First you collect tons of data through data warehousing.
Then you analyze the data in the data warehouse. How do you analyze it? By letting computers take the data and perform all sorts of calculations ahead of time. They precompute all the values that would otherwise take too long to obtain on the fly.
The resulting bunch of precomputed data is the OLAP cube. It’s a nice, big cube of raw and precomputed data that can be sliced and diced nicely.
Data warehousing is exactly what it sounds like. You use data warehousing when you have a company that produces so much data that you can no longer analyze the data instantly using simple SQL queries.
In data warehousing, huge amounts of data are stored in the data warehouse. The data warehouse is like a little Costco of bits on a hard drive. It’s physically small compared to a real Costco, but it’s huge compared with the average database.
The data from the data warehouse gets analyzed and processed ahead of time, since it can’t be done instantaneously. Usually this processing is done overnight, because at night there is very little or no new data being collected.
Businesspeople have a whole bunch of data thrown at them. So much data, in fact, that making decisions based on all the raw data will make their heads spin.
That’s why there are tools called analytics. Analytics are all about analyzing the data and digesting it into a form that businesspeople can use to make decisions.
Enterprise business solutions, data warehousing, product lifecycle management, and business intelligence. What do all of those terms mean, and what opinions about them should I have in order to sound intelligent during business lunches?
This site will attempt to clear up the confusion as well as provide thoughts and opinions for you to recycle during those business lunches.
That way, you will not have to work so hard on learning these things, and therefore you will have more time to practice golfing so that you appear to be experienced during those business golf outings.