%0 Journal Article %1 6648585 %A Louridas, P. %A Ebert, C. %D 2013 %J Software, IEEE %K development orchestration user.experience %N 6 %P 33-39 %R 10.1109/MS.2013.125 %T Embedded Analytics and Statistics for Big Data %U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6648585 %V 30 %X Embedded analytics and statistics for big data have emerged as an important topic across industries. As the volumes of data have increased, software engineers are called to support data analysis and applying some kind of statistics to them. This article provides an overview of tools and libraries for embedded data analytics and statistics, both stand-alone software packages and programming languages with statistical capabilities.

@article{6648585, abstract = {Embedded analytics and statistics for big data have emerged as an important topic across industries. As the volumes of data have increased, software engineers are called to support data analysis and applying some kind of statistics to them. This article provides an overview of tools and libraries for embedded data analytics and statistics, both stand-alone software packages and programming languages with statistical capabilities.}, added-at = {2015-01-05T16:14:07.000+0100}, author = {Louridas, P. and Ebert, C.}, biburl = {https://www.bibsonomy.org/bibtex/2726f5bb98debaa0737ffc8658401d9ed/ispma}, doi = {10.1109/MS.2013.125}, interhash = {cba022006c2cc19c7fe8a5a3a0d21d96}, intrahash = {726f5bb98debaa0737ffc8658401d9ed}, issn = {0740-7459}, journal = {Software, IEEE}, keywords = {development orchestration user.experience}, month = nov, number = 6, pages = {33-39}, timestamp = {2015-01-08T15:21:01.000+0100}, title = {Embedded Analytics and Statistics for Big Data}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6648585}, volume = 30, year = 2013 }