Big Data Analyst
With the development of information technology, central and local governments, enterprises and institutions have begun to take notice of the management and utilization of data, giving rise to a shortage of talents in big data. To this end, Neusoft Education organizes special digital technology training for big data analysts, carefully designing course content for those who are interested in learning and engaging in big data analysis-related work. Students will obtain the "Big Data Analyst" special technical certificate after passing the exam.
This course is mainly divided into seven parts.
• The first part is an overview, which mainly introduces the main content of this course.
• The second part is the SQL language, which mainly introduces the use of various commonly used SQL statements to prepare for big data analysis.
• The third part is the basics of Java programming, which mainly introduces the basic syntax, object-oriented features of the Java language and common Java class libraries.
• The fourth part is the Hadoop ecosystem, which mainly introduces Hadoop-related big data technologies, including HDFS, HBase, MapReduce, Flume, and Sqoop, and focuses on the data warehouse technology Hive for data analysis.
• The fifth part is Spark technology, which is an enhancement of Hadoop-related technologies.
• The sixth part is data visualization, which introduces commonly used data visualization methods, including Excel-based data visualization and visualization using professional Tableau tools.
This course is mainly divided into seven parts.
• The first part is an overview, which mainly introduces the main content of this course.
• The second part is the SQL language, which mainly introduces the use of various commonly used SQL statements to prepare for big data analysis.
• The third part is the basics of Java programming, which mainly introduces the basic syntax, object-oriented features of the Java language and common Java class libraries.
• The fourth part is the Hadoop ecosystem, which mainly introduces Hadoop-related big data technologies, including HDFS, HBase, MapReduce, Flume, and Sqoop, and focuses on the data warehouse technology Hive for data analysis.
• The fifth part is Spark technology, which is an enhancement of Hadoop-related technologies.
• The sixth part is data visualization, which introduces commonly used data visualization methods, including Excel-based data visualization and visualization using professional Tableau tools.
• The seventh part uses website log analysis cases to deepen the understanding of various technologies.
Training Level
• Big Data Analyst (Junior)
• Big Data Analyst (Intermediate)
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