There are a lot of terms in this Data-driven world which sounds almost similar that any learner beginning to explore the field finds difficult to analyze the minute differences involved in each of these concepts. I have taken two terms from these terminologies viz. Data Mining and Data Warehousing which we will try to explore in this article.
Data Warehousing is a term that is often not discussed in comparison to Data Science and others which is also why most learners are unaware of its concepts. If I start and put before you the definition of Data Warehousing then it will become quite a boring process to learn. Instead, I would like to explain this concept to you through a good example that will remain in your memory for a longer time.
Do you save your files randomly into any drive on your PC or in your Hard disk without actually caring for your important information that might be lost or do you actually try to keep all these files into a separate folder in your PC so that you can have access to any of these anytime without actually looking for in different folders or different drives?
I hope you must have the habit of keeping all your data in a well-organized way in a separate folder. Organizing has its own way of clarity and understanding. The broader view of this simple habit of organizing data into a single database becomes the base for Data Warehousing in an organization where all of the data of the organization from various sources are put into a single database.
This obviously is a clear approach to handle such a large amount of data in an organization where data is always flooding from various sources. Indeed, Data Warehousing will help the organization in doing many works with data like Data mining, which I am going to brief you in the following part of this article. Data Warehousing is a very important process for the organization in terms of having their data in one unit which is safe, secure and accessible with much clarity than the unorganized data. I hope you must have understood the concept of Data Warehousing till now and now it is a good time to move into the next part of understanding Data Mining.
You need to have done Data Warehousing before doing Data mining. Understand Data mining in the sense that you need to analyze the large dataset in Data Warehouse and find those hidden meaningful patterns that are required by your business to extract information from it. Extracting information simply means that you need to find those patterns in data that were not known before. You can also consider it as a first approach to do with your data where you trying to find the information contained in it, the patterns contained in it. You are not actually analyzing the data in terms of finding some of the key answers to your business. You are just finding the patterns from that. The analysis will be a later step which will be done in Data Analysis which is also quite confused with Data Mining.
Now the point has arisen in the article where we are known of Data Mining and Data Warehousing. Now could you relate these two terms and find out the differences that actually sets them apart. I hope you must be in that position now. Data Warehousing is moving all your required data into a database while Data Mining is the next step involved in finding out the information from that data stored in the database.