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Cloudera Certified Associate (CCA) Data Analyst

Certificate Only CERTIFICATION ONLY
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RM1,252.36(+RM75.14 Tax)
* Training Dates:

* Price excludes Exam

Overview

A CCA Data Analyst has proven their core analyst skills to load, transform, and model Hadoop data in order to define relationships and extract meaningful results from the raw input.

You are given eight to twelve customer problems with a unique large data set, a CDH cluster, and 120 minutes. For each problem, you must implement a technical solution with a high degree of precision that meets all the requirements. You may use any tool or combination of tools on the cluster (see list below) -- you get to pick the tool(s) that are right for the job. You must possess enough knowledge to analyze the problem and arrive at an optimal approach given the time allowed. You need to know what you should do and then do it on a live cluster, including a time limit and while being watched by a proctor.

  • Number of Questions: 8–12 performance-based (hands-on) tasks on CDH 5 cluster. See below for full cluster configuration

  • Time Limit: 120 minutes

  • Passing Score: 70%

  • Language: English

Audience Profile

Candidates for CCA Data Analyst can be SQL devlopers, data analysts, business intelligence specialists, developers, system architects, and database administrators. There are no prerequisites.

Prerequisities

Prepare the Data

Use Extract, Transfer, Load (ETL) processes to prepare data for queries.

  • Import data from a MySQL database into HDFS using Sqoop

  • Export data to a MySQL database from HDFS using Sqoop

  • Move data between tables in the metastore

  • Transform values, columns, or file formats of incoming data before analysis

Provide Structure to the Data

Use Data Definition Language (DDL) statements to create or alter structures in the metastore for use by Hive and Impala.

  • Create tables using a variety of data types, delimiters, and file formats

  • Create new tables using existing tables to define the schema

  • Improve query performance by creating partitioned tables in the metastore

  • Alter tables to modify existing schema

  • Create views in order to simplify queries

Data Analysis

Use Query Language (QL) statements in Hive and Impala to analyze data on the cluster.

  • Prepare reports using SELECT commands including unions and subqueries

  • Calculate aggregate statistics, such as sums and averages, during a query

  • Create queries against multiple data sources by using join commands

  • Transform the output format of queries by using built-in functions

  • Perform queries across a group of rows using windowing functions

Course Information
EXAM CODE
CCA-159
DURATION
0.5 Day
CERTIFICATION
Cloudera Certified Associate (CCA) Data Analyst
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