Talend Big Data v7
Certified Developer Exam

Talend certification exams are designed to be challenging to ensure that you have the skills to successfully implement quality projects. Preparation is critical to passing.

This certification exam covers Talend Big Data Basics, Talend Big Data Advanced – Spark Batch, and Talend Big Data Advanced – Spark Streaming learning plans. The emphasis is on the Talend Big Data architecture, Hadoop ecosystems, Spark, Kafka, and Kerberos.

Certification exam details

Exam content is updated periodically. The number and difficulty of questions may change. The passing score is adjusted to maintain a consistent standard.

Duration: 65 minutes
Number of questions: 65
Passing score: 70%

Recommended experience

  • At least six months of experience using Talend products
  • General knowledge of Hadoop (HDFS, MapReduce v2, Hive, HBase, Sqoop, YARN), Spark, Kafka, the Talend Big Data architecture, and Kerberos
  • Experience with Talend Big Data 7.x solutions and Talend Studio, including metadata creation, configuration, and troubleshooting


Preparation

To prepare for this certification exam, Talend recommends:

  • Taking the Big Data Basics, Big Data – Spark Batch, Big Data – Spark Streaming learning plans
  • Studying the training material in the Talend Big Data v7 Certified Developer preparation training module
  • Reading the product documentation and Community Knowledge Base article

For more information about the recommended Learning Plans, go to the Talend Academy Catalog.


Badge

After passing this certification exam, you are awarded the Talend Big Data Developer Certified badge. To know more about the criteria to earn this badge, refer to the Talend Academy Badging program page.


Certification exam topics

Big Data in context

  • Define Big Data
  • Understand the Hadoop ecosystem
  • Understand cloud storage architecture in a Big Data context

Read and write data (HDFS, cloud)

  • Understand HDFS
  • Use Studio components to import Big Data files to and export them from HDFS
  • Use Studio components to import Big Data files to and export them from the cloud

Sqoop

  • Understand Sqoop principles and usage
  • Create database metadata for Sqoop
  • Use Studio components to import tables to HDFS with Sqoop

Standard, batch, and streaming Jobs

  • Understand the differences between standard, batch, and streaming Jobs
  • Know when to use a standard, batch, or streaming Job
  • Migrate Jobs

Spark

  • Understand Spark principles and usage
  • Set up Spark batch Jobs
  • Set up Spark Streaming Jobs
  • Troubleshoot Spark Jobs
  • Optimize Spark Jobs at runtime

Kafka

  • Understand Kafka principles and usage
  • Use Studio components to produce data in a Kafka topic
  • Use Studio components to consume data from a Kafka topic

Setting up a Big Data environment

  • Talend architecture and Big Data
  • Kerberos and security

Basic concepts

  • Define Talend metadata stored in the repository
  • Understand the main elements of Hadoop cluster metadata
  • Create Hadoop cluster metadata
  • Create additional metadata (Hadoop Distributed File System, HDFS; YARN, Hive)

HBase

  • Understand HBase principles and usage
  • Use Studio components to connect to HBase
  • Use Studio components to export data to an HBase table

Hive

  • Understand Hive principles and usage
  • Create database metadata for Hive
  • Use Studio components to import data to a Hive table

Hadoop

  • Use Studio components to process data stored in a Hive table
  • Analyze Hive tables in the Profiling perspective
  • Understand MapReduce Jobs in Studio
  • Create a Big Data batch MapReduce Job to process data in HDFS

YARN

  • Understand YARN principles and usage
  • Tune YARN
  • Monitor Job execution with web UIs
  • Use Studio to configure resource requests to YARN

Big Data Streaming Jobs

  • Understand Big Data Streaming Jobs in Studio
  • Tune Streaming Jobs

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