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Big Data Aplicado E Inteligencia de Negocios Con Herramientas de Software.

Big Data Aplicado E Inteligencia de Negocios Con Herramientas de Software.


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About the Book

El libro comienza analizando herramientas de computación masiva en los ecosistemas de Big Data con especial atención a Hadoop, Mapreduce, Hadoop Distribute File System y Hadoop Common Components (Pig, Hive, Flume, Oozie, Hbase, Sqoop, Mahout y otras). A continuación se aborda la automatización de trabajos y se presentan ejemplos desarrollados con SQL Server. También se presenta el ecosistema Hadoop de Apache Ambari. Adicionalmente se presentan las herramientas de Big Data Analytics de SAS (SAS Access Interface to Hadoop, SAS Data Management, SAS Visual Analytics, SAS Visual Statistics, SAS In Memory Statistics for Hadoop, SAS High Performance Data Mining, SAS High Performance Text Mining, SAS VIYA, etc.) También se presentan las herramientas de Big Data Analytics de Oracle (Big Data Appliance, Big Data Connectors, NoSQL Database, Exadata, Business Analytics, etc.), Microsoft (HDInsight, Azure, etc.) e IBM (IBM Solution for Hadoop Power Systems Edition, BM AIX Solution Editions para Cognos y SPSS, IBM SPSS Modeler, etc.). A continuación se abordan la calidad e integridad de los datos en procesos de Big Data y el movimiento de datos entre clústers. Como ejemplo se desarrolla la copia y movimiento de bases de datos entre servidores en SQL Server. Más adelante se tratan las herramientas de monitorización de clústers HYPER-V, Hadoop y Ganglia, así como herramientas para interfaz web y otras. Finalmente se profundiza en las técnicas de Big Data e Inteligencia de Negocios. Se analizan las herramientas más importantes de Business Intelligence (Business Objects, MicroStrategy, Tableau, Power BI, Qlik, Domo, Pentaho, etc.) con especial atención a los cuadros de mando. Se describen las herramientas SAS Visual Analytics y herramientas de SAP para cuadros de mando. Por último, se describe la implementación del KDD (Knowledge Discovery in Data Bases) con herramientas de SAS (SAS Enterprise Miner) e IBM (IBM SPSS Modeler) a través de ejemplos.


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Product Details
  • ISBN-13: 9798353867739
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 302
  • Spine Width: 16 mm
  • Width: 178 mm
  • ISBN-10: 8353867737
  • Publisher Date: 20 Sep 2022
  • Binding: Paperback
  • Language: Spanish
  • Returnable: N
  • Weight: 580 gr


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