SAS Certified Big Data Professional Using SAS 9 Practice Exam

The SAS Certified Big Data Professional Using SAS 9 certification is suitable for SAS professionals who want to certify their skills and knowledge in managing and analyzing big data using SAS software. The  SAS certification assess your skills in data preparation, exploration, and how you apply analytical techniques for getting insights from large and complex datasets. The certification includes concepts related to big data technologies, data manipulation, and the use of SAS tools for data analysis. The certification attests to your skills to use data effectively to drive business decisions especially for professionals working in data analytics, data science, and related domains.
Why is SAS Certified Big Data Professional Using SAS 9 important?

• Validates expertise in managing and analyzing big data using SAS software.
• Enhances career opportunities in data analytics, data science, and related fields.
• Demonstrates proficiency in data preparation, exploration, and analysis techniques.
• Provides recognition of skills in using SAS tools for big data analytics.
• Supports organizations in identifying qualified professionals to handle big data projects.

Who should take the SAS Certified Big Data Professional Using SAS 9 Exam?

• Data Scientist
• Data Analyst
• Business Intelligence Analyst
• Big Data Engineer
• Analytics Consultant
• Data Engineer

Skills Evaluated

Candidates taking the certification exam on the SAS Certified Big Data Professional Using SAS 9 is evaluated for the following skills:

• Proficiency in data manipulation and preparation for analysis.
• Knowledge of big data technologies and concepts.
• Ability to explore and visualize large datasets.
• Skills in applying statistical and analytical techniques to derive insights.
• Familiarity with using SAS software tools for big data analysis.

SAS Certified Big Data Professional Using SAS 9 Certification Course Outline
The SAS Certified Big Data Professional Using SAS 9 Certification covers the following topics -

SAS Big Data Preparation, Statistics, and Visual Exploration Exam

Module 1. Data Management -

• Navigate within the Data Management Studio Interface

• Create, design and be able to explore data explorations and interpret results

• Define and create data collections from exploration results

• Apply a Standardization definition and scheme

• Apply Parsing definitions

• Compare and contrast the differences between identification analysis and right fielding nodes

• Apply the Gender Analysis node to determine gender

• Create an Entity Resolution Job

• Define and create business rules

Module 2. ANOVA and Regression

• Verify the assumptions of ANOVA

• Analyze differences between population means using the GLM and TTEST procedures

• Fit a multiple linear regression model using the REG and GLM procedures

• Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models

• Use the REG or GLMSELECT procedure to perform model selection

• Assess the validity of a given regression model through the use of diagnostic and residual analysis

• Optimize model performance through input selection

• Interpret the output of the LOGISTIC procedure

Module 3. Visual Data Exploration

• Examine, modify, and create data items

• Select and work with data sources

• Create, modify, and interpret automatic chart visualizations in Visual Analytics Explorer

• Create, modify, and interpret graph and table visualizations in Visual Analytics Explorer

• Enhance visualizations with analytics within Visual Analytics Explorer

• Interact with visualizations and explorations within Visual Analytics Explorer

SAS Big Data Programming and Loading Exam

Module 1. SAS and Hadoop -

• Describe the baseline requirements for interacting with Hadoop

• Use the HADOOP procedure and the Hadoop FILENAME statement to interact with Hadoop from a SAS session

• Query and manage Hive tables stored in Hadoop using explicit SQL pass-through

• Work with Hadoop files using the SAS/ACCESS LIBNAME statement

Module 2. SAS DS2 Programming

• Write DS2 programs

• Read data using DS2

• Work with variables, arrays, and ANSI SQL data types

• Use expressions and functions in DS2 programs

• Work with Methods, Packages, and Threads

Module 3. Hadoop Programming

• Describe the Hadoop architecture

• Manipulate and load data files using command-line tools

• Write Hive programs to create, join, and query data tables

• Write Pig programs to perform ETL tasks and to analyze large data sets

Module 4. Data manipulation with the IMSTAT procedure

• Execute IMSTAT procedures

• Perform actions required to produce graphs with PROC IMSTAT

• Manipulate In-Memory Data

• Use High-Performance procedures with the SAS LASR Analytic Server