Difference Between SAS vs RapidMiner

SAS – It stands for Statistical Analysis System, which presents SAS business intelligence and analytics solution. Developed by SAS Institute. The frequently used tool in commercial analytics marketing. Even people with basic knowledge of SQL can learn it easily. RapidMiner – It’s an open-source data mining solution. It enables users to create, deliver predictive analysis because it has a pervasive set of machine learning (cleaning, transformation, pre-processing, filtering) algorithms and functions. They use a client-server model application with Software -as- Service. The process structure is described internally by XML and developed by the Graphical user interface. They have strong enabled Visualizations like 3-D graphs, scatter metrics, and self-organizing maps.

What are SAS and RapidMiner?

Let us study much more about SAS vs Rapid Miner in detail:

Easy to use

Rapid Miner- It is a user-friendly visual workflow designer software, helps users with data preparation and modeling.
SAS – It can be learned easily without programming knowledge. They have simple coding statements.

Data Security

Rapid Miner- They have 4- layer security system. The user can log into the system or laptop through a single – sign- in. With Hadoop, it is solved by Kerberos authentication. They boost security and authentication for big data.
SAS- being closed source, the company’s data are safeguarded. Security prevents the data from manipulated. As it works in a closed environment, algorithms used in procedures are not made public.

Applications

Rapid miner- Some of the applications are:

Clinical Data
In Machine Learning for classification and clustering.

SAS – Some of the SAS applications are:

Factor Analysis (different statistical variables of an outcome, for Example: analyzing price, quality, feedback while buying a product).
Minimize programming effort & saves money and time.
Predictive analysis (for future work).
In medicine.

Features

Rapid miner – It uses XML to describe tree modeling, and it has a flexible file operator for data input and output file formats.
SAS – 1. Data retrieval and management. 2. Report writing and graphics.

Advantages

Rapid miner- No Coding Required. They have multiple deployment options based on user preference.
SAS – It is the market leader in analytic companies, has plenty of job opportunities in the fields. It can be easily debugged.

Disadvantage

Rapid miner – 1. Expensive licenses need to be purchased. 2. They need knowledge of data handling.
SAS – They doesn’t have fancy graphical possibilities.

Head to Head Comparison Between SAS and RapidMiner (Infographics)

Below is the top 6 difference between SAS and RapidMiner:

Key Differences Between SAS and RapidMiner

Both SAS vs RapidMiner are popular choices in the market; let us discuss some of the major Difference Between SAS and RapidMiner:

RAPID MINER is a powerful data mining tool for building predictive models. They perform hundreds of data preparation and machine learning algorithms to support data mining projects by simply using drag and drop off boxes representing modules called operators. RAPID MINER is a memory-based Systems. They analyze the data as long as it fits the RAM.
A key advantage of SAS is they are simple to learn. Adapted effectively by one with no programming knowledge. They have the potential to deal with huge data sets and data handling.
SAS works in many Platform. It has strong data access with good data visualizations ability. Even Rapid Miner is platform-independent and runs on different platforms. They have limited Graphical user Interface ability. An online data service has been improved in Rapid Miner.
Speaking about Customer support, Rapid miner has tiered support levels; documents and forums are publicly available and also has additional support with paid edition, whereas SAS has process improvements.
Coming to maintainability in RapidMiner, updates are optional but easily manageable.

Examples Between SAS and RapidMiner

The below example shows how SAS works:

DATA CLASS;

INPUT NAME $ 1-3 SEX $ 5 length $ 2 breadth $ 2

cards;

Divya F 12 2

prabha M 4 4

Suma F 2 6

PROC MEANS;

VAR SEX, LENGTH, BREADTH;

PROC PLOT;

PLOT LENGTH * BREADTH;

ENDSAS;

;

The input statements – variables are named sex.
Proc means procedure means, calculates the means for every variable.
PLOT – plot the values for length and breath.

Rapid Miner works in:

Rapid miner studio (accelerating prototype & interface, we can access, load data)
Rapid Miner server (increases productivity of data science).

SAS vs RapidMiner Comparison Table

Below is the topmost comparison between SAS and RapidMiner:

The Basis of Comparison between SAS vs RapidMiner	RapidMiner	SAS
Working Platform	Rapid Miner is an open-source platform (Cross Platform- can be installed in different OS).	SAS isn’t open-source. Therefore, the algorithms defined in the SAS system are not made open. It’s a licensed product. Numerous packages are paid here.
Ranking	Ranking 4^th in data science	Ranking 5^th in Data Science
Language used and its Type	Raid miner uses Java Programming Language. They have easily understandable graphs and charts.	SAS is a procedural language with no of lines of codes.
Popular Course in this category SAS Training (9 Courses, 10+ Projects)9 Online Courses \| 10 Hands-on Projects \| 123+ Hours \| Verifiable Certificate of Completion \| Lifetime Access 4.5 (9,370 ratings) Course Price View Course Related Courses Java Training (41 Courses, 29 Projects, 4 Quizzes)Python Training Program (40 Courses, 13+ Projects)HTML Training (12 Courses, 19+ Projects, 4 Quizzes) Ease of Use	Easy to use. Doesn’t require technical users. It includes a lot of data mining libraries and algorithms to work with.	Easily accessible web-based development. They have good performance and scalability.
Processing Steps	It works with the cloud domain. STEPS: Setting data source Decide parameters Execute (graph views)	SAS process consists of three steps: Data step (new variables are defined) Procedure Step (using ‘PROC name’) Data handling
COST	Quite expensive, and it consumes a lot of RAM which freezes the computer, doesn’t work well with big data.	The cost of SAS is slightly restrictive. Since it’s a closed source individual, I find it difficult in accessing applications without a license.

Conclusion

SAS is a good Model development using base SAS which is completely code-driven. The scalability issue associated with it is due to the slow down of RAM. Statistical analyses in SAS is done by direct Programming and use of SAS Analyst. They are leading in the market as advanced predictive analysis share. Rapid Miner is the only tool that is Language independent. Their functionality is extended with additional plug-ins. The results are displayed in multiple formats (as table / Statistical). It lacks market standard levels.

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