Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Highly Scalable

JANUARY 31, 2012

Several practical case studies are also provided. Applications: Log Analysis, Data Querying. It is required to save all items that have the same value of function into one file or perform some other computation that requires all such items to be processed as a group. This framework is depicted in the figure below.

C++ 144

C++ Network Ecommerce Processing 144

All Things Distributed

DECEMBER 8, 2016

It adopted Amazon Redshift, Amazon EMR and AWS Lambda to power its data warehouse, big data, and data science applications, supporting the development of product features at a fraction of the cost of competing solutions. For more customer case studies, see All AWS Customer Stories. Rapid time to market.

AWS 155

AWS Cloud Lambda Innovation 155

Highly Scalable

MARCH 10, 2015

Data mining offers a variety of techniques for nonparametric modeling that helps to create flexible and practical models. Many articles and case studies published during the last decade successfully achieve the balance between abstract models and machine learning. However, many of these models are highly parametric (i.e.

Retail 152

Retail C++ Analytics Metrics 152