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== Introduction ==
Intel Data Analytics Acceleration Library, also known as Intel DAAL, is a library created by Intel in 2015 to solve problems associated with Big Data.
Intel DAAL is available for Linux, OS X and Windows platforms and it is available for the C++, Python, and Java programming platforms.
* Online processing - Data is processed in chunks and then the partial results are combined during the finalizing stage. This is also called Streaming.
* Distributed processing - Similarly to MapReduce Consumers in a cluster process local data (map stage), and then the Producer process collects and combines partial results from Consumers (reduce stage). Developers can choose to use the data movement in a framework such as Hadoop or Spark, or explicitly coding communications using MPI.
== How Intel DAAL Works ==
Intel DAAL is a simple and efficient approach towards Big Data, Machine Learning, and Deep Learning because it takes away all the hustle of creating complex and efficient algorithms and all developers have to do is calling functions.
Intel DAAL provides many functions for Data Management, Algorithms, and Services.
[[File:https://software.intel.com/sites/products/documentation/doclib/daal/daal-user-and-reference-guides/daal_prog_guide/GUID-94AB71E1-77B3-4049-A195-B86EC1FD0053-low.png]]
== Sources ==
* [https://software.intel.com/en-us/intel-daal Intel's DAAL website]
* [https://software.intel.com/en-us/blogs/daal Intel's Blog Post about Intel DAAL]
* [https://software.intel.com/en-us/daal-programming-guide Intel DAAL Guide Book]
