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Analytics USE Case
Big data analytics use case and software
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
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.
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.
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.
‘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.
IBM SPSS
IBM SPSS Analytics

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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.