PROC CATMOD

•PROC CATMOD provides a wide variety of categorical data analyses.

•Now that PROC LOGISITIC handles classification variables, there is less of a need to use PROC CATMOD for regression.

•PROC CATMOD should not be used when a continuous input variable has many distinct values.

PROC ANOVA

•Each treatment should have exactly the same number of observations; every categorical outcome has the same number of observations.

•Caution: If you use PROC ANOVA for analysis of unbalanced data, you must assume responsibility for the validity of the results.

•Use PROC GLM instead. 

Regression Example

Residuals

•The studentized residual, the RSTUDENT statistic, is similar to the the standardized residual except that the mean square error is calculated omitting the observation.

•Observations with studentized residual absolute values of greater than 2 are potential outliers.

SAS - PROC REG

•Inputs and output are interval

•Ordinal data may be included

•Assumptions on e

– Normally distributed

– e has mean zero and constant variance

– Is independent

•Residual analysis should be a routine part of the analysis

SAS - Gplot – further example

•The following example shows more flexibility of the procedure

goptions reset=all;

proc gplot data=sashelp.Class;

symbol1 color = green i = join v= diamond line = 1 w=2 h=2;

symbol2 color = red i= join v= star line = 2 w=2 h=2;

plot Height*Weight=Sex/ hminor=0 legend=legend1;

legend1 down=1 position=(top center inside)

cshadow = blue frame value = (f=duplex)

ACROSS =1

label=(font=duplex h=1.5);

title f= zapf color=blue h =5pct 'Testing the graph';

run;

SAS - Gplot – A simple example

•SAS/ Graph modular is feathered by the flexible PROC gplot

•A simple example:

proc gplot data=sashelp.Class;

symbol i=none v=star;

plot height*weight;

run;

quit;

Resulting graph

SAS - PROC tabulate – For example 2

proc tabulate data=sashelp.Class;

class sex;

var height weight age;

table sex all, (age height weight)*(std mean sum);

run;

Result:

SAS - PROC tabulate – example (1)

proc tabulate data=sashelp.Class;

class sex;

var height weight;

table sex, height weight;

run;

Result:

  

SAS - PROC tabulate

•Summarize the data in the form of a well organized table

•Syntax:

PROC tabulate DATA=dataname;

ClASS class variables;

VAR variables;

TABLE page, row, column description/options;

 RUN;

Subqueries Operators SQL

 data plan_2008;
 input plancode $ year plan $ cust;
 cards;
 p101 2008 1min/2rs 450
 p201 2008 2min/3rs 560
 p207 2008 1min/1ps 660
 p345 2008 2min/2rs 640
 p420 2008 1min/80p 713
 ;
data plan_2009;
input plancode $ year plan $ cust;
cards;
p109 2009 1sec/2p 780
p207 2009 1min/1rs 640
p225 2009 1sec/1p 680
p420 2009 1min/80p 750
p431 2009 2sec/1p 790
;
data ae;
input pid visit $ aetype $;
cards;
103 visit1 eye dis
125 visit1 ear dis
145 visit1 eye dis
178 visit1 ear dis
198 visit1 rashes
103 visit2 ear dis
113 visit2 ear dis
125 visit2 eye dis
178 visit2 rashes
198 visit2 ear dis
103 visit3 rashes
113 visit3 eye dis
178 visit3 rashes
210 visit3 ear dis
;

/*row comparision between subqueries and operators*/
/*in all visits*/
proc sql;
select pid from ae where visit='visit1'
intersect
select pid from ae where visit='visit2'
intersect
select pid from ae where visit='visit3';
quit;

proc sql;
select * from ae where pid in(select pid from ae where visit='visit1'
intersect
select pid from ae where visit='visit2'
intersect
select pid from ae where visit='visit3');
quit;

/*1st visit*/
proc sql;
select pid from ae where visit='visit1'
except
select pid from ae where visit='visit2'
except
select pid from ae where visit='visit3';
quit;

proc sql;
select * from ae where pid in(select pid from ae where visit='visit1'
except
select pid from ae where visit='visit2'
except
select pid from ae where visit='visit3');
quit;

/*1st & 2nd visit*/
proc sql;
select pid from ae where visit='visit1'
intersect
select pid from ae where visit='visit2'
except
select pid from ae where visit='visit3';
quit;

proc sql;
select * from ae where pid in(select pid from ae where visit='visit1'
intersect
select pid from ae where visit='visit2'
except
select pid from ae where visit='visit3');
quit;

/*3rd visit*/
proc sql;
select pid from ae where visit='visit3'
except
select pid from ae where visit='visit1'
except
select pid from ae where visit='visit2';
quit;

proc sql;
select * from ae where pid in(select pid from ae where visit='visit3'
except
select pid from ae where visit='visit1'
except
select pid from ae where visit='visit2');
quit;

SAS - Operators SQL

 data plan_2008;
 input plancode $ year plan $ cust;
 cards;
 p101 2008 1min/2rs 450
 p201 2008 2min/3rs 560
 p207 2008 1min/1ps 660
 p345 2008 2min/2rs 640
 p420 2008 1min/80p 713
 ;

data plan_2009;
input plancode $ year plan $ cust;
cards;
p109 2009 1sec/2p 780
p207 2009 1min/1rs 640
p225 2009 1sec/1p 680
p420 2009 1min/80p 750
p431 2009 2sec/1p 790
;

/*operators*/
proc sql;
select * from plan_2008
union all
select * from plan_2009;
quit;

proc sql;
select * from plan_2008
union
select * from plan_2009;
quit;

proc sql;
select plancode,plan from plan_2008
intersect
select plancode,plan from plan_2009;
quit;

/*customisation*/
proc sql;
select plancode,plan,
'available in 2008-2009'as message from plan_2008
intersect
select plancode,plan,
'available in 2008-2009'as message from plan_2009;
quit;

/*except*/
proc sql;
select plancode,plan from plan_2008
except
select plancode,plan from plan_2009;
quit;

/*customization*/
proc sql;
select plancode,plan,
'only in 2008 'as message from plan_2008
except
select plancode,plan,
'only in 2008'as message from plan_2009;
quit;

proc sql;
proc sql;
select plancode,plan,
'only in 2008 'as message from plan_2008
except
select plancode,plan,
'only in 2008'as message from plan_2009;
quit;

proc sql;
(select plancode,plan from plan_2008
except
select plancode,plan from plan_2009)
union all
(select plancode,plan from plan_2009
except
select plancode,plan from plan_2008);
quit;

proc sql;
(select plancode,plan,
'only in 2008 'as message from plan_2008
except
select plancode,plan,
'only in 2008'as message from plan_2009)
union all
(select plancode,plan,
'only in 2009 'as message from plan_2008
except
select plancode,plan,
'only in 2009'as message from plan_2009);
quit;

/*sub queries*/
proc sql;
select * from plan_2008 where plancode not in(select plancode from plan_2009)
union all
select * from plan_2009 where plancode not in(select plancode from plan_2008);
quit;

proc sql;
select * from plan_2008 where plancode  in(select plancode from plan_2009)
union all
select * from plan_2009 where plancode  in(select plancode from plan_2008);
quit;

proc sql;
select * from plan_2009 where plancode  in(select plancode from plan_2008)
select * from plan_2008  where (cust<plan_2009 ,cust);
quit;

SAS - Strings SQL

proc import datafile='C:\Documents and Settings\mobileclub\Desktop\source\xls\data.xls'
out=demo1 dbms=excel replace;
sheet='sheet1$';
run;
proc sql;
select fname,
length(fname) as len,
index(fname, 'a') as ind1,
index(fname,'rao') as ind2,
scan(fname,3) as sc,
upcase(fname) as up,
compress(fname,'a') as comp1,
compress(fname) as comp2
 from demo1;
quit;
proc sql;
select fname,
compress(fname) as comp2,
substr(fname,3,10) as sub1,
substr(fname,3) as sub2
 from demo1;
 quit;
proc import datafile='C:\Documents and Settings\mobileclub\Desktop\source\xls\data.xls'
out=mh dbms=excel replace;
sheet='sheet3$';
run;
proc sql;
select pid,drug,dose,scan(adevents,1) as ae,
scan(adevents,2) as adr from mh;
quit;
proc import datafile='C:\Documents and Settings\mobileclub\Desktop\source\xls\data.xls'
out=mh1 dbms=excel replace;
sheet='sheet2$';
run;
proc sql;
select pid,drug ||'-'||dose as treatment from mh1;
quit;

Clinical SAS Resume13

                                             

                                                CURRICULAM VITAE

Objective

 Looking for a position in Research (Industrial), where I can demonstrate my technical and experimental skills and contribute to the development and better understanding of science for benefit.

Education

·         M.Sc. Chemistry with specialization in Organic Chemistry. Completed P.G. from Amravati University (M.S), with 66.10% of marks in 2005.

·         B.Sc. with subject as Chemistry, Physics &Math. Scored 68.60% of marks from Nalanda Degree Collage Adilabad (Kakatiya University) (A.P.)

·         Passed INTER with 77.90% of marks (maths, physics, and chemistry) from Nalanda Jr.Collage, Adilabad (A.P.)

·         Passed S.S.C with 76.00% of marks from Sri Saraswathi Shishum Mandir, Adilabad.(A.P.)

REFFERENCE

DR.V.LINGAM(PHD,MBA),

SENIOR MANAGER-BUSINESS DEVELOPMENT,

INOGENT LABORATORIES PVT.LTD,

PLOTNO 28 A, IDA NACHARAM,

HYDERABAD-500076, INDIA

MOBILE NO.09177404035.

Work Experience

 Current experience 

Having 2.7 Years of experience in Research & Development. Working as a chemist (R&D) in “Shree Vinayaka Life Science Pvt. Ltd”, Hyderabad. (www.vinayakalifesciences.com).

chemicals handled

 Bromine, Sodiumhydride, Acidchlorides,  Grignard Reagents(MMB, VMB,IPMC,4MBMC,,BMB,TBMC,NBMB,) , NaBH4, 

Aceticanhydride, , Aluminiumchloride, Chlorosulfonicacid , Thionylchloride., sodium azide, pyridine, 2-bromo propanoyl bromide, nbutyl lithium(NBL), potassium cynuide(KCN), olium, palladium acetate

Chemicals prepared

 Diphenyl cholro phosphate, magnesium chloride, vinyl bromide, methyl bromide, isopropyl chloride, teritiory butyl chloride, para methoxy benyl chloride,n-butyl bromide

Reaction Handled

Handled drugs & INTERMEDIATES:

DRUGS:

• Effaverienz (EF),(ONLY 4 STEPS)
• montolucast (MNT), (ONLY 3 STEPS)
• curcumin(CCM )
• merophenum(MAP),(ONLY 3STEPS)

INTERMEDIATES :

• magnesium salts(MONO PARA NITRO BENZYL MALONATE MAGNESIUM SALT),
• 2 –phenyl 2-propanol,
• DMF SULFER TRIOXIDE complexe
• MAGNESIUM TERITIORY BUTAOXIDE,
• SRPN,
• RF,
• MAGNESIUM ACETATE,

      REACTION CAPABLITIES                                                                                                                      

• Development of new  synthetic  process routes

• Handling of Compounds in Milligrams to grams level to killo gramlevel

• Having experience in carrying reactions with air and moisture sensitive

• Impurities Separation by using Column

• Expertise in High Vacuum & Steam, fractional distillation

• Reaction Monitoring through HPLC, GC & TLC System

• Purification of Organic Compounds through Techniques such as Column             Chromatography, extrations and Crystallizations

• Having experience in handling high temperatre(upto250C) and high colling

Reactions

• Capable of Collaborative and independent Research
•  

      Technical Skills                                                                                                                       

• PG-DCA cleared in 2006 with (Grade-A)
• C++, C language
• MS-Office.
• Windows XP/2000

          

Personal  skills

  

• Positive thinking
• Good Attitude
• Hard Working
• Learning Nature

Personal  Profile

  

                 

• Name                      :

• Father Name            :

• Date of Birth            :

• Religion                   :

• Gender          :

• Marital Statues         :

• Nationality               :

• Language Known       :

• Hobbies                   :

Declaration

I hereby declared that above information is correct according to my knowledge & belief. If it found incorrect or wrong, you have all right to cancel my candidature.

Date:                                                                             

Place:    

                                                                                                                                                                                                           

Clinical SAS Resume13

Professional Summary:-

·         Having 3+ years of experience in analyzing, developing and implementing of various applications in SAS for Pharmaceutical.

    

·         Strong proven knowledge in Base SAS, SAS/MACRO, SAS/SQL and SAS/STAT.  

·         Experience in Data Exporting and Data Importing of different file structures.

·         Extensive knowledge in data management like Merging, concatenating, interleaving and moving of SAS datasets.

·         Strong working knowledge on analysis of clinical trial data, generating reports, tables, listings, graphs and summaries as per company standards.

·         Experience with extraction and migration of data, Multivariate Statistical Analysis using various analysis procedures such as Proc Freq, Proc Means, and Proc ANOVA.

·         Experience in SAS/SQL to access data from relational databases.

·         Generating reports and graphs as per client’s specifications.

·         Ability to learn and adapt new technologies quickly. Analytical and problem solving skills.

Professional Experience:-

·            Working as a SAS programmer in Satyam Computer Services Ltd., Hyderabad from Aug 2005 to till date.

·            Worked as a SAS Programmer in Maxis Software Therapeutics Pvt.Ltd., Hyderabad from Jun2004-Jul2005.

Education Profile:-

·            Bachelor of Science in Mathematics from Acharya Nagarjuna University, Guntur.

Technical Expertise:-

Languages	C , SQL
SAS Tools	BASE /SAS, SAS/MACROS, SAS/STAT,  SAS/SQL,SAS/ODS, SAS/GRAPH, SAS/ACCESS
Operating Systems	Windows 98/XP/NT,  UNIX
Databases	ORACLE.

                                                                                                                                                                                      

Major Assignments:

ASSIGNMENT 1:

Client          :	Zila Pharmaceuticals
Position        :	SAS Programmer
Duration       :	Aug 2006-Till date
Environment  :	Base SAS, SAS/Macro, SAS/Access, SAS/Stat and SAS/SQL
Platforms      :	Windows NT/2000.

Zila, Inc. is a progressive company, bringing needed pharmaceutical, biomedical, dental and nutritional products to medical professionals and consumers worldwide. Involved in clinical data extraction, data mapping, analysis, validates protocols and reporting.

Description:

Is a Biopharmaceutical company developing products designed to improve the safety of the world’s health in Oncology and is conducting Phase III clinical trials. As a SAS Programmer, my role was in analysis of clinical trials data and generating required reports, listings, summaries and graphs for submission to FDA and other regulatory authorities.

Responsibilities:

●     Extracted data from Oracle using SAS/Access.

·         Modified existing datasets using Set, Merge, Sort, and Update, Functions and conditional statements.

·         Macros were extensively created and utilized. Developing user defined Formats and Informats to integrate the data.

·         Performed data integrity checks and data cleaning using SAS/MACROS and data steps, created HTML outputs with table of contents using ODS HTML.

·         Developed SAS Programs based on wide usage of SAS/BASE, SAS/MACRO facility to generate tables, listings, reports for clinical studies.

·         Created safety reports and efficacy reports using PROC REPORT for publishing and FDA submission.

ASSIGNMENT 2:

Client                :	Roche, Switzerland
Position             :	SAS programmer
Duration            :	Aug 2005-Jun 2006
Environment      :	Base SAS, SAS/Macro, SAS/Access, SAS/Stat and SAS/SQL
Platforms           :	Windows NT/2000.

Description:

     We are concentrating on how the Gender, Weight and Age are influencing on drug & combined effect Cmax concentrations, Clearance and Bioavailability at different doses. The main objective of the study is to determine how hormones influence the pharmacokinetic parameters against children and adolescents.

     The data (CRFs) provided by the client is entered into Oracle-Clinical. Data is then imported to SAS system. The safety analysis of the drug is done under the guidance of clinical research associates. Reports are generated in html or PDF or in graphs according to the client’s specification.

Responsibilities:

• Extracted raw data from Excel sheets and created SAS data sets that are required for the project analysis
• Cleaning, validating, sorting and merging techniques is done using SAS/Base include Macros.
• Generating reports BY using the PROC REPORT,PROC TABULATE,PROC MEANS, PROC PRINT and PROC SQL
• Involved in Delivering output using ODS (Output Delivery system)
• Using the Statical procedures like PROC UNIVARIATE,PROC FREQ,PROC CORR,PROC MEANS ,PEOC REG and PROC ANOVA   

ASSIGNMENT 3:

Client             :	IMS Health, NY
Position          :	SAS Programmer
Duration         :	Oct 2004-Jun2005
Environment   :	Base SAS, SAS/Macro, SAS/Access, SAS/Stat and SAS/SQL.
Platforms        :	Windows NT/2000.

Description:

                              

IMS is the one global source for pharmaceutical market intelligence, providing critical information, analysis and services that drive decisions and shape strategies. They monitor the sales of prescription drugs in over 100 countries for active drug manufacturers.                             

  

Clinical Trials are conducted to study the effect of new medicine in the treatment of cancer disease. This study was a double blind randomized, multi-dose studies conducted in two groups of patients i.e., one in patients with metastasis Cancer disease and one in patients with hormone refractory prostate cancer. I had the Opportunity of doing highly skilled Clinical Statistical Analysis. Extensively worked with statisticians to generate listings, summary reports, and tables for FDA submissions according to 21 CFR. Designed tables and graphs for clinical study reports.

Responsibilities:

·          Extracted raw data and created SAS data sets that are required for the project analysis.

·          Cleaning, validating, sorting and merging techniques are done using Base SAS includes Macros and SQL.

·          Once the data is prepared and validated, linear regression models are applied for analysis.

·          From the processed data several reports were generated, used Proc Report, Proc Tabulate and also converted the data into dbf format and sent to the client.

·          Involved in delivering output using ODS.

·          Generated Tables, Graphs and Listings for inclusion in Clinical study reports and regulatory submission.

·          Created SAS datasets in local SAS directory.

·          Analyzed data using SAS/Stat procedures. 

Clinical SAS Resume12

Career Objective:

                Seeking a position as a SAS analyst / programmer to utilize my skills and abilities in the Information Technology Industry. Having 3.6 years Experience in SAS.

Technical Knowledge:

                  SAS:

Modules include:  SAS Base, SAS Macros, SAS SQL, SAS/STAT, SAS/GRAPH, SAS Access and SAS Data warehouse Administrator. 

                  Database Tools:

                        SQL Server 2000, MS-SQL and MS-Access

Conversion Software:

                        Quanvert 1.7.3.1        

                  Platforms:

                        UNIX, Windows9x, Windows 2000 and Window NT

                  Programming Languages:

                                VB 6.0, Java, ASP.NET & VB.NET

Certification:

Ø      SAS Base Certified Programmer 

Employment:

    Standard chartered Bank Ltd.                                         From Feb 2007 to Till Date

    Business Intelligence analyst – Associate Manager, Datawarehouse

          Job Profile:

Ø      It’s a business intelligence unit and the datawarehouse team is responsible for the datamart and finance validation for Unsecured, Secured and wealth banking products.

Ø      Creating Cards data mart and profit base monthly and validating with finance number and also modifying the codes as per the collection and finance team request.

Ø      Dedupe the customer records using the several keys and calculating maximum unsecured exposure for them depends upon their salary and other details.

Ø      Maintaining do not call list (DND) database and extracting the data from it as per the request.

Ø     Responsible for CIBIL data upload monthly for all cards, PL, Smartcredit, Auto, Mileage, Mortgage, FAS and SME.

Projects:                                                                                          Aug 2007 – Till date

                  Project                     : Customer Profitability – BVL2

Tools                        : Base SAS, SAS SQL, SAS MACROS and SAS/Graph

Platform                  : UNIX       

Client                       : India

Team Size                           : 7

Role:

Product level,  account level profit bases are created using account level TP system information & values sourced from Finance MIR’s which are allocated.

These bases are then grouped at customer level via X custid.

      Responsibility of handling complex coding in SAS

      Project Planning and resource allocation.

Preparation of all individual profit bases for all banking products and aggregated at customer level.

                                                                                                           

                                                                                                            Mar 2007 - Jul 2007

                  Project                  : NPA bases for all products

                  Tools                     : Base SAS, SAS Macros, SAS/Stat, SAS/Graph and UNIX

                  Client                    : Internal

                  Team Size            : 5

Responsibilities:

The objective of this process is to create the bases for asset classification in terms of Non Performing Assets and provisioning thereof will be done borrower wise for the purposes of reporting to regulators.

Responsibilities include importing of raw data which in the form of Excel sheets, and collecting inputs from various units across the bank.

And developing sas codes for identifying cross hold products from several bases and written macro to avoid the duplication of customers.

    Marketics Technologies India Pvt. Ltd.                         From Sep 2004 to Feb 2007

             Team Leader           

It’s a Marketing Research company which provides solution to leverage the customer information so that marketers can design relevant marketing programs, target the campaigns appropriately, and measure results on the back end.

I am handling team of four members.

The major clients are Proctor & Gamble (P&G), USA, Asia Pacific.

     

   

  Job Profile:

·     Strong concepts of Information Systems, Data warehousing, Data Mining & Business Intelligence.

·     Involved in using SAS, SQL, and Business Objects to manipulate and analyses data.

·     Using simple Proc house-keeping commands like proc import, proc copy, proc append, Proc SQL (for making queries on datasets

·     Using all Proc statements, Regression analysis using Base SAS.

·     Convert the data from Quanvert to SAS.

·     Data analysis varies from simple descriptive statistics like customer profiling and reports, to more complex data modeling like regression analysis, step disc analysis and frequency distribution.

·     Generating the Sales data analysis reports using SQL 2000 and OLAP. Identifying potential customers from database and data-marts.

Projects:

                        Team lead - Marketics Technologies India Pvt. Ltd, Bangalore

                                                                                                            July 2006 - Feb 2007

                  Project                  : Global hair color architecture

                  Tools                     : Base SAS, SAS Macros, SAS/Stat, SAS/Graph and UNIX

                  Client                    : P&G – USA

                  Team Size            : 5

                  Responsibilities:

                  Leading a team of five members in Global hair color architecture project.

Interfaced with client to assess the exact requirements and volume of metrics reported in several report.

Joining and Linking Multiple Tables.

Performed data integrity checks and data cleaning using SAS/MACROS.

                 

                  Project Planning and resource allocation.

                  Issue Log, Defect tracking and Weekly Status Report

                  Senior Analyst - Marketics Technologies India Pvt. Ltd, Bangalore

                                                                                                       Mar 2006 - June 2006

Project                     : Data stability

Tools                        : Base SAS, SAS Access, SAS/Graph and Unix         

Database                : SQL Server 2000

Client                       : Confidential

Duration                 : 4 months

Team Size                           : 7

                  Role:

                     Database Clean up and structuring for mailing and analysis Mail merging for a six level personalization, Label Generation, Mail  Handling and Dispatch. Batching of responses to assign day of week and time slot for tennis session.

Responsibilities include  importing of raw data which in the form of Excel sheets, Text files to SAS datasets.

Sorting the data, removing the redundant data and match merging the datasets.

User defined queries written using proc sql. Report generation using Proc Report, Tabulate, Freq, Summary.

                                   

                                                                        Nov 2005 - Feb 2006

                        Project                  :  The Paper towel segmentation Project

      Client                    :  P&G Geniva

      Tools                     :  Base SAS, SAS Macros, SAS/STAT and Unix

      Database              :  Excel and Quanvert

      Hardware             :  Windows XP

      Duration               :  4 Months

      Team Size                        :  5

                        Role:

Involved in complete understanding of Business problems and identifying appropriate analysis technique.

Data cleaning and identifying specific attributes for analysis.

Finalizing the base sizes for breaks.

Guidance to juniors for factor analysis and cluster analysis.

      Analyzing the results obtained from cluster analysis and profiling.

     

                        Business Analyst - Marketics Technologies India Pvt. Ltd, Bangalore

                                                                                                      June 2005 - Oct 2005

              

                  Project                  : Bounty US Data management

                  Tools                     : Base SAS, SAS Macros, SAS/Stat, SAS/Graph

                  Client                    : P&G – USA

                  Team Size                        : 5

                 

                  Role:

Involved in using SAS, SQL, and Unix to manipulate and analysis data. Data analysis varies from simple descriptive statistics like customer profiling and reports, to more complex data modeling like regression analysis, Predictive sales analysis and frequency distribution.

Getting customer contact information from various sources like Event

registrations, Fax-Back forms, eMail responses and telemarketing agents.

Organizing the data into a standardized format using Format Procedure.

                  Generating the Sales data analysis reports using Proc Reports.

     

Building Mart tables using datasteps and Warehouse Admin

Mailing activities done to various customers.

Identifying potential customers from database and data-marts.

                                                                                                            Mar 2005 - May 2005

                                              Project                  : The UK paper towel database maintenance                        

                                              Tools                      : Base SAS, SAS Stats, SAS/Graph        

      Database               : Quanvert and MS-SQL

      Client                     : P&G

                  Duration               : 3 months

                  Team Size                        : 7

                  Role:

                  Involved in Data cleaning, analyzing and supporting a reporting system using

SAS BASE and SAS Stats. Final reports are produced by the system both in Excel and PPT format. Also involved in generating reports/listing using

                  PROC FREQ/TAB/SUMMARY.

                  Import of customer data from MS-SQL, Quanvert and Excel  into SAS

                  Have done Regression and Structural Equation Modeling analysis. .

                                                                                                            Oct 2004 - Feb 2005

              

      Project Title         : Global hair care country segmentation

Client                   : P&G

Operating System: Windows XP

Language             : SAS 8.2, SPSS

Others                  : Quanvert and Excel

Team Size                        : 3

Technique           : Factors and cluster analysis

                  Role:

                  Involed in the data mining and factor and cluster analysis.

Fixing the factors and used those factors in clusters to find out necessary    segmentation results.

Have done SAS macros to automate cluster analysis methods.

Educational Qualification:

#   B.E Computer Science in Mahendra Engg.college. from Periyar  

      University In 2004 with 70.5 %.

#   H.S.C. from ST.paul’s higher secondary school In 1999 with 84 %.

#   S.S.L.C. from Little flower higher secondary school In 1997 with 79%.

                 

Personal Details:

        

References upon Request.