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This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to run Unzip the zip file Windows : java -cp .\lib\*;osdq-spark-0.0.1.jar org.arrah.framework.spark.run.TransformRunner -c .\example\samplerun.json Mac UNIX java -cp ./lib/*:./osdq-spark-0.0.1.jar org.arrah.framework.spark.run.TransformRunner -c ./example/samplerun.json For those on windows, you need to have hadoop distribtion unzipped on local drive and HADOOP_HOME set. ...

(Beta Version) This is sister project for https://sourceforge.net/projects/dataquality/ . It provides Restful APIs for features for data quality and data preparation features. This project will help projects which want embed data quality and data preparation features in their project or UI using restful calls. Data Cleansing APIs Dockerfile: # Pull base image FROM frnde/jetty-9.4.2-jre8-alpine-cet ADD osdq-v0.0.1.war /var/lib/jetty/webapps/osdq.war EXPOSE 8080 Docker...

...This enables it to: * be very flexible * be truly multi-platform * draw from all the features available to the language and its sprawling ecosystem * partake in that ecosystem as a library. It has a strong focus on ease of use and low maintenance. Anyone should be able to get started with minimal outside(consultants) help and quickly get the system working. Note : Its sibling projects, QAL (https://sf.net/p/qal)

Student tracking modules based on Liferay Portal and Pentaho BI tools to get a educational system oriented to do a more useful analysis of student marks than actual student tracking plattforms seems to perform.