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Simplifying the Oracle Database Data Mining Parameters for Your Business

Oracle commerce offers an effective platform for e-commerce websites backed by a robust and specialized design. As the leading database solutions provider, according to a 2014 study by eRetailer, this system offers proven, tested and optimized capabilities over the years.

Behind the success of Oracle database is highly scalable technology that enables you to efficiently manage large volumes of data. More importantly, through Oracle Advanced Analytics SQL API, data mining your business is able to sort through this data, identify customer shopping patterns and establish relationships that come in handy in targeting your customers.

Capitalizing on Oracle Database Capabilities

Over the last five years, e-commerce has evolved from just an ephemeral marketing platform to a full bloom business concept that cannot be ignored. One reason for this success is seamless online data flow. As a shrewd investor, you can optimize this data to learn customer preferences and thus apply targeted marketing. This is where Oracle e-commerce database mining comes into play.

Key Parameters in Oracle Data Mining

Data mining might sound too complicated because software technology is involved. Well, this doesn’t have to be so. To appreciate what Oracle database mining is all about, check out these parameters used to categorize the data for your company’s use:

  1. Data association: This involves searching for events that are closely connected to each other. The system will look for rules associated with frequently co-occurring items. It is crucial in bundling products, in-store placement, among other functions.
  2. Clustering: This parameter sieves through your database to find natural groupings which feature similarities within the database. These clusters are initially unknown and the system is thus important to help form customer segments, which your business can then use for email marketing and other targeted advertising.
  3. Classification: This is considered the most important parameter in any Enterprise Performance Management (EPM). It looks for, and identifies, new patterns and sequences. It is thus important in predicting customer responses, for example, if they will buy or not. This in turn helps classify customers as high-value, mid0-value or low-value, among other classifications.
  4. Anomaly detection: Through Oracle Advanced Analytics SQL API, data mining your business can stay alert because all deviations from the norm are noted through this parameter. Fraud instances, such as health fraud, expense report fraud, among other vices, have been detected in this aspect of data mining.
  5. Predictive analytics: Forecasting is an important part of every company’s strategy and through this e-commerce platform, your business will have a basis to form a better future strategy. Predicting a continuous numerical outcome, including long-term value of a customer, helps you in revenue projection and also in marketing.
  6. Attribute ranking: This is an intensive ranking process done by the Oracle database where your business gets findings based on the strength of the target attribute. This will help you appreciate if there is a correlation between a particular attribute and the way a customer responds. If there is, you can then target more customers from your database with similar attributes.

Amazing what technology can do, isn’t it? The fact that all this is done by the Oracle EPM in real-time makes data mining an invaluable business tool.

BIO

Jim Chu has worked as a database expert over the last 16 years in several continents. After active employment, Chu has concentrated on consultancy specializing in Oracle Enterprise Performance Management (EPM).

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