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According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase.
Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of datastorage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.
Data engineers must therefore have a thorough understanding of programming languages like Python, Java, or Scala. Candidates looking for Azure data engineering positions should also be familiar with bigdatatools like Hadoop. Automation : Automation is key for managing large datasets efficiently.
Basic knowledge of ML technologies and algorithms will enable you to collaborate with the engineering teams and the Data Scientists. It will also assist you in building more effective data pipelines. It then loads the transformed data in the database or other BI platforms for use. Hadoop, for instance, is open-source software.
Here are some role-specific skills you should consider to become an Azure data engineer- Most datastorage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Get familiar with popular ETLtools like Xplenty, Stitch, Alooma, etc.
Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on bigdata fundamentals, bigdatatools/technologies, and bigdata cloud computing platforms.
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