Because ETL is much more I/O intensive than standard query processing of most BI environments, simply adding more storage and CPU can be impractical. Bottom line, you can't just throw more horsepower at more data.
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