It's important to remember there are different types of analytics, both of which are important for any organization. Real-time analytics are what I would consider to be tactical. If your site is getting slammed you need to know about it - right now! And then you need to act. If you only focus on the RT analytics though it's easy to get stuck in local minimums, miss the forest through the trees, or simply not realize you're measuring the wrong things.

There are also strategic analytics. When looking at strategy, sufficient time periods are generally required. This type of analysis guides decisions in terms of months, quarters, and years. Strategic analytics are what drive the business long term. They provide the decions makers the data and visibility they need to solidify their vision.

Finally, I like to think of analytic data in 3 distinct iterative stages:

First is the data. This is the raw data spinning off the multitude of systems in any company. In any slightly complex system there are many datapoints that can be captured and counted. Companies often have entire systems just to capture the data, and this is before any analysis can occur.

Next is the information stage. In this stage all of that raw data is turned into some sort of reporting. It's still a lot of data, but is in a format that can start to be analyzed and acted upon (tactical reporting). In the past I've used various data warehousing solutions to execute on this step.

Finally, the organization turns the information into long term knowledge. This step occurs when the data has been analyzed and used to drive champion/challenger, A/B testing, etc... and those results are rolled back into the organization (vision and long term organizational changes). This knowledge also helps the organization discover what other datapoints need to be found and/or captured and the process starts again.