What ' s the difference between data mining and data warehousing?

Data mining is the process of finding patterns in a given data set. These patterns can often provide meaningful and insightful data to whoever are interested in that data. Data mining is used today in a wide variety of contexts–in fraud detection, as an aid in marketing campaigns, and even s Upermarkets use it to study their consumers.

Data warehousing can said to being the process of centralizing or aggregating data from multiple sources into one Common repository.

Example of data Mining

If you've ever used a credit card and then your may know that credit card companies would alert you when they think R credit Card is being fraudulently used by someone and other than. This is a perfect example of data Mining–credit card companies has a history of your purchases from the past and know G Eographically where those purchases has been made. If all of a sudden some purchases is made in a city far from where you live, the credit card companies is put on alert t o A possible fraud since their data mining shows that's you don ' t normally make purchases in this city. Then, the credit card company can disable your card for this transaction or just put a flag on your card for suspicious AC Tivity.

Another interesting example of data mining is what one grocery store in the USA used the data it collected on it ' s shoppers To find patterns in their shopping habits.
They found that when men bought diapers on Thursdays and Saturdays, they also had a strong tendency to buy beer.

The grocery store could has used this valuable information to increase their profits. One thing they could has done–odd as it sounds–is move the beer display closer to the diapers. Or, they could has simply made sure not to give any discounts on beer on Thursdays and Saturdays. This is the data mining in action–extracting meaningful data from a huge data set.

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Example of Data Warehousing–facebook

A Great example of data warehousing so everyone can relate to be what Facebook does. Facebook basically gathers all of your data–your friends, your likes, who you stalk, Etc–and then stores that data int o one central repository. Even though Facebook most likely stores your friends, your likes, etc, in separate databases, they does want to take the MoS T relevant and important information and put it into one central aggregated database. Why would they want? For many Reasons–they want to make sure so you see the most relevant ads that you ' re most likely to click on, they wan T to make sure that the friends that they suggest be the most relevant to you, etc–keep on mind that this is the data m Ining phase, in which meaningful data and patterns is extracted from the aggregated data. But, underlying all these motives are the main motive:to make more Money–after all, and Facebook is a business.

We can say that data warehousing are basically a process in which data from multiple sources/databases are combined into one Comprehensive and easily accessible database. Then this data are readily available to any business professionals, managers, etc. who need to use the data to create Forec Asts–and who basically use the data for data mining.

Datawarehousing vs DataMining

Remember that data warehousing is a process this must occur before any data mining can take place. In other words, data warehousing are the process of compiling and organizing data into one common database, and data mining Is the process of extracting meaningful data from the. Database. The data mining process relies on the data compiled in the datawarehousing phase in order to detect meaningful patterns.

In the Facebook example that we gave, the data mining would typically be done by business users who is not engineers, but Who would most likely receive assistance from engineers when they is trying to manipulate their data. The data warehousing phase is a strictly engineering phase, where no business users are involved. And this gives us another the defining the 2 terms:data mining was typically done by business users with the assistance of engineers, and data warehousing is typically a process do exclusively by engineers.

What ' s the difference between data mining and data warehousing?