Un año más, gran agenda y grandes ponentes en el Pentaho User Meeeting (PUM18) en Frankfurt: * Migrating from Business Objects to Pentaho (CERN, Gabriele Thiede) * Pentaho 8 (Pedro Alves) * Best Practices for Data Integration Architectures ( Matt Casters) * Operating Pentaho at Scale (Jens Bleuel) * Running Pentaho in Kubernetes (Nis Christian Carstensen,

Interesante:

Gracias a nuestros amigos de Carto [https://carto.com/]nos llega esta interesante recopilación de las principales tendencias en Visualización de Datos para 2018 1. Data visualization is not just for data scientists anymore. IBM projects a 39% increase in demand [https://www.ibm.com/analytics/us/en/technology/data-science/

Some new features of one of 'our favourites tools' in analytics that you can use it for Adhoc web reporting for end users with no licenses and professional support You can use it 'standalone', with some BI solutions like Pentaho ( check online Demo [http://pentaho.stratebi.

[http://udep.edu.pe/ingenieria/bigdata-machine-learning-business-intelligence/] Este interesante Curso [http://udep.edu.pe/ingenieria/bigdata-machine-learning-business-intelligence/] supone una de las primeras participaciones de la compañía especialista en Analytics, Stratebi [http://www.stratebi.com/]en Perú, en donde hay un gran interés en estas tecnologías y ya se están acometiendo algunos proyectos

Os recomendamos esta gran iniciativa, Dear Data [http://www.dear-data.com/], de Giorgia Lupi y Stefanie Posavec Se trata de un libro colaborativo en el envío de cartas que convierte a los imagenes en arte y elegancia. Muy recomendable!!

Hi, Pentaho Community fans, just available in Pentaho Marketplace [http://www.pentaho.com/marketplace/]in order to download STPivot4 Olap Viewer [http://www.stratebi.com/download-github], so you have compiled and ready-to-use STPivot4 [https://github.com/stratebi/STPivot4]is based on the old Pivot4J project where functionality has been added,

As Machine Learning tools become mainstream, and ever-growing choice of these is available to data scientists and analysts, the need to assess those best suited becomes challenging. In this study, 20 Machine Learning models were benchmarked for their accuracy and speed performance on a multi-core hardware, when applied to 2