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The Future of Data Mining – Predictive Analytics

The Future of Data Mining – Predictive Analytics. Unfulfilled Expectations. It overlaps with data profiling, data warehousing and even such approaches to data analysis as online analytic processing (OLAP) and enterprise analytic applications. Common Goals.

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The Future of Data Mining – Predictive Analytics

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  1. The Future of Data Mining – Predictive Analytics

  2. Unfulfilled Expectations • It overlaps with data profiling, data warehousing and even such approaches to data analysis as online analytic processing (OLAP) and enterprise analytic applications.

  3. Common Goals • All aim at understanding consumer behavior, forecasting product demand, managing and building the brand, tracking performance of customers or products in the market and driving incremental revenue from transforming data into information and information into knowledge. However, they cannot be substituted for one another.

  4. Technology Cycle • Data mining has endured significant consolidation of products since 2000

  5. Predictive Analytics Enabling Technologies

  6. Technology Hierarchy • Data mining is a process for knowledge discovery, primarily relying on generalizations of the "law of large numbers" and the principles of statistics applied to them.

  7. Methods • The method of data warehousing is structured query language (SQL) and its various extensions.

  8. Definition

  9.  Data Warehousing, Data Mining and Predictive Analytic Differentiators

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