Data Mining on Azure ML Studio

What is Data Mining?

Data Mining is a Knowledge Discovery in Databases (KDD) process, which identifies relevant patterns in data, so people can get useful, valid and pertinent knowledge that they can use for making decisions in business.

It is important to emphasize that, before starting the data mining process, it is necessary to execute prior tasks for selection and pre-processing or transformation of data.

Data Mining Benefits

Market Analysis and Management

  • Customer Profiling: Data mining helps to determine what kind of people buy a specific product.
  • Identifying Customer Requirements: Data mining helps in identifying the best products for different customers. It also predicts factors that may attract new customers.
  • Cross Market Analysis: Data mining performs associations/correlations between one or more product sales.
  • Target Marketing: Data mining helps to find clusters of model customers who share the same characteristics- such as interests, spending habits, income, etc.
  • Determining Customer Purchasing Patterns: Data mining helps determine customer purchasing patterns.
  • Providing Summary Information: Data mining provides a variety of multidimensional summary reports.

Corporate Analysis & Risk Management

  • Financial Planning and Asset Evaluation: For cash flow analysis/prediction and contingent claim analysis to evaluate assets.
  • Resource Planning: For summarizing and comparing resources and spending.
  • Competition: For monitoring competitors and market trends.

Fraud Detection

  • Data mining is also used in credit card services and telecommunication to detect fraud. In telecommunication fraud, it helps to find the destination, duration, and time of day or week of the phone call. It also analyzes when expected norms deviate.

Data Mining With Azure ML Studio

Data mining with Azure ML Studio Azure Machine Learning Studio has a large number of machine learning algorithms available, along with modules that help with data input, output, preparation, and visualization. Using these components, you can develop a predictive analytics experiments, iterate on them, and use them to train your model. This way, you can operate your model with just one click in the Azure cloud, so that it can be used to score new data.

Even though Data Mining is not a recent practice, its many advantages has made it essential for businesses. Azure ML allows users to very easily calculate and manipulate the data volumes from the cloud platform.

Due to data mining’s emphasis on finding repetitive patterns, it has become very diverse.  It assists in management and marketing analysis areas, as well as fraud detection. Today, data mining provides accurate predictive analysis related to important topics, since it can be complemented with an easy management tool like Azure ML.

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