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SAS Institute Advanced Analytics Professional A00-226

Product Description

Exam Code:A00-226

Exam Name:SAS Text Analytics, Time Series, Experimentation, and Optimization

Q&A:60 Q&As

Updated: 05-05-2024

Number:

ExamGood SAS Institute A00-226 preparation material provides you everything you will need to take your A00-226 certification exam. Download the latest SAS Text Analytics, Time Series, Experimentation, and Optimization A00-226 certification exam from Examgood.com

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ExamGood A00-226 Exam Features

A00-226: SAS Text Analytics, Time Series, Experimentation, and Optimization

SAS Certified Specialist:

Text Analytics, Time Series, Experimentation and Optimization

For individuals who want to analyze big data with a variety of statistical analysis and predictive modeling techniques

Successful candidates should have experience in the following areas:

Text analytics

Experiment design for business

Optimization techniques

Time series forecasting

Exam Content & Pricing

This exam is administered by SAS and Pearson VUE.

50-55 multiple choice, short answer, and interactive questions.

Interactive questions simulate the SAS environment and ask you to complete a task.

110 minutes to complete exam (must achieve score of 68% correct to pass)

Use exam ID A00-226; required when registering with Pearson VUE

This exam is based on SAS 9.4

Successful candidates should have hands-on experience with a variety of SAS data preparation tools, including experience with the following analytical tools:

SAS Text Analytics

SAS/ETS

SAS/OR

SAS® Data Management - centralized console screenshot on monitor

Exam fee: $180 USD in the U.S

Exam Content Guide

Below we provide a list of the objectives that will be tested on the exam. For more specific details about each objective download the complete exam content guide.

Text Analytics - 30%

Create data sources for text mining

Import data into SAS Text Analytics

Use text mining to support forensic linguistics using stylometry techniques

Retrieve information for Analysis

Parse and quantify Text

Perform predictive modeling on text data

Use the High-Performance (HP) Text Miner Node

Time Series - 30%

Identify and define time series characteristics, components and the families of time series models

Diagnose, fit, and interpret ARIMAX Models

Diagnose, fit, and interpret Exponential Smoothing Models

Diagnose, fit, and interpret Unobserved Components Models

Experimentation & Incremental Response Models - 20%

Explain the role of experiments in answering business questions

Relate experimental design concepts and terminology to business concepts and terminology

Explain how incremental response models can identify cases that are most responsive to an action

Use the Incremental Response node in SAS Enterprise Miner

Optimization - 20%

Optimize linear programs

Optimize nonlinear programs

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