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SAS or R-uld must know the background.

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What is SAS?

Data analysis is performed using statistical analysis software, or SAS.

This enables you to implement high-quality methods and processes that increase employee output and revenue for your company. How Sass SAS is pronounced.

Data is extracted and classified in SAS, making it easy to find and examine data patterns.

It is a software package that enables you to perform advanced analytics, business intelligence, predictive analytics and data management to function successfully in a challenging and evolving corporate environment.

Additionally, SAS is platform-independent, so it can be used with Linux or Windows as the operating system.

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What does r mean?

R is a programming language often used for data analysis by data scientists and large businesses like Google, Airbnb, Facebook, etc.

For every type of data manipulation, statistical model, or visualization a data analyst would require, the R language provides a vast number of functions.

R provides the underlying tools for data organization, performing calculations on the provided data, and producing graphical displays of those data sets.

primary difference

R is open-source software, whereas SAS is proprietary software that requires a cash commitment to use.

The simplest tool to learn is SAS. So, even those with basic SQL experience can pick it up quickly; In contrast, R programmers must create painstaking, lengthy scripts.

R is an open-source program that is updated constantly, whereas SAS is updated somewhat regularly.

While R tools have weak graphical capabilities, SAS provides good graphical support.

While R has the largest online community but no customer service support, SAS does provide specialized customer support.

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Why use SAS?

Get raw data files and information from an external database.

Analyze data using linear programming, forecasting, modeling, descriptive statistics and multivariate methods.

Assistance with data entry, formatting, conversion, editing and retrieval

You can modify and enhance your business processes using advanced analytics.

Helps companies understand their historical data

Why use R?

For data analytics, R provides helpful programming features including conditionals, loops, input and output options, user-defined recursive functions, etc.

R has a strong and growing ecosystem, and a ton of online documentation.

This utility can be used on many operating systems including Windows, Unix and macOS.

A strong graphics capability backed by a large user network.

SAS. background of

At the University of North Carolina, Jim Goodnight and John Shawl created SAS in 1970.

It was initially built for agricultural research.

Later, it evolved to include various tools including BI, data management and predictive analysis.

Today 98 of the top 400 global corporations use SAS data analytics tools for data analysis.

How to measure the efficiency of an algorithm? ,

R . background of

The history of R dates back to 1993 when Ross Ihaka and Robert Gentleman created the programming language.

R was first made available as an open-source program in 1995 under the GPL2 license.

The R Core Group and CRAN were created in 1997.

Launch of R website, r-project.org in 1999

R 1.0.0 released in 2000

R 2.0.0 released in 2004

R 3.0.0 was launched in 2013, following the introduction of the R journal in 2009.

The new R logo was introduced in 2016

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Difference:- ParametersSASRAavailability/costSAS requires a monetary investment as it is commercial software. R is free software that is available to all. Ease of Learning is the simplest tool to learn SAS. So even those having basic understanding of SQL can pick it up quickly. R programmers are required to develop painstaking, extensive code. Statistical Capability SAS is a robust software that provides all kinds of statistical procedures and analysis. R is a free software program that lets users submit their own packages and libraries. R often sees the introduction of the latest technology. Files produced by SAS are not allowed to be shared with anyone who does not use SAS. Transferring files with another user is quite easy as anyone can use R. UpdateSAS is updated somewhat regularly. Since R is an open-source program, updates are always being made. As a result of fierce competition from MarketShareR and other data analytics tools, the market share of SAS is currently declining steadily. With its increasing popularity over the past five years, R experienced exponential growth. Because of this, its market share is increasing rapidly. Graphical Capabilities SAS has remarkable graphic capabilities. However, customization is not possible. R’s graphical support is subpar. Customer Support SAS provides dedicated customer service. The largest online community is R-Related, yet it does not provide any customer service. Support for deep learning still has to be completed before deep learning can be done. SAS reaches maturity. R provides sophisticated integration for deep learning. Job Scenario As far as corporate employment is concerned, SAS dominates the analytical tools market. SAS is still in use by many large businesses. In the last few years, there have been reports of increase in jobs at R.Salary Range. In the United States, a SAS programmer pays an average of $81,560. Data scientists can expect to earn an average of between $127,937 and $147,189 per year as “R” programmers. Best Features Variable Mixins Nested Rules Maintainable Functions Data Analysis Graphics and Data Flexible Statistical Analysis Incredibly Interactive Airbnb, StacShare, Asana, HubSpot, Instacart, Adroll, OpBandit, Custora Well-known companies that use

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