Working with SAS(R) Data Loader for Hadoop

Course code: DL31HD

This course gives business analysts and data scientists a seamless platform to profile, integrate, cleanse, and move big data without writing code in a Hadoop environment using an intuitive web-based interface.

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Course dates

Starting date: Upon request

Type: E-learning

Course duration: 14 hours

Language: en

Price without VAT: 720 EUR


Starting date: Upon request

Type: Upon request

Course duration: 14 hours

Language: en

Price without VAT: 1 200 EUR


Type Course
Language Price without VAT
Upon request E-learning 14 hours en 720 EUR Register
Upon request Upon request 14 hours en 1 200 EUR Register
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Target group

Business users who interact with data, perform data discovery, query data, and ensure that data is in the proper place and format for other users; data analysts, data scientists, and statisticians who review results of data discovery activities, create new tables, create new data elements, change the format/structure of data tables to view them in a variety of ways, manipulate and score data elements, and load data for use by other users; and data management specialists who apply enterprise standards to the data, ensure data quality throughout the enterprise, move data into and out of the Hadoop cluster, and optimize code running in the Hadoop cluster

Course structure

Introduction to Big Data and Hadoop

  • big data and Hadoop
  • Hadoop ecosystem

SAS Data Loader Overview

  • SAS Data Loader capabilities and architecture
  • SAS Data Loader directives and tasks
  • steps common to most directives
  • preparing data for analysis and reporting
  • course overview and logistics

Acquiring and Discovering Data

  • introduction to acquiring and discovering data
  • copying a table into Hadoop
  • importing a delimited file into Hadoop
  • profiling data for inconsistencies
  • querying data for relevant columns and rows

Transforming and Transposing Data

  • introduction to transforming and transposing data
  • transforming data to be fit-for-purpose
  • transposing data for use in analysis and reporting

Cleansing Data

  • introduction to cleansing data
  • parsing data into meaningful subsets
  • standardizing data into consistent formats
  • using match codes to determine data similarity
  • using names to identify gender
  • analyzing data for data types
  • applying casing for data consistency
  • extracting data in useful tokens
  • analyzing data for inconsistent patterns

Integrating Data

  • introduction to integrating data
  • joining data in Hadoop
  • sorting and de-duplicating data
  • clustering and surviving data to determine a best record
  • matching and merging data into a single table
  • deleting rows in Hadoop tables
  • running user-written programs inside Hadoop

Delivering Data

  • introduction to delivering data from Hadoop
  • loading data to the SAS LASR Analytic Server for analysis and reporting
  • copying Hadoop data to SAS and relational database tables

Managing and Integrating Directives

  • introduction to managing and integrating directives
  • creating data flows by chaining directives
  • integrating directives into SAS platform applications
  • running directives as batch jobs

Additional Topics

  • SAS and Hadoop data processing
  • SAS DS2 programs
  • debugging Hadoop jobs


There are currently no prerequisites for this course.

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