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Big Data Analytics

Big Data Analytics for Data Engineers

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  • Overview

    This is an intensive, hands-on introduction to Data Engineering as it relates to Big Data applications. Participants will leverage numerous programming languages to gain hands-on experience with toolsets required in Big Data applications.

  • Who Should Take This Course

    PREREQUISITES

    Students should have a strong understanding of programming languages and a basic proficiency in Python as well as strong analytical and problem-solving skills.

  • Schedule
  • Course Outline
    • Prerequisites
    • Definition of Data Engineering
    • ETL
    • AWS
      • S3
      • SNS/SQS
      • Kinesis
      • EMR
      • ElastiCache
      • Redshift
    • Hadoop
      • MapReduce and HDFS
    • Apache Spark
    • Apache Kafka
    • Apache Flume
    • Apache Nifi
    • Streamsets
    • Cassandra
    • Elasticsearch
    • SMACK Stack vs. LAMP
    • File storage
      • .csv, tsv
      • .json, .xml
      • Sequence files
      • Avro
      • Parquet

    Labs

    Hands-on activities will include the use of an AWS private cluster utilizing Scala, Java, and
    Python as supporting coding languages. Large, public data sources will be used for all Big
    Data labs.

  • FAQs
    Is there a discount available for current students?

    UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Online courses are excluded from this offer.

    What is the cancellation and refund policy?

    Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.

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