SAS

Dheeraj

Java

Information management and data analysis for raw data using Base SAS, SAS Enterprise Guide; SAS Data Integration Studio; SAS Viya, Tableau, Qlikview. Find SAS WFH freelancers on January 21, 2025 who work remotely. Read less

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From college-level to SAT, ACT, AP, find statisticians to teach

Math / Statistics

MATLAB

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Statistical Analysis

Mathcad

Build simulation models to solve real-world problem using Discrete Event

Simulation Modeling

Regression test planning; writing of test cases and test scripts;

Regression Testing

Interpret data from disparate sources, analyze results using stats, AI

Machine Learning

Design, build and delivery of analytics and reporting products and

Business Intelligence / Analysis

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How do freelancers use SAS software?

SAS (Statistical Analysis System) is a widely used software suite for advanced analytics, multivariate analysis, business intelligence, data management, and predictive analytics. Here are some key features of SAS software:

1. Data Management
Data Integration: SAS Data Management allows for the integration of data from various sources, cleaning, transforming, and preparing it for analysis.
Data Quality: Features for data profiling, cleansing, and standardization to ensure data accuracy and consistency.
Master Data Management (MDM): Provides capabilities for managing golden records of core business data.

2. Statistical Analysis
Advanced Analytics: Offers a vast array of statistical procedures for both basic and advanced analytics, from descriptive statistics to complex multivariate analysis.
Predictive Modeling: Includes tools for regression analysis, time series forecasting, decision trees, neural networks, and more.
Survival Analysis: Specialized procedures for time-to-event analysis, commonly used in medical and reliability research.

3. Business Intelligence (BI)
SAS Visual Analytics: Interactive data visualization and discovery tool that allows users to explore data, create dashboards, and share insights.
SAS Enterprise Guide: An interface for less technical users to perform data analysis with a point-and-click environment.
Reporting: Powerful reporting capabilities with options for static reports as well as interactive, web-based reports.

4. Machine Learning
SAS Visual Machine Learning: Enables users to build, validate, and deploy predictive models with a focus on ease of use for non-data scientists.
Model Management: Tools for managing the lifecycle of machine learning models from development to deployment.

5. Programming Language
SAS Language: A powerful, data-centric programming language used for data manipulation, analysis, and reporting. It's known for its PROC steps for statistical analysis and DATA steps for data processing.
MACRO Language: For automating repetitive tasks and creating more complex programs.

6. Data Mining
SAS Enterprise Miner: A comprehensive data mining tool that automates the process of building predictive models, with features for data partitioning, transformation, and model assessment.

7. Text Analytics
SAS Text Miner: Provides tools for extracting information from unstructured text data, including topic detection, sentiment analysis, and entity recognition.

8. Forecasting
SAS Forecast Server: Advanced forecasting capabilities for time series data, supporting a wide range of methods from simple to complex models.

9. Risk Management
SAS Risk Management for Banking: Specialized tools for financial risk analysis, including credit risk, market risk, and operational risk.

10. Security and Compliance
Data Governance: Tools for data lineage, metadata management, and policy enforcement to ensure compliance with regulations like GDPR or HIPAA.
Security: Strong encryption, access controls, and audit trails for securing sensitive data.

11. Scalability and Performance
In-Memory Analytics: SAS Viya introduces in-memory processing for faster analytics on large datasets.
Distributed Computing: Capabilities to scale analytics across multiple machines or in the cloud for handling big data.

12. Integration
Open Interfaces: SAS supports integration with other systems through APIs, SQL access, and support for data formats like JSON, XML, and many database systems.
Cloud Support: SAS Viya is designed to run on cloud platforms, offering hybrid cloud solutions.

13. Industry Solutions
Vertical Applications: SAS provides tailored solutions for industries like healthcare, banking, insurance, manufacturing, and more, with specific analytical tools for each sector.

14. User Interface
Modern UI: With SAS Viya, there's a shift towards more user-friendly interfaces, which can be accessed via web browsers for broader accessibility.

15. Learning Ecosystem
SAS Academy for Data Science: Comprehensive training and certification programs to help users master SAS tools.

While SAS is known for its robust statistical capabilities and enterprise-level deployment, it's also recognized for its steep learning curve compared to some open-source alternatives. However, its depth, support, and integration with business processes make it a preferred choice for many organizations dealing with complex data and analytics needs.

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