Data Mining

What Is Data Mining?

Data mining is the in-depth analysis of a data set in search of useful information and actionable insights. The process behind data mining involves identifying patterns and correlations among fields in large relational databases.

A variety of software and shareware programs, available from SAS, Cognos, Microsoft, and other brands, allows users to analyze data from multiple angles, categorize it, and identify relationships.

Data mining software includes statistical, machine learning, and neural networks used to analyze transactional data relationships and patterns based on open-ended user queries. Relationships may include classes, clusters, associations, or sequential patterns.

While a relatively new term, data mining is not entirely new as a concept. For many years now, companies have been using powerful computers to sift through vast amounts of supermarket scanner data and transactions. However, technological advances in computer processors, storage, and software are making data analysis faster, cheaper, and more commonplace.

The data mining process typically includes five components:

  • Extract and load data into the warehouse system.
  • Manage the data in a multidimensional database system.
  • Provide data access to business analysts and technology professionals.
  • Analyze the data using application software.
  • Provide a visual presentation of the data to stakeholders.

Sifting and Sorting

Private and public organizations around the world are accumulating vast amounts of data in a wide variety of formats and databases, including:

  • Data – Including transactional data (sales, expenses, etc.), nonoperational data (industry and competitor data, macro economic data, etc.), and meta data (data about the data itself)
  • Information – Discovering patterns in all the cumulative data can yield insights into consumer behavior, for example.
  • Knowledge – Studying historical patterns can help forecast future trends.

A key precursor to data mining is data warehousing. By centralizing the storage of all data management and retrieval, organizations are able to maximize their data mining efforts through data analysis software. Recent software advances have made this a fast-growing source of information and a priority initiative for many large organizations that recognize the potential for competitive advantage.

Who Is Data Mining?

Big brands. The large corporations/brands who sell directly to customers are positioning themselves to uncover marketing gems through data mining. By analyzing correlations between internal factors such as price, cost, and inventory with external factors such as the economy, competition, and consumer trends, these companies can more astutely time their sales, product launches, advertising campaigns, and more. It also allows them to better forecast future profit and loss.

With data mining a retailer can:

  • Send targeted promotions based on an individual’s purchase history.
  • Develop a product to appeal to a specific segment by analyzing demographic data from warranty cards.
  • Manage inventory at a micro level by accessing store-level data on consumer buying patterns.