Big data analytics use case and software
•
1 j'aime•1,414 vues
R is becoming the third most popular statistical software behind SAS and SPSS due to its open source nature and syntax that uses actual mathematical nomenclature. SAS is most commonly used and has over 60 modules, with the most popular being SAS BASE for data extraction, macros, and graphs from multiple sources, SAS ETL for extracting data from different sources, and SAS Graph for generating intuitive graphs. SPSS was acquired by IBM in 2009 and allows many analytical functions not previously available in IBM Cognos, integrating the two products. R has generated significant interest in recent years for its mathematical syntax and ability to be configured with any system as open source, such as using it with Hadoop for big data analytics.
Recommandé
Contenu connexe
Tendances
Tendances (20)
En vedette
En vedette (20)
Similaire à Big data analytics use case and software
Similaire à Big data analytics use case and software (20)
Plus de Sandeep Sharma IIMK Smart City,IoT,Bigdata,Cloud,BI,DW
Plus de Sandeep Sharma IIMK Smart City,IoT,Bigdata,Cloud,BI,DW (20)
Dernier
Dernier (20)
Big data analytics use case and software
- 3. Popular Statistical/Analytics Software Most popular Languages/packages which are used for Analytical and Statistical Processing : SPSS: Statistical Processing package taken over by IBM in year 2008. SAS: Statistical Analytical Software. Minitab: Is most used by Six Sigma practitioners . Matlab: Used for Data Analysis as well scientific software easier to work with Mathematical equations. R: Open Source package for statistical processing
- 4. Why ‘R’ • Interest in R is fuelled by its syntax which uses actual mathematical nomenclature and its open source. • Popularity of Analytical Software is like this 1st SAS, 2nd SPSS,3rd ‘R’ …… • SAS have industry specific modules like SAS econometrics while SPSS also has more depth but ‘R’ is used more as its open source.
- 5. SAS overview: Main module • SAS has more than 60 different modules but more used one are SAS BASE,SAS ETL,SAS Graph. • SAS has language called SAS BASE which can easily take data from multiple sources including excel sheet and can generates macros, graphs etc.. • SAS ETL used for Extracting data from disperate sources. SAS BI added 5 yrs back can be used for reporting. • SAS Graph is used to generate intuitive graphs.
- 6. SPSS overview • IBM acquired SPSS in 2009. SPSS allows lots of analytical functions which were not present in IBM Cognos. So now both products are integrated with IBM Cognos you can use SPSS. • So Architecture footprint is like SAS BI=IBM cognos, SAS Graph=SPSS graph module. SPSS is less program driven like SAS is on BASE.
- 7. ‘R’ overview • ‘R’ programing language last 2-3 yrs have generated lot of interest owing to its more mathematical inclined syntax and its open source so can be configured or integrated with any system. • E.g. today for Bigdata Analytics ‘R’ can be combined with Hadoop to analysis. • Most stack of Hadoop is open source hence ‘R’ fits in well there.
- 8. IBM SPSS