There are quite a few different ways to accomplish this; martin_mueller suggestion is a good one. However, speaking from experience, this is a very difficult thing to monitor without getting a ton of false positives. It all depends on the data you are watching. If for example you were to setup such an alert for Windows Event Log events, you would find that it probably trips every Monday morning when you have a bunch of users accessing the network at 8:00AM. If you adjust the thresholds to ignore this, you risk missing a similar (unexpected spike) at 11:00PM on a Sunday.
I setup some similar alerts, and spent a good week writing horrendous search queries that were many liens long. I ended up comparing the data coming in over the last hour, to the average data coming in during the same day/hour for the last 4 weeks. After fiddling with this for two months, and still not getting what I wanted, I gave up, just graphed the data on a chart, and got an intern to sit and watch it for anomalies.
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