THE JEWELS OF DATA MINING

Mining for jewels is not an easy task, you need all the useful information you can get to harbour precious stones such as rubies, sapphires and emeralds. But it is not an easy task, usually in mines not all rocks contain elegant stones so the information you have in hand must be accurate to get to your goal and successfully get what you want.

Data Mining is also similar to Geographic Mining, according to the introduction to Data Mining by Kurt Thearling: “Data Mining is the extraction of hidden predictive information from large databases”. It is a powerful technology that is developed through the years of data collection and is used to harvest the most important information hidden or stocked in data warehouses. It is considered so powerful because according to the article it cannot only solve business problems but predict the future trends of your businesses so you can come out with a plan before the problem even starts.

To operate such complicated software Data Mining needs three basic foundations. First, it needs a memory that can handle various amounts of data because of the existing amount of information today. Second, it needs multiprocessor computers which can analyze data in shorter time to gather data faster. And third, it needs Data mining algorithms which serve as the protocol in managing information. With these foundations Data mining is considered stable.

So what are the advantages of data mining?

Given its big memory size and quality of its service Data Mining can provide Capabilities like Automated prediction of trends and behaviour and discovery of unknown existing patterns.
Because it can forecast in to the future trend or demand the user of Data Mining can have a competitive advantage over its competitors because they have a step forward against them. And since it can see through the unusual patterns in demands the company can see the anomalous data in the data warehouse and they can fix it before it can cause trouble to the data reservoir.

Data Mining is also a great aid to Database Systems and Data Warehouses because it had made getting the data you want easier. The book “MANAGEMENT INFORMATION SYTEMS BY HAAG” defines Database as a collection of information that you can organize access according to the logical structure of the information. Data mining tools such as Query and Reporting tools, Intelligent Agents, Multi dimensional Analysis and Statistical Tools are used to query information in a Data Warehouse. Here is the Information about the following Data Mining Tools:

· Query and Reporting Tools: Similar to QBE tools, SQL, and report generators in the typical database environment.

· Intelligent Agents: Utilize various artificial intelligence tools such as neural networks and fuzzy logic to form the basis of “information discovery” and building business intelligence in OLAP.

· Multidimensional Analysis: Slice and Dice techniques that allow you to view multidimensional information from different perspectives.

· Statistical Tools: Help you apply various mathematical models to the information stored in data warehouse to discover new information.



As I go down to this part I realize that Data Warehouses and Data Mining are related to business intelligence and gaining competitive advantage. Due to the information extracted from your data warehouse you can get knowledge about customers, competitor’s partners, suppliers, the competitive environment and your internal operations. These factors can help a company build effective and important business decisions. It can be also be combined to one’s advertising strategy, information on customer demographics and can identify possible target markets.

Now that you can see that Data Mining, Data Warehouses and Business intelligence work hand in hand to produce a significant data and helps company build better strategy as well as competitive advantages over their competitors.

Relating to Telecommunications Data Warehouse, Data Mining and Business Intelligence can be helpful in their strategies. For example, Smart Telecommunication needs to successfully identify its target market and aligned its advertising strategy to that market. With the existence of data warehouse SMART’s marketing team can trace out the biggest market shares of cell phone users based on the latest trends, with that smart can point out to which customer they will advertise their commercial advertisements. Another application of data mining is that it can trace which post paid users are willing to have a second post-paid account. Not only it saves money in advertisements it also gives very useful information with just a touch of the user’s finger. It is very convenient and at the same time efficient.


In Conclusion, INFORMATION is very valuable to a company so they need the proper data mining tools in order to get the proper information that is hidden under the bedrock of data.

With the help of Kurt Threaling’s site and our reference book in Data mining I was able to come up with this blog. But I find it hard to read Kurt Threalings’s Post because most of the terms in the overview are too long and full of information. I think it would be best if the writer chops down the chunks of information posted on the readings so that the readers can easily digest all the complicated terms. And I hope that in our Datamin class Mr. Ramon Duremdes can give us a more detailed idea about the
subject matter for the benefit of the whole class.

For more information about Data Mining please see the blogs of my fellow colleagues: Danielle Benig, Camille Caleon, Jerika Hemedez and Julie Nolasco.