For the success of any venture, it is mandatory for you to turn information into actionable knowledge. Unfortunately, this is something you can never achieve hassle-free especially when you do not have the right business intelligence tools in place. By business intelligence tools we are simply referring to data warehousing and data mining. But are these two related? If you thought they are the same, then it is high time that you erased this information completely from your mind.

One of the most important distinctions between these two business intelligence tools emanates from the methods and processes relied by each of them to achieve desired goals. With data mining, analysts have to make do with technical tools when querying or examining terabytes of data in search of patterns. In most cases, the analyst will be forced to come up with a hypothesis. Businesses can then use this information whenever they want to make well-informed decisions. After all, they only have to understand the behavior of both their customers and suppliers.

When it comes to data warehousing, it is all about explaining the process involved when determining how you are going to store data. This action is aimed at making sure businesses improve reporting and analysis. In fact, data warehouse experts consider different stores of data to be connected to each other. Even though businesses rely on multiple databases when storing data, they must collect all the data in some way when planning to analyze it. To cut the long story short, all data within them must be related to any other critical data available. It is only then that businesses can examine this data for reporting purposes.

So, the crux of the relationship that exists between data mining vs data warehousing is based on the ease of mining properly warehoused data. Be sure to seek the help of experts if you are still finding it hard in telling the difference between data mining and data warehousing. It is then that you can take your business a notch higher within the shortest time possible.