What is data mining?

Data mining is integral to business development. In simple terms, data mining is a great technological process that helps businesses and companies collect the online data of their customers and convert this into useful information that helps them understand the reaction of the customers to their products or services. Data mining helps companies and businesses gain access to information that queries and reports can’t uncover. A company that understands how to mine their customer’s data would be able to know the best way to handle their customer needs and ensure they satisfy these needs. Data mining can be used in a number of ways including credit risk management, database marketing, fraud detection, and filtering spam email. 

The quality and volume of data a company can collect about their customers can determine how well they would be able to satisfy their customers. Data drives everything in the business world. Starting from the stage of manufacturing to the point of satisfying the customer, data can help to determine a lot of things. Data holds the power to make the process of production less difficult and consequently make the product cheaper and more satisfying to the customer. Data can help a company that is struggling to get to the top in no time.

There are five ways to process involved in carrying out data mining, these processes include: 

Extract, Transform, and Load (ETL): in data mining, the first stage is the stage of extracting the customer’s details online. Some of the sources that companies can access the detail of their customers include Logistic Management Tool, Retail Point of Sales Software, and lo T-equipped manufacturing machinery). Having extracted the data from any of these sources, the data is then loaded into the data warehouse.

Store and Manage: once a company or business has saved the customers' data in the data warehouse, the next action is to manage the data in a multidimensional database system such as tabular cubes or OLAP.

Access: after extracting and managing the data, the next action is to employ a professional data analyst that would determine the vital data among the numerous data that has been extracted.

Analysis: The next action is to analyze the already filtered data by the data analyst. 

Present: the last action is to present the data to the end-user. Before this stage, the data must have been thoroughly analyzed and converted into information that is useful to the company’s management team. 

Data Warehousing

Data warehousing is an important aspect of the data mining process used in consolidating data located in disparate databases. A data warehouse stores large databases in specific categories so that the data would be easier to extract and use. The warehouse made it easy for a company to store well-detailed data that provides the company with the rightful information needed to respond adequately to the customer's needs. 

However, in order case, the analyst may create a data warehouse for specific kinds of data, whichever way the analyst chooses to do this, having a data warehouse makes it easy for the company to analyze their customers'