What is SAS?
SAS stands for Statistical Analysis Software which is developed by the SAS Institute in 1960. It is used to collect data from different sources like databases, files, warehouse, etc and performs operations like alter, insert, retrieve, etc to do a statistical analysis.
Functions of SAS
SAS can be used for the following functions:
- Statistical analysis
- Managing a large amount of data
- To improve quality
- Developing applications
- Extracting, transforming, updating Data
- Planning Business
As input to a DATA step, you can use different types of data. The DATA step includes SAS statements you write that contain data processing instructions. Compile or execute the DATA step in a SAS program, SAS generates
A log contains messages for processing and error messages. These messages can assist in debugging a SAS program.
SAS Alternatives
SAS is the leader in a universal Business Intelligence Software products and applicational services. As a result, it is the largest vendor in the universal Business Intelligence industry.
Because of its solid components and user interface, it is the popular tool but organizations choose alternatives to SAS based on the organization’s requirements. There are various tools and software used for business intelligence.
List of SAS Alternatives
Below is the list of few notable SAS Alternatives:
1. Sisense
Sisense is a business intelligence service that helps in managing and support business data with analytics, reporting, and visuals. It analyzes big and complex data and generates essential business trends for data sets.
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Sisense helps to collect the data which comes from various sources and combines them into a single database. After that, this software itself rearranges datasets into a standard format that is predefined. By using multiple filters and analytical tools provided by the software, users can then modify the data or perform slicing and dicing.
Sisense provides various functionalities as follows:
- Data warehousing
- ETL (Extract, transform and load)
- Dashboards and scoreboards for better analytics.
- Report writer
In Sisense, Crowd Accelerated BI technology provides the ability to share reports of analysis with users belongs to the organization both working internally and externally.
2. Anaconda
Anaconda is an open source python distribution which is used for processing a large amount of data, predictive analysis, and computation.
It supports 100 + packages of Python for science, math, engineering, and data analysis.
Linux, Windows, Mac is cross-platform. Anaconda does not require the privileges of root or local administrator.
3. WPS Analytics
The WPS industrial analysis platform has been developed for data science and heavy data written in the SAS and R languages. WPS software includes advanced GUI i.e graphical user interfaces, robustness, high-power data processing, and production-ready frameworks. it is best known for the SAS Language Compiler. WPS Analytics uses file, database, data warehouse, Hadoop clustering and some special connectors cloud storage for use in all processing and storage technologies.
4. Pentaho
Pentaho is a software company for business intelligence offering Pentaho Business Analytics, it is an open-source software suite of data integration, OLAP (online analytical processing), reporting, dashboarding, data mining and ETL functions.
The edition of the company contains additional characteristics that are not found in the community edition.
The company edition is received annually and includes additional support services.
5. Jamovi
The new open statistical spreadsheet for “3rd generation” is jamovi. Jamovi is a compelling alternative to costly statistic products such as PLCs and SAS, which is designed from ground-up to easy use. jamovi is a community project that invites people from all over the world to contribute. Jamovi saves your data, analyze it and their options and the results in the same file.
6. Gaio
Connect easily to drag & drop tables in databases such as Oracle, MS SQL, MySQL Server, etc. Build a data process that transforms your information, combines multiple sources of data, uses parameters and generates charts and table reports.
It is used to find out patterns, compare time-period values, and calculate all kinds of statistics easily. After the data workflow has been established, it will be performed frequently or once at a predefined time.
7. Montecarlito
As Montecarlito is an Open Source code with that in Excel Sheet there is a Direct Output. MonteCarlito is a free Monte-Carlo simulation Excel add-in. In addition, statistical analyzes such as average, median, standard error, variance, skewness, kurtosis also can be performed. Montecarlito is used to create Histogram
8. Data Robot
The automated learning platform for Data Robot enables predictive models to be created and deployed quickly and easily. In health records, clinical trials, billing processing systems, the healthcare industry still finds itself struggling to unblock the value of these data to lead to better patient results and comply with health care regulations.
9. R Programming
R is a programming language and it is a free software environment supported by the R Statistical Computing Foundation. The programming environment for the R language is based on a standard command-line interface. It is an open-source platform widely used for analyzing statistical data and graphs. It is a GNU project. R language can be considered as a distribution of S developed by John Chambers. Many fields like Data mining and Data analysis make use of this language to analyze data efficiently. It provides users to run commands, read and load the data and fetch results. Math operators are used such as +, -, *, / for calculations. The environment allows users to join separate data files in a single document, to pull out a variable and to regression into a single function in the resulting data set.
10. Stan
Stan is a programming language used for data analysis. It automatically enables the inference for large statistical models. It supports math library in C++ which is used to solve many mathematics problems like an algebraic equation, parabolic equations, probabilities, variance, etc.
Conclusion
By comparing all the tools and software anyone can choose the best alternative based on the requirements.
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