SAS Finance Data Analyst Course in Ahmedabad

Track	Week Days	Weekends
Course Duration	144 Hrs	144 Hrs
Hours	1 Hrs Per Day	2 Hrs per Day
Training Mode	Live Web/Classroom	Live Web/Classroom

learn how to write SAS programs to access, explore, prepare, and analyze data. It is the entry point to learning SAS programming for data science, machine learning, and artificial intelligence. It is mapped to SAS Certified Specialist: Base Programming Using SAS 9.4 Credential.

This course covers the content of both SAS Data Integration Studio: Essentials and SAS Data Integration Studio: Additional Topics.

It introduces and expands the knowledge of SAS Data Integration Studio and includes topics for registering sources and targets; creating and working with jobs, and working with transformations.

This course also covers information on working with slowly changing dimensions, working with the Loop transformations, and defining new transformations. Targeted towards Data integration developers and data integration architects

This course focuses on statistical analysis. Ready-to-use procedures handle a wide range of statistical techniques including simple descriptive statistics, data visualization, analysis of variance, regression, categorical data analysis, multivariate analysis, cluster analysis, and non-parametric analysis

It covers a range of introductory statistical topics and uses SAS Software to carry out an analysis. Emphasis will be placed on the interpretation of the results.

This course covers the skills required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models). SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 credential.

This course is designed for SAS Enterprise Guide users who want to perform statistical analysis.

Generate descriptive statistics and data exploration in graphs; perform linear regression techniques, using diagnostic statistics to identify multiple regressions.

Beneficial to statisticians and business analysts who want to interface with SAS.

These courses use the SAS Enterprise Miner toolset to perform the essentials of data analytics such as graphically exploring data, modifying data for better results in data analytics, building future models such as decision trees, regression, and neural network models, and to understand, as well as applying association and sequence searches to transactional data.

This course provides an introduction & advanced features of data preparation, data discovery, analytics, and report creation in SAS Visual Analytics.

Using SAS Visual Analytics you will learn the following: Accessing and examining data, searching and analyzing data, creating interactive reports, geographic analysis, forecasting, network analysis, path analysis, reconstructing data by text analysis, data filtering in advanced data, etc.

This course can help prepare you for the following certification exam(s): SAS Certified Specialist: Visual Business Analytics 7.5/8.3 credential

This course introduces data and risk analysts to Tasks used in the monthly production cycle

The course includes hands-on demonstrations and teaches you key concepts, terminology, and base functionality that are integral to SAS Solution for IFRS 9. Get an overview of concepts in risk, IFRS9 & IFRS17 & applications of SAS solutions in the same.

Key features of SAS Solutions for RISK and IFRS are Modeling & analytics, Modeling, and analytics, Unified workflows frameworks, and reporting, financial aggregation, etc.

The SAS Financial Data Analyst Certification Course digital badge represents your skills and expertise online and allows sharing in real-time for easy verification. You can easily share this digital badge on various social media platforms like LinkedIn, Facebook and Twitter

SAS Financial Data Analyst Course helps you to prepare the following SAS Credentials:

SAS Certified Specialist: Base Programming Using SAS 9.4

The fees is inclusive of Instructor Based Training, Course material (PDF) & One attempt of Global Certification worth 180$ for -

1. SAS Certified Specialist: Base Programming Using SAS 9.4 (Exam id A00-231)

2. SAS Certified Specialist: SAS Visual Analytics using SAS Viya (Exam ID A00-470)

3. SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 (Exam ID A00-255)

Certification attempt needs to be taken within 3 months of course completion.

Financial is the largest top 10 sector in the world. As it has a market share of 13.9%. A number of companies involved in data analytics have been observed.

India's Fintech market is the third largest in the world. Many Fintech organizations like PhonePe, Paytm, Policybazaar, kissht, PayU, Razorpay, Billdesk and MobiKwik have used data analytics and AI to grow their business.

The field of data analysis is economically very beneficial for the growth of the sector and it is used in various fields. Some companies working on financial analytics report that non-IT sectors in India have huge potential for engineers with SAS Data Analytics Certification.

In the future, there will be good career opportunities in the field of Data Analytics. Anyone who enjoys working with statistics has logical reasoning, can understand data and turn it into action, and will have a bright future in this Data Analytics Industry.

Before starting a career in the SAS Finance Data Analytics, it is necessary to have a thorough understanding of SAS tools and technologies. The course also requires work to study and earn SAS certification.

You may know that a Finance Data Analysis Engineer in India as well as in other countries can expect to earn an average of Rs 10 Lakh or more per annum

As you gain experience in an organization, your compensation will increase. Rs. Salary up to 15 lakhs is not uncommon for SAS Financial Data Analytics Engineers with more than five years of experience. A senior data analyst with more than ten years of experience might expect more than INR 20 lakhs.

You can check the SAS Finance Data Analyst Salary statistics page mentioned by Glassdoor, Ambition box, and Payscale and choose the course you want to study to get a SAS Financial Data Analyst Salary in India.

So what are you waiting for? Enroll today at Aspire Techsoft Academy the Best Finance Data Analyst Training Institute in Ahmedabad with 100% Placement Assistance. Not sure you're ready? Enroll in SAS certification Guidance here from our SAS Experts to enhance your skills.

Interpret data, analyze results using statistical techniques and provide ongoing reports

Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.

Identify, analyze, and interpret trends or patterns in complex data sets.

Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems.

Extracting the data from various sources & preparation of reports.

Work with management to prioritize business and information needs, Locate and define new process improvement opportunities.

SAS Data Analyst works on developing or maintaining SAS programs using Base SAS Macros and SQL.

Developed database in projects with large, diverse, client data source files.

Collecting Data Sets from Primary and Secondary Sources.

Cleaning and Organizing Data.

Preparing Data for Analysis.

Creating Reports with Clear Visualizations

Designing and Maintaining Databases and Data Systems

SAS Financial Data Analyst

Financial Analyst – Analytics & Reporting

Health Care Financial Analyst

Finance Manager

Team Lead, Operations

Data Analyst (Statistician)

SAS Data Engineer

Lead Fraud/Risk Analyst

SAS Credit Risk Analyst

Senior Analyst – Risk Management

Lead Business Analys

Course Title	Days	Mode	Date	Time
Base SAS (Week-end) / Clinical SAS	Sat-Sun	Instructor-led Live	4-5, 11-12 & 18 May	9am-2pm
19, 25-26 May & 1-2 June	9am-2pm

SAS Certification Training

Download Curriculum

▪ the SAS programming process

▪ using SAS programming tools

▪ understanding SAS syntax

▪ understanding SAS data

▪ accessing data through libraries

▪ importing data into SAS

▪ exploring data

▪ filtering rows

▪ formatting columns

▪ sorting data and removing duplicates

▪ reading and filtering data

▪ computing new columns

▪ conditional processing

▪ enhancing reports with titles, footnotes, and labels

▪ creating frequency reports

▪ creating summary statistics reports

▪ exporting data

▪ exporting reports

▪ using Structured Query Language in SAS

▪ joining tables using SQL in SAS

▪ setting up for this course

▪ understanding DATA step processing

▪ directing DATA step output

▪ creating an accumulating column

▪ processing data in groups

▪ understanding SAS functions and CALL routines

▪ using numeric and date functions

▪ using character functions

▪ using special functions to convert column type

▪ creating and using custom formats

▪ creating custom formats from tables

▪ concatenating tables

▪ merging tables

▪ identifying matching and nonmatching rows

▪ using iterative DO loops

▪ using conditional DO loops

▪ restructuring data with the DATA step

▪ restructuring data with the TRANSPOSE procedure

▪ Discussing fundamental statistical concepts.

▪ Examining distributions.

▪ Describing categorical data.

▪ Constructing confidence intervals

▪ Performing simple tests of hypothesis.

▪ Performing one-way ANOVA.

▪ Performing multiple comparisons.

▪ Performing two-way ANOVA with and without interactions

▪ Using exploratory data analysis.

▪ Producing correlations.

▪ Fitting a simple linear regression model.

▪ Understanding the concepts of multiple regression.

▪ Building and interpreting models

▪ Describing all regression techniques

▪ Exploring stepwise selection techniques.

▪ Examining residuals

▪ Investigating influential observations and collinearity

▪ Describing categorical data.

▪ Examining tests for general and linear association.

▪ Understanding the concepts of logistic regression and multiple logistic regression.

▪ Performing backward elimination with logistic regression

▪ Introduction to SAS Enterprise Miner.

▪ Creating a SAS Enterprise Miner project, library, and diagram.

▪ Defining a data source.

▪ Exploring a data source.

▪ Introduction.

▪ Cultivating decision trees.

▪ Optimizing the complexity of decision trees.

▪ Understanding additional diagnostic tools (self-study).

▪ Autonomous tree growth options (self-study).

▪ Selecting regression inputs.

▪ Optimizing regression complexity.

▪ Interpreting regression models.

▪ Transforming inputs.

▪ Categorical inputs

▪ Polynomial regressions (self-study).

▪ Input selection.

▪ Stopped training.

▪ Other modeling tools (self-study).

▪ Model fit statistics.

▪ Statistical graphics.

▪ Model fit statistics.

▪ Adjusting for separate sampling.

▪ Profit matrices.

▪ Internally scored data sets.

▪ Score code modules.

▪ Cluster analysis.

▪ Market basket analysis (self-study).

▪ Ensemble models

▪ Variable selection.

▪ Categorical input consolidation.

▪ Surrogate models.

▪ SAS Rapid Predictive Modeler..

▪ Banking segmentation case study.

▪ Website usage associations case study.

▪ Credit risk case study.

▪ Enrollment management case study..

▪ Introduction to SAS Visual Analytics.

▪ Exploring the SAS Visual Analytics course environment..

▪ Viewing SAS Visual Analytics reports..

▪ Investigating data in SAS Visual Analytics.

▪ Transforming data using Data Studio.

▪ Working with data items.

▪ Exploring data with charts and graphs.

▪ Creating data items and applying filters.

▪ Performing data analysis (relationship charts).

▪ Creating a simple report.

▪ Creating interactive reports.

▪ Working with display rules.

▪ Overview of SAS Visual Analytics.

▪ Automated explanation.

▪ Introduction to SAS Data Studio.

▪ Restructuring data.

▪ Analyzing geographic information.

▪ Restructuring data.

▪ Forecasting.

▪ Restructuring data for network analysis.

▪ Creating a network analysis object..

▪ Creating calculated items.

▪ Creating aggregated measures.

▪ Creating advanced filters.

▪ Creating advanced interactive filters.

▪ Using numeric parameters.

▪ Using character parameters.

▪ Using date parameters.

▪ Risk defined.

▪ Types of Risk.

▪ Regulatory Bodies in Risk.

▪ Basel Accords.

▪ IFRS9.

▪ IFRS17.

▪ SAS for Credit and Market Risk

▪ SAS for Operational Risk.

▪ SAS for IFRS9.

▪ SAS for IFRS17.

▪ Solution Components

▪ SAS process for IFRS9.

▪ SAS Outcomes and Disclosure reports.

▪ Solution Components

▪ SAS process for IFRS17.

▪ SAS Outcomes and Disclosure reports.

Take a SAS training to sharpen your skills.

Key Benefits of SAS for Banking and Financial Analytics Course from Aspire Techsoft Academy

SAS Certified Trainers with Live Web Training Center (Demonstrate your true SAS skills and understanding.)

Hands on learning(Learn SAS Financial Data Analyst Course in Ahmedabad with a SAS Certified expert instructor in a traditional classroom setting for an in-depth, hands-on learning experience.)

SAS free Learning resources for 30 days(Get started with free certification prep materials.)

Receive ongoing support and be a part of a community.

Software Access(A secure, electronic verification of your achievement.)

Earn Digital Badge (A secure, electronic verification of your achievement.)

SAS Global Certification Credentials(Earn your SAS Financial Data analyst Certification credentials and be recognized across all industries and geographic locations.)

Allow employers to easily discover you.

You are trying to stand out from crowd? Stop telling; showcase your skills with SAS Digital Badge!

Provide labor market insights that connect your new skills to jobs.

Enable recruiters to view and verify candidates with certain SAS skills.

It will answer what you did? Who says you did it? And why it matters? These questions for you.

BASE SAS Programmer Certification Training

Download Curriculum

▪ the SAS programming process

▪ using SAS programming tools

▪ understanding SAS syntax

▪ understanding SAS data

▪ accessing data through libraries

▪ importing data into SAS

▪ exploring data

▪ filtering rows

▪ formatting columns

▪ sorting data and removing duplicates

▪ reading and filtering data

▪ computing new columns

▪ conditional processing

▪ enhancing reports with titles, footnotes, and labels

▪ creating frequency reports

▪ creating summary statistics reports

▪ exporting data

▪ exporting reports

▪ using Structured Query Language in SAS

▪ joining tables using SQL in SAS

▪ setting up for this course

▪ understanding DATA step processing

▪ directing DATA step output

▪ creating an accumulating column

▪ processing data in groups

▪ understanding SAS functions and CALL routines

▪ using numeric and date functions

▪ using character functions

▪ using special functions to convert column type

▪ creating and using custom formats

▪ creating custom formats from tables

▪ concatenating tables

▪ merging tables

▪ identifying matching and nonmatching rows

▪ using iterative DO loops

▪ using conditional DO loops

▪ restructuring data with the DATA step

▪ restructuring data with the TRANSPOSE procedure

▪ Discussing fundamental statistical concepts.

▪ Examining distributions.

▪ Describing categorical data.

▪ Constructing confidence intervals

▪ Performing simple tests of hypothesis.

▪ Performing one-way ANOVA.

▪ Performing multiple comparisons.

▪ Performing two-way ANOVA with and without interactions

▪ Using exploratory data analysis.

▪ Producing correlations.

▪ Fitting a simple linear regression model.

▪ Understanding the concepts of multiple regression.

▪ Building and interpreting models

▪ Describing all regression techniques

▪ Exploring stepwise selection techniques.

▪ Examining residuals

▪ Investigating influential observations and collinearity

▪ Describing categorical data.

▪ Examining tests for general and linear association.

▪ Understanding the concepts of logistic regression and multiple logistic regression.

▪ Performing backward elimination with logistic regression

▪ Introduction to SAS Enterprise Miner.

▪ Creating a SAS Enterprise Miner project, library, and diagram.

▪ Defining a data source.

▪ Exploring a data source.

▪ Introduction.

▪ Cultivating decision trees.

▪ Optimizing the complexity of decision trees.

▪ Understanding additional diagnostic tools (self-study).

▪ Autonomous tree growth options (self-study).

▪ Selecting regression inputs.

▪ Optimizing regression complexity.

▪ Interpreting regression models.

▪ Transforming inputs.

▪ Categorical inputs

▪ Polynomial regressions (self-study).

▪ Input selection.

▪ Stopped training.

▪ Other modeling tools (self-study).

▪ Model fit statistics.

▪ Statistical graphics.

▪ Model fit statistics.

▪ Adjusting for separate sampling.

▪ Profit matrices.

▪ Internally scored data sets.

▪ Score code modules.

▪ Cluster analysis.

▪ Market basket analysis (self-study).

▪ Ensemble models

▪ Variable selection.

▪ Categorical input consolidation.

▪ Surrogate models.

▪ SAS Rapid Predictive Modeler..

▪ Banking segmentation case study.

▪ Website usage associations case study.

▪ Credit risk case study.

▪ Enrollment management case study..

▪ Introduction to SAS Visual Analytics.

▪ Exploring the SAS Visual Analytics course environment..

▪ Viewing SAS Visual Analytics reports..

▪ Investigating data in SAS Visual Analytics.

▪ Transforming data using Data Studio.

▪ Working with data items.

▪ Exploring data with charts and graphs.

▪ Creating data items and applying filters.

▪ Performing data analysis (relationship charts).

▪ Creating a simple report.

▪ Creating interactive reports.

▪ Working with display rules.

▪ Overview of SAS Visual Analytics.

▪ Automated explanation.

▪ Introduction to SAS Data Studio.

▪ Restructuring data.

▪ Analyzing geographic information.

▪ Restructuring data.

▪ Forecasting.

▪ Restructuring data for network analysis.

▪ Creating a network analysis object..

▪ Creating calculated items.

▪ Creating aggregated measures.

▪ Creating advanced filters.

▪ Creating advanced interactive filters.

▪ Using numeric parameters.

▪ Using character parameters.

▪ Using date parameters.

▪ Risk defined.

▪ Types of Risk.

▪ Regulatory Bodies in Risk.

▪ Basel Accords.

▪ IFRS9.

▪ IFRS17.

▪ SAS for Credit and Market Risk

▪ SAS for Operational Risk.

▪ SAS for IFRS9.

▪ SAS for IFRS17.

▪ Solution Components

▪ SAS process for IFRS9.

▪ SAS Outcomes and Disclosure reports.

▪ Solution Components

▪ SAS process for IFRS17.

▪ SAS Outcomes and Disclosure reports.

Take a SAS training to sharpen your skills.

Key Benefits of SAS for Banking and Financial Analytics Course from Aspire Techsoft Academy

SAS Certified Trainers with Live Web Training Center (Demonstrate your true SAS skills and understanding.)

Hands on learning(Learn SAS Financial Data Analyst Course in Ahmedabad with a SAS Certified expert instructor in a traditional classroom setting for an in-depth, hands-on learning experience.)

SAS free Learning resources for 30 days(Get started with free certification prep materials.)

Receive ongoing support and be a part of a community.

Software Access(A secure, electronic verification of your achievement.)

Earn Digital Badge (A secure, electronic verification of your achievement.)

SAS Global Certification Credentials(Earn your SAS Financial Data analyst Certification credentials and be recognized across all industries and geographic locations.)

Allow employers to easily discover you.

You are trying to stand out from crowd? Stop telling; showcase your skills with SAS Digital Badge!

Provide labor market insights that connect your new skills to jobs.

Enable recruiters to view and verify candidates with certain SAS skills.

It will answer what you did? Who says you did it? And why it matters? These questions for you.

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SAS Financial Data Analyst Course in Ahmedabad

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About SAS Financial Data Analyst certification Course

SAS Financial Data Analyst Certification

SAS Financial Data Analyst Certification

Validate your skills with a SAS Advance Certification

SAS Credential: SAS Financial Data Analyst

SAS Certification Course Curriculum

Key Benefits of SAS for Banking and Financial Analytics Course from Aspire Techsoft Academy

Key Benefits of SAS for Banking and Financial Analytics Course from Aspire Techsoft Academy

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SAS Financial Data Analyst Course in Ahmedabad

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About SAS Financial Data Analyst certification Course

Why Choose SAS for Banking Analytics?

Why Choose SAS for Banking Analytics?

SAS Financial Data Analyst Certification

SAS Financial Data Analyst Certification

Prerequisites for SAS Financial Data Analyst Course

Who can Learn SAS Financial Data Analyst Certification Course

SAS Financial Data Analyst Certification Course: Training Mode

Online Training:

SAS Financial Data Analyst Live Web Course:

Take all the Benefits of the SAS Financial Data analyst Classes without the travel:

SAS Financial Data Analyst Classroom Training:

Taught by SAS certified experts at high-tech facilities across the country:

Key features for SAS Financial Data Analyst Certification Course

SAS Products Covered

The fees are inclusive of

Digital Badging

Validate your skills with a SAS Advance Certification

Plenary for SAS-FINANCIAL-DATA-ANALYST

SAS Credential: SAS Financial Data Analyst

Base SAS Programming

SAS Data Integration studio:

SAS Predictive Modeling Certification:

A) SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression:

B) Applied Analytics Using SAS Enterprise Miner:

SAS Visual Analytics for SAS Viya:

SAS Solutions for RISK and IFRS:

Digital Badges

Certification Exam

SAS Financial Data Analyst Global Certification:

SAS Financial Data Analyst Future Scope

SAS Financial Data Analyst Salary in India

What does SAS Financial Data Analyst Do?

Job Profiles for SAS Financial Data Analyst

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SAS Certification Course Curriculum

Module 1 - SAS Programming 1: Essentials

1.Essentials

2.Accessing Data

3. Exploring and Validating Data

4. Preparing Data

5. Analyzing and Reporting on Data

6. Exporting Results

7.Using SQL in SAS

Module 2 - SAS Programming 2: Data Manipulation Techniques

1.Controlling DATA Step Processing

2.Summarizing Data

3.Manipulating Data with Functions

4.Creating Custom Formats

5.Combining Tables

6. Processing Repetitive Code

7.Restructuring Tables

Module 3 - SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression

1.Introduction to Statistics

2.Analysis of Variance (ANOVA)

3.Regression

4.Regression Diagnostics

5.Categorical Data Analysis

Module 4 - Applied Analytics Using SAS Enterprise Miner

1.Introduction

2.Accessing and Assaying Prepared Data

3.Introduction to Predictive Modeling: Predictive Modeling Fundamentals and Decision Trees

4.Introduction to Predictive Modeling: Regressions

5.Introduction to Predictive Modeling: Neural Networks and Other Modeling Tools

6.Model Assessment

7.Model Implementation

8.Introduction to Pattern Discovery

9.Special Topics

10.Case Studies

Module 5 - SAS Visual Analytics 1 for SAS Viya: Basics

1.Getting Started with SAS Visual Analytics

2.Preparing Data in SAS Data Studio

3.Analyzing Data in SAS Visual Analytics

4.Designing Reports with SAS Visual Analytics

Module 6 - SAS Visual Analytics 2 for SAS Viya: Advanced

1.SAS Visual Analytics Overview

2.Restructuring Data for Geographic Mapping

3.Restructuring Data for Forecasting