[MIT Digital Programs] BigDataFr recommends: Tackling the Challenges of Big Data #datascientist #machine learning #hadoop

 recommends: MIT’s Digital Program: Tackling the Challenges of Big Data’ New Session!  Tackling the Challenges of Big Data, running May 5th – June 16th « This Digital Programs course will survey state-of-the-art topics in Big Data, looking at data collection (smartphones, sensors, the Web), data storage and processing (scalable relational databases, Hadoop, Spark, etc.), extracting structured […]

[O’R] BigDataFr recommends: Squarring Big Data with Database Queries #datascientist #hadoop #spark

BigDataFr recommends: Squarring Big Data with Database Queries Integrating open source tools into a data warehouse has its advantages. Although next-gen big data tools such as Hadoop, Spark, and MongoDB are finding more and more uses, most organizations need to maintain data in traditional relational stores as well. Deriving the benefits of both key/value stores […]

[O’R] BigDataFR recommends: The O’Reilly Data Show Podcast – Michael Stack #hadoop #cloudera #datacientist

BigDataFR recommends: The O’Reilly Data Show Podcast – Michael Stack, engineer at Cloudera Michael Stack on HBase past, present, and future. Coming full circle with Bigtable and HBase « At least once a year, I sit down with Michael Stack, engineer at Cloudera, to get an update on Apache HBase and the annual user conference, HBasecon. […]

[SAS] #datascientist #hadoop BigDataFr recommends: 60 Second Scoop on SAS Data Loader for Hadoop

BigDataFr recommends: 60 Second Scoop on SAS Data Loader for Hadoop « SAS Data Loader for Hadoop tackles the Hadoop skills shortage and empowers business analyst and data scientist to prepare, integrate and cleanse big data faster and easier without writing code. » About SAS « SAS is the leader in business analytics software and services, and the […]

[After The Web] Big Data – les prédictions 2015 de Xavier Guérin, MapR

BigDataFr recommande : Big Data – les prédictions 2015 de Xavier Guérin, MapR ‘2015 sera l’année où les organisations poussent leurs déploiements Big Data au-delà des implémentations initiales de traitement par lots pour passer au temps réel. Cette évolution est le fruit des avancées considérables réalisées par les leaders de l’industrie, et par les leaders […]