SAS(R) Data Management Tools and Applications

Course code: DISDS2

This is the second course in the Data Curation Professional, SAS Academy for Data Science program. The program is required to earn your SAS data science certification. Designed for SAS data scientists, this program covers SAS topics for data curation techniques, including big data preparation with Hadoop. In this course, you discover how to access your data from a variety of sources, create processes to manage and transform data, and ensure the reliability and consistency of your data.
1 800 EUR

2 178 EUR including VAT

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Starting date: Upon request

Type: Upon request

Course duration: 21 hours

Language: en

Price without VAT: 1 800 EUR


Type Course
Language Price without VAT
Upon request Upon request 21 hours en 1 800 EUR Register
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Course structure

SAS/ACCESS Technology Overview

  • SAS/ACCESS technology overview.

SAS Data Integration Studio: Essentials

  • Exploring the SAS platform and SAS Data Integration Studio.
  • Exploring SAS Data Integration Studio basics.
  • Examining SAS Data Integration Studio jobs and options.

SAS Data Integration Studio: Defining Source Data Metadata

  • Setting up the environment.
  • Defining metadata for a library.
  • Registering metadata for data sources.
  • Registering SAS table metadata.
  • Registering DBMS table metadata.
  • Registering ODBC data source table metadata.
  • Registering metadata for external files.

SAS Data Integration Studio: Defining Target Data Metadata

  • Registering metadata for target tables.
  • Importing metadata.

SAS Data Integration Studio: Working with Jobs

  • Creating metadata for jobs.
  • Working with the Join transformation.

SAS Data Integration Studio: Working with Transformations

  • Working with the Extract and Summary Statistics transformations.
  • Exploring the SQL transformations.
  • Creating custom transformations.

Introduction to Data Quality and the SAS Quality Knowledge Base

  • Introduction to data quality.
  • SAS Quality Knowledge Base overview.

DataFlux Data Management Studio: Essentials

  • Overview of Data Management Studio.
  • DataFlux Repositories.
  • Quality Knowledge Bases and reference data sources.
  • Data connections.

DataFlux Data Management Studio: Understanding Data

  • Methodology review.
  • Creating data collections.
  • Designing data explorations.
  • Creating data profiles.
  • Profiling other input types.
  • Designing data standardization schemes.

DataFlux Data Management Studio: Building Data Jobs to Improve Data

  • Introduction to data jobs.
  • Standardization, parsing, and casing.
  • Identification analysis and right fielding.
  • Branching and gender analysis.
  • Data enrichment.

DataFlux Data Management Studio: Building Data Jobs for Entity Resolution

  • Creating match codes.
  • Clustering records.
  • Survivorship.

Understanding the SAS Quality Knowledge Base (QKB)

  • Working with QKB component files.
  • Working with QKB definitions.

Using SAS Code to Access QKB Components

  • SAS configuration options for accessing the QKB.
  • SAS Data Quality Server overview.


Before attending this course, you should have:
  • Experience with SAS programming basics and data manipulation techniques.
  • Familiarity with SQL processing.
  • Do you need advice or a tailor-made course?


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