Bo0mB0oma Posted March 29, 2019 Report Share Posted March 29, 2019 Big Data, Hadoop & Apache Spark: Analytics, Pig & MapReduce MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 4.5 Hours | Lec: 40 | 563 MB Genre: eLearning | Language: English Big Data Databases Analytics With Hadoop & Apache Spark: Programming, Pig, MySQL & MapReduce For Developers Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. There are five dimensions to big data known as Volume, Variety, Velocity and the recently added Veracity and Value. Analysis of data sets can find new correlations to spot business trends, prevent diseases, combat crime and so on, but if you don't master business intelligence, you will miss the opportunity to give value to businesses. What if you could change that? My complete Big Data course will show you the exact techniques and strategies you need to design systems that manage big data, create scripts to process data, frame big data analysis problems and develop codes in Scala. You will get over 4 hours of video lectures and the freedom to ask me any questions regarding the course as you go through it. :) What Is In This Course? Your Big Data Skills Will Be Much Easier. Except if you're an expert at Big Data, reutilizing of the Hadoop framework comfortably, nesting big data using map reduce, configure Pig analysis based on NoSQL schema, do development of big data analysis codes, analyze relational data and perform Big data MapReduce operations on web application, you are going to lose many job/career opportunities or even miss working with big data. As what Atul Butte, a biotechnology entrepreneur in Silicon Valley, says "Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world." You can try it with no financial risk. In This Big Data Training, You'll Learn: Design distributed systems of Big data Reutilizing of the Hadoop framework comfortably Relational development based on SQL performances Hadoop analytical applications system design Creating Hadoop analytical queries'(HDFS) Nesting big data using map reduce Managing clustering of data using sparks comfortably(YARN) learn how to create the running query to ensure flow part of the equation Configuring Pig analysis based on NoSQL schema Creating, dropping and Understanding Hadoop big data databases Constructing analytical Ooze Hadoop queries (Oozie) Arithmetic concept of designing MapReduce analysis using different tool Development of big data analysis codes Schematic archiving Big data systems (streaming) Analysis relational data Hadoop software connectivity and compatibility to the system(pigs) Analytical Hadoop system interface feature design (social networks) Publication of big data to your Hadoop cluster applications Performing Big data MapReduce operations on web application Algorithms website structures DOWNLOAD (Buy premium account for maximum speed and resuming ability) http://nitroflare.com/view/29A4707735CE442/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part1.rar http://nitroflare.com/view/98A75A041A96651/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part2.rar http://nitroflare.com/view/E6C82AB9C4700B3/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part3.rar https://rapidgator.net/file/8e7bdb80e1c11e3f7bdedf70ef2b8ffc/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part1.rar https://rapidgator.net/file/85cb4f5ab8af8697edce15c578a9e49b/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part2.rar https://rapidgator.net/file/7b28bfad881ed11b7a62aa8a0b8f6d56/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part3.rar http://turbobit.net/xxookl4xjjm7/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part1.rar.html http://turbobit.net/rkcv4f3uvg4q/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part2.rar.html http://turbobit.net/xafhx6va098n/01a61.Big.Data.Hadoop..Apache.Spark.Analytics.Pig..MapReduce.part3.rar.html Link to comment Share on other sites More sharing options...
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