400.Can SAS Detect Hidden Fraud in Remote Work Environments?

Can SAS Detect Hidden Fraud in Remote Work Environments?

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HERE IN THIS PROJECT WE USED THESE SAS STATEMENTS —
DATA STEP | PROC SQL |  PROC PRINT | PROC SGPLOT | MACROS | PROC CORR | PROC MEANS | PROC FREQ | PROC UNIVARIATE | PROC SORT | APPEND | MERGE | PROC TRANSPOSE | PROC DATASETS DELETE | DATA FUNCTIONS

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TABLE OF CONTENTS

1. Introduction
2. Business Context
3. Project Objectives
4. Dataset Design & Variables
5. Raw Dataset Creation
6. Data Cleaning & Formatting
7. Date Intelligence (MDY, INTCK, INTNX)
8. Character & Numeric Functions
9. Productivity & Utilization Logic (Macros)
10. Fraud Detection Logic (Macros)
11. SQL Analytics
12. Statistical Analysis
13. Frequency & Distribution Analysis
14. Correlation Analysis
15. Visualization (SGPLOT)
16. Transpose, Append, Set & Merge
17. PROC DATASETS 
18. Business Insights
19. Interview-Ready Talking Points
20. Conclusion

1. INTRODUCTION

Remote work has transformed how organizations manage productivity, employee well-being, and operational risk. Unlike office environments, remote teams require data-driven monitoring to ensure:

• Optimal productivity
• Controlled burnout
• Fair workload distribution
• Fraud or misuse detection

This project simulates a real corporate analytics use case using SAS.

2.BUSINESS CONTEXT

Organizations with remote employees face challenges like:

• Over-reporting work hours
• Low output despite high availability
• Burnout leading to attrition
• Communication gaps
• Fraudulent time reporting

Hence, analytics teams use SAS to monitor patterns using:

• Productivity Index
• Utilization classification
• Burnout thresholds
• Statistical anomaly detection

3.PROJECT OBJECTIVES

* Create a remote employee dataset (15+ records)
* Apply SQL, DATA step, Macros
* Perform descriptive & inferential statistics
* Implement fraud detection logic
* Demonstrate interview-level SAS expertise

4. DATASET DESIGN & VARIABLES

Variable	Description
Employee_ID	Unique employee number
Employee_Name	Employee full name
Role	Job role
Join_Date	Date of joining
Report_Date	Date of performance capture
Hours_Worked	Daily working hours
Tasks_Completed	Tasks completed
Communication_Frequency	Meetings/emails count
Burnout_Score	Stress indicator
Productivity_Index	Derived KPI (%)
Utilization_Class	Macro-driven
Fraud_Flag	Macro-driven

5. RAW DATASET CREATION

data remote_employees_raw;

    length Employee_Name $20. Role $20. Region $15. Work_Mode $15.;

    input Employee_ID Employee_Name $ Role $ Join_Date : date9. Report_Date : date9.

          Hours_Worked Tasks_Completed Communication_Frequency Burnout_Score Region $

          Work_Mode $;

    format Join_Date Report_Date date9.;

datalines;

101 Nithish Data_Analyst 15JAN2022 01JAN2026 9 12 6 32 India Fully_Remote

102 Anjali SAS_Programmer 12FEB2021 01JAN2026 10 14 8 28 India Hybrid

103 Rahul Statistician 20MAR2020 01JAN2026 11 15 9 35 USA Fully_Remote

104 Sneha Data_Manager 01APR2019 01JAN2026 8 10 5 40 UK Fully_Remote

105 Arjun BI_Analyst 17MAY2022 01JAN2026 7 9 4 22 India Hybrid

106 Kavya Clinical_Analyst 10JUN2021 01JAN2026 9 13 7 30 India Fully_Remote

107 Amit QA_Analyst 05JUL2020 01JAN2026 12 16 10 45 USA Fully_Remote

108 Pooja Risk_Analyst 18AUG2019 01JAN2026 6 7 3 20 UK Hybrid

109 Rakesh SQL_Developer 01SEP2022 01JAN2026 8 11 6 27 India Fully_Remote

110 Neha Data_Scientist 15OCT2018 01JAN2026 10 14 8 38 USA Fully_Remote

111 Suresh ETL_Developer 01NOV2021 01JAN2026 9 12 7 29 India Hybrid

112 Kiran Report_Analyst 20DEC2020 01JAN2026 7 9 5 26 India Fully_Remote

113 Meena Validation_Lead 05JAN2019 01JAN2026 11 15 9 42 UK Fully_Remote

114 Prasad Macro_Developer 14FEB2022 01JAN2026 10 14 8 33 India Hybrid

115 Divya Safety_Analyst 30MAR2021 01JAN2026 8 10 6 25 India Fully_Remote

;

run;

proc print data=remote_employees_raw;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score
1	Nithish	Data_Analyst	India	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32
2	Anjali	SAS_Programmer	India	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28
3	Rahul	Statistician	USA	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35
4	Sneha	Data_Manager	UK	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40
5	Arjun	BI_Analyst	India	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22
6	Kavya	Clinical_Analyst	India	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30
7	Amit	QA_Analyst	USA	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45
8	Pooja	Risk_Analyst	UK	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20
9	Rakesh	SQL_Developer	India	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27
10	Neha	Data_Scientist	USA	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38
11	Suresh	ETL_Developer	India	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29
12	Kiran	Report_Analyst	India	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26
13	Meena	Validation_Lead	UK	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42
14	Prasad	Macro_Developer	India	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33
15	Divya	Safety_Analyst	India	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25

·  Core SAS dataset creation

·  Supports formats, informats, raw ingestion

·  Industry-standard for structured data

6. DATA CLEANING & FORMATTING

data remote_employees_clean;

    set remote_employees_raw;

    Employee_Name = propcase(strip(Employee_Name));

    Role = upcase(Role);

    Region = lowcase(Region);

    Work_Mode = catx('_',strip(Work_Mode));

run;

proc print data=remote_employees_clean;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25

·  STRIP, TRIM → remove spaces

·  PROPCASS, UPCASE, LOWCASE → standardization

·  CATX → controlled concatenation

7. DATE INTELLIGENCE

data remote_dates;

    set remote_employees_clean;

    Tenure_Months = intck('month', Join_Date, Report_Date);

    Next_Review_Date = intnx('month', Report_Date, 3, 'same');

    Review_Month = month(mdy(month(Report_Date),1,year(Report_Date)));

run;

proc print data=remote_dates;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1

·  HR analytics

·  Performance cycles

·  Payroll fraud windows

8. PRODUCTIVITY INDEX CALCULATION

data remote_productivity;

    set remote_dates;

    Productivity_Index = round((Tasks_Completed / Hours_Worked)*10,0.01);

run;

proc print data=remote_productivity;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1	13.33
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1	14.00
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1	13.64
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1	12.50
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1	12.86
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1	14.44
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1	13.33
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1	11.67
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1	13.75
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1	14.00
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1	13.33
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1	12.86
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1	13.64
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1	14.00
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1	12.50

·  Reusability

·  Parameterization

·  Enterprise scalability

9. UTILIZATION CLASSIFICATION (MACRO)

%macro utilization;

data remote_utilization;

    set remote_productivity;

length  Utilization_Class $8.;

    if Productivity_Index >= 15 then Utilization_Class='High';

    else if Productivity_Index >=10 then Utilization_Class='Medium';

    else Utilization_Class='Low';

run;

proc print data=remote_utilization;

run;

%mend;

%utilization;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index	Utilization_Class
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1	13.33	Medium
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1	14.00	Medium
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1	13.64	Medium
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1	12.50	Medium
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1	12.86	Medium
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1	14.44	Medium
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1	13.33	Medium
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1	11.67	Medium
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1	13.75	Medium
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1	14.00	Medium
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1	13.33	Medium
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1	12.86	Medium
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1	13.64	Medium
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1	14.00	Medium
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1	12.50	Medium

10. FRAUD DETECTION LOGIC

%macro fraud;

data remote_fraud;

    set remote_utilization;

    if Hours_Worked > 11 and Tasks_Completed < 10 then Fraud_Flag='YES';

    else Fraud_Flag='NO';

run;

proc print data=remote_fraud;

run;

%mend;

%fraud;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index	Utilization_Class	Fraud_Flag
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1	13.33	Medium	NO
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1	14.00	Medium	NO
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1	13.64	Medium	NO
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1	12.50	Medium	NO
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1	12.86	Medium	NO
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1	14.44	Medium	NO
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1	13.33	Medium	NO
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1	11.67	Medium	NO
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1	13.75	Medium	NO
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1	14.00	Medium	NO
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1	13.33	Medium	NO
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1	12.86	Medium	NO
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1	13.64	Medium	NO
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1	14.00	Medium	NO
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1	12.50	Medium	NO

·  High hours + low output

·  Burnout anomalies

·  Communication mismatch

11. PROC SQL ANALYTICS

proc sql;

    create table role_summary as

    select Role,

           avg(Productivity_Index) as Avg_Productivity,

           avg(Burnout_Score) as Avg_Burnout

    from remote_fraud

    group by Role;

quit;

proc print data=role_summary;

run;

OUTPUT:

Obs	Role	Avg_Productivity	Avg_Burnout
1	BI_ANALYST	12.86	22
2	CLINICAL_ANALYST	14.44	30
3	DATA_ANALYST	13.33	32
4	DATA_MANAGER	12.50	40
5	DATA_SCIENTIST	14.00	38
6	ETL_DEVELOPER	13.33	29
7	MACRO_DEVELOPER	14.00	33
8	QA_ANALYST	13.33	45
9	REPORT_ANALYST	12.86	26
10	RISK_ANALYST	11.67	20
11	SAFETY_ANALYST	12.50	25
12	SAS_PROGRAMMER	14.00	28
13	SQL_DEVELOPER	13.75	27
14	STATISTICIAN	13.64	35
15	VALIDATION_LEAD	13.64	42

12. STATISTICAL ANALYSIS

proc means data=remote_fraud mean min max std;

    var Hours_Worked Tasks_Completed Productivity_Index Burnout_Score;

run;

OUTPUT:

The MEANS Procedure

Variable	Mean	Minimum	Maximum	Std Dev
Hours_Worked Tasks_Completed Productivity_Index Burnout_Score	9.0000000 12.0666667 13.3233333 31.4666667	6.0000000 7.0000000 11.6700000 20.0000000	12.0000000 16.0000000 14.4400000 45.0000000	1.6903085 2.6583203 0.7329945 7.3568886

proc univariate data=remote_fraud;

    var Productivity_Index;

run;

OUTPUT:

The UNIVARIATE Procedure

Variable: Productivity_Index

Moments
N	15	Sum Weights	15
Mean	13.3233333	Sum Observations	199.85
Std Deviation	0.73299451	Variance	0.53728095
Skewness	-0.7055677	Kurtosis	0.31175916
Uncorrected SS	2670.1901	Corrected SS	7.52193333
Coeff Variation	5.50158502	Std Error Mean	0.18925837

Basic Statistical Measures
Location		Variability
Mean	13.32333	Std Deviation	0.73299
Median	13.33000	Variance	0.53728
Mode	13.33000	Range	2.77000
		Interquartile Range	1.14000

Note: The mode displayed is the smallest of 2 modes with a count of 3.

Tests for Location: Mu0=0
Test	Statistic		p Value
Student's t	t	70.39759	Pr > |t|	<.0001
Sign	M	7.5	Pr >= |M|	<.0001
Signed Rank	S	60	Pr >= |S|	<.0001

Quantiles (Definition 5)
Level	Quantile
100% Max	14.44
99%	14.44
95%	14.44
90%	14.00
75% Q3	14.00
50% Median	13.33
25% Q1	12.86
10%	12.50
5%	11.67
1%	11.67
0% Min	11.67

Extreme Observations
Lowest		Highest
Value	Obs	Value	Obs
11.67	8	13.75	9
12.50	15	14.00	2
12.50	4	14.00	10
12.86	12	14.00	14
12.86	5	14.44	6

13. FREQUENCY ANALYSIS

proc freq data=remote_fraud;

    tables Utilization_Class Fraud_Flag Work_Mode;

run;

OUTPUT:

The FREQ Procedure

Utilization_Class	Frequency	Percent	Cumulative Frequency	Cumulative Percent
Medium	15	100.00	15	100.00

Fraud_Flag	Frequency	Percent	Cumulative Frequency	Cumulative Percent
NO	15	100.00	15	100.00

Work_Mode	Frequency	Percent	Cumulative Frequency	Cumulative Percent
Fully_Remote	10	66.67	10	66.67
Hybrid	5	33.33	15	100.00

14. CORRELATION ANALYSIS

proc corr data=remote_fraud;

    var Hours_Worked Tasks_Completed Burnout_Score Productivity_Index;

run;

OUTPUT:

The CORR Procedure

4 Variables:	Hours_Worked Tasks_Completed Burnout_Score Productivity_Index

Simple Statistics
Variable	N	Mean	Std Dev	Sum	Minimum	Maximum
Hours_Worked	15	9.00000	1.69031	135.00000	6.00000	12.00000
Tasks_Completed	15	12.06667	2.65832	181.00000	7.00000	16.00000
Burnout_Score	15	31.46667	7.35689	472.00000	20.00000	45.00000
Productivity_Index	15	13.32333	0.73299	199.85000	11.67000	14.44000

Pearson Correlation Coefficients, N = 15 Prob > |r| under H0: Rho=0
	Hours_Worked	Tasks_Completed	Burnout_Score	Productivity_Index
Hours_Worked	1.00000	0.98558 <.0001	0.80416 0.0003	0.65434 0.0081
Tasks_Completed	0.98558 <.0001	1.00000	0.75433 0.0012	0.77042 0.0008
Burnout_Score	0.80416 0.0003	0.75433 0.0012	1.00000	0.37455 0.1690
Productivity_Index	0.65434 0.0081	0.77042 0.0008	0.37455 0.1690	1.00000

15. VISUALIZATION

proc sgplot data=remote_fraud;

    scatter x=Hours_Worked y=Productivity_Index;

run;

OUTPUT:

16. TRANSPOSE

proc transpose data=remote_fraud out=prod_t;

    var Productivity_Index Burnout_Score;

    by Employee_ID;

run;

proc print data=prod_t;

run;

OUTPUT:

Obs	Employee_ID	_NAME_	COL1
1	101	Productivity_Index	13.33
2	101	Burnout_Score	32.00
3	102	Productivity_Index	14.00
4	102	Burnout_Score	28.00
5	103	Productivity_Index	13.64
6	103	Burnout_Score	35.00
7	104	Productivity_Index	12.50
8	104	Burnout_Score	40.00
9	105	Productivity_Index	12.86
10	105	Burnout_Score	22.00
11	106	Productivity_Index	14.44
12	106	Burnout_Score	30.00
13	107	Productivity_Index	13.33
14	107	Burnout_Score	45.00
15	108	Productivity_Index	11.67
16	108	Burnout_Score	20.00
17	109	Productivity_Index	13.75
18	109	Burnout_Score	27.00
19	110	Productivity_Index	14.00
20	110	Burnout_Score	38.00
21	111	Productivity_Index	13.33
22	111	Burnout_Score	29.00
23	112	Productivity_Index	12.86
24	112	Burnout_Score	26.00
25	113	Productivity_Index	13.64
26	113	Burnout_Score	42.00
27	114	Productivity_Index	14.00
28	114	Burnout_Score	33.00
29	115	Productivity_Index	12.50
30	115	Burnout_Score	25.00

17. CREATE A NEW DATASET,APPEND

data remote_fraud_new;

    set remote_fraud;

    Report_Date = intnx('month', Report_Date, 1, 'same');

    format Report_Date date9.;

run;

proc print data=remote_fraud_new;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index	Utilization_Class	Fraud_Flag
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01FEB2026	9	12	6	32	48	24197	1	13.33	Medium	NO
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01FEB2026	10	14	8	28	59	24197	1	14.00	Medium	NO
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01FEB2026	11	15	9	35	70	24197	1	13.64	Medium	NO
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01FEB2026	8	10	5	40	81	24197	1	12.50	Medium	NO
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01FEB2026	7	9	4	22	44	24197	1	12.86	Medium	NO
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01FEB2026	9	13	7	30	55	24197	1	14.44	Medium	NO
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01FEB2026	12	16	10	45	66	24197	1	13.33	Medium	NO
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01FEB2026	6	7	3	20	77	24197	1	11.67	Medium	NO
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01FEB2026	8	11	6	27	40	24197	1	13.75	Medium	NO
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01FEB2026	10	14	8	38	87	24197	1	14.00	Medium	NO
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01FEB2026	9	12	7	29	50	24197	1	13.33	Medium	NO
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01FEB2026	7	9	5	26	61	24197	1	12.86	Medium	NO
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01FEB2026	11	15	9	42	84	24197	1	13.64	Medium	NO
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01FEB2026	10	14	8	33	47	24197	1	14.00	Medium	NO
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01FEB2026	8	10	6	25	58	24197	1	12.50	Medium	NO

proc append base=remote_fraud 

            data=remote_fraud_new force;

run;

proc print data=remote_fraud;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index	Utilization_Class	Fraud_Flag
1	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1	13.33	Medium	NO
2	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1	14.00	Medium	NO
3	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1	13.64	Medium	NO
4	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1	12.50	Medium	NO
5	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1	12.86	Medium	NO
6	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1	14.44	Medium	NO
7	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1	13.33	Medium	NO
8	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1	11.67	Medium	NO
9	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1	13.75	Medium	NO
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1	14.00	Medium	NO
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1	13.33	Medium	NO
12	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1	12.86	Medium	NO
13	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1	13.64	Medium	NO
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1	14.00	Medium	NO
15	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1	12.50	Medium	NO
16	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01FEB2026	9	12	6	32	48	24197	1	13.33	Medium	NO
17	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01FEB2026	10	14	8	28	59	24197	1	14.00	Medium	NO
18	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01FEB2026	11	15	9	35	70	24197	1	13.64	Medium	NO
19	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01FEB2026	8	10	5	40	81	24197	1	12.50	Medium	NO
20	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01FEB2026	7	9	4	22	44	24197	1	12.86	Medium	NO
21	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01FEB2026	9	13	7	30	55	24197	1	14.44	Medium	NO
22	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01FEB2026	12	16	10	45	66	24197	1	13.33	Medium	NO
23	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01FEB2026	6	7	3	20	77	24197	1	11.67	Medium	NO
24	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01FEB2026	8	11	6	27	40	24197	1	13.75	Medium	NO
25	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01FEB2026	10	14	8	38	87	24197	1	14.00	Medium	NO
26	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01FEB2026	9	12	7	29	50	24197	1	13.33	Medium	NO
27	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01FEB2026	7	9	5	26	61	24197	1	12.86	Medium	NO
28	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01FEB2026	11	15	9	42	84	24197	1	13.64	Medium	NO
29	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01FEB2026	10	14	8	33	47	24197	1	14.00	Medium	NO
30	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01FEB2026	8	10	6	25	58	24197	1	12.50	Medium	NO

proc sort data=remote_fraud;by Role;run;

proc print data=remote_fraud;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index	Utilization_Class	Fraud_Flag
1	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1	12.86	Medium	NO
2	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01FEB2026	7	9	4	22	44	24197	1	12.86	Medium	NO
3	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1	14.44	Medium	NO
4	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01FEB2026	9	13	7	30	55	24197	1	14.44	Medium	NO
5	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1	13.33	Medium	NO
6	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01FEB2026	9	12	6	32	48	24197	1	13.33	Medium	NO
7	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1	12.50	Medium	NO
8	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01FEB2026	8	10	5	40	81	24197	1	12.50	Medium	NO
9	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1	14.00	Medium	NO
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01FEB2026	10	14	8	38	87	24197	1	14.00	Medium	NO
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1	13.33	Medium	NO
12	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01FEB2026	9	12	7	29	50	24197	1	13.33	Medium	NO
13	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1	14.00	Medium	NO
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01FEB2026	10	14	8	33	47	24197	1	14.00	Medium	NO
15	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1	13.33	Medium	NO
16	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01FEB2026	12	16	10	45	66	24197	1	13.33	Medium	NO
17	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1	12.86	Medium	NO
18	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01FEB2026	7	9	5	26	61	24197	1	12.86	Medium	NO
19	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1	11.67	Medium	NO
20	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01FEB2026	6	7	3	20	77	24197	1	11.67	Medium	NO
21	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1	12.50	Medium	NO
22	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01FEB2026	8	10	6	25	58	24197	1	12.50	Medium	NO
23	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1	14.00	Medium	NO
24	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01FEB2026	10	14	8	28	59	24197	1	14.00	Medium	NO
25	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1	13.75	Medium	NO
26	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01FEB2026	8	11	6	27	40	24197	1	13.75	Medium	NO
27	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1	13.64	Medium	NO
28	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01FEB2026	11	15	9	35	70	24197	1	13.64	Medium	NO
29	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1	13.64	Medium	NO
30	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01FEB2026	11	15	9	42	84	24197	1	13.64	Medium	NO

proc sort data=role_summary;by Role;run;

proc print data=role_summary;

run;

OUTPUT:

Obs	Role	Avg_Productivity	Avg_Burnout
1	BI_ANALYST	12.86	22
2	CLINICAL_ANALYST	14.44	30
3	DATA_ANALYST	13.33	32
4	DATA_MANAGER	12.50	40
5	DATA_SCIENTIST	14.00	38
6	ETL_DEVELOPER	13.33	29
7	MACRO_DEVELOPER	14.00	33
8	QA_ANALYST	13.33	45
9	REPORT_ANALYST	12.86	26
10	RISK_ANALYST	11.67	20
11	SAFETY_ANALYST	12.50	25
12	SAS_PROGRAMMER	14.00	28
13	SQL_DEVELOPER	13.75	27
14	STATISTICIAN	13.64	35
15	VALIDATION_LEAD	13.64	42

data merged;

    merge remote_fraud 

          role_summary;

    by Role;

run;

proc print data=merged;

run;

OUTPUT:

Obs	Employee_Name	Role	Region	Work_Mode	Employee_ID	Join_Date	Report_Date	Hours_Worked	Tasks_Completed	Communication_Frequency	Burnout_Score	Tenure_Months	Next_Review_Date	Review_Month	Productivity_Index	Utilization_Class	Fraud_Flag	Avg_Productivity	Avg_Burnout
1	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01JAN2026	7	9	4	22	44	24197	1	12.86	Medium	NO	12.86	22
2	Arjun	BI_ANALYST	india	Hybrid	105	17MAY2022	01FEB2026	7	9	4	22	44	24197	1	12.86	Medium	NO	12.86	22
3	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01JAN2026	9	13	7	30	55	24197	1	14.44	Medium	NO	14.44	30
4	Kavya	CLINICAL_ANALYST	india	Fully_Remote	106	10JUN2021	01FEB2026	9	13	7	30	55	24197	1	14.44	Medium	NO	14.44	30
5	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01JAN2026	9	12	6	32	48	24197	1	13.33	Medium	NO	13.33	32
6	Nithish	DATA_ANALYST	india	Fully_Remote	101	15JAN2022	01FEB2026	9	12	6	32	48	24197	1	13.33	Medium	NO	13.33	32
7	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01JAN2026	8	10	5	40	81	24197	1	12.50	Medium	NO	12.50	40
8	Sneha	DATA_MANAGER	uk	Fully_Remote	104	01APR2019	01FEB2026	8	10	5	40	81	24197	1	12.50	Medium	NO	12.50	40
9	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01JAN2026	10	14	8	38	87	24197	1	14.00	Medium	NO	14.00	38
10	Neha	DATA_SCIENTIST	usa	Fully_Remote	110	15OCT2018	01FEB2026	10	14	8	38	87	24197	1	14.00	Medium	NO	14.00	38
11	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01JAN2026	9	12	7	29	50	24197	1	13.33	Medium	NO	13.33	29
12	Suresh	ETL_DEVELOPER	india	Hybrid	111	01NOV2021	01FEB2026	9	12	7	29	50	24197	1	13.33	Medium	NO	13.33	29
13	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01JAN2026	10	14	8	33	47	24197	1	14.00	Medium	NO	14.00	33
14	Prasad	MACRO_DEVELOPER	india	Hybrid	114	14FEB2022	01FEB2026	10	14	8	33	47	24197	1	14.00	Medium	NO	14.00	33
15	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01JAN2026	12	16	10	45	66	24197	1	13.33	Medium	NO	13.33	45
16	Amit	QA_ANALYST	usa	Fully_Remote	107	05JUL2020	01FEB2026	12	16	10	45	66	24197	1	13.33	Medium	NO	13.33	45
17	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01JAN2026	7	9	5	26	61	24197	1	12.86	Medium	NO	12.86	26
18	Kiran	REPORT_ANALYST	india	Fully_Remote	112	20DEC2020	01FEB2026	7	9	5	26	61	24197	1	12.86	Medium	NO	12.86	26
19	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01JAN2026	6	7	3	20	77	24197	1	11.67	Medium	NO	11.67	20
20	Pooja	RISK_ANALYST	uk	Hybrid	108	18AUG2019	01FEB2026	6	7	3	20	77	24197	1	11.67	Medium	NO	11.67	20
21	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01JAN2026	8	10	6	25	58	24197	1	12.50	Medium	NO	12.50	25
22	Divya	SAFETY_ANALYST	india	Fully_Remote	115	30MAR2021	01FEB2026	8	10	6	25	58	24197	1	12.50	Medium	NO	12.50	25
23	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01JAN2026	10	14	8	28	59	24197	1	14.00	Medium	NO	14.00	28
24	Anjali	SAS_PROGRAMMER	india	Hybrid	102	12FEB2021	01FEB2026	10	14	8	28	59	24197	1	14.00	Medium	NO	14.00	28
25	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01JAN2026	8	11	6	27	40	24197	1	13.75	Medium	NO	13.75	27
26	Rakesh	SQL_DEVELOPER	india	Fully_Remote	109	01SEP2022	01FEB2026	8	11	6	27	40	24197	1	13.75	Medium	NO	13.75	27
27	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01JAN2026	11	15	9	35	70	24197	1	13.64	Medium	NO	13.64	35
28	Rahul	STATISTICIAN	usa	Fully_Remote	103	20MAR2020	01FEB2026	11	15	9	35	70	24197	1	13.64	Medium	NO	13.64	35
29	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01JAN2026	11	15	9	42	84	24197	1	13.64	Medium	NO	13.64	42
30	Meena	VALIDATION_LEAD	uk	Fully_Remote	113	05JAN2019	01FEB2026	11	15	9	42	84	24197	1	13.64	Medium	NO	13.64	42

18. PROC DATASETS CLEANUP

proc datasets library=work nolist;

    delete prod_t;

quit;

LOG:

NOTE: Deleting WORK.PROD_T (memtype=DATA).

18. BUSINESS INSIGHTS

 1. High productivity ≠ long hours
 2. Burnout strongly correlates with communication overload
 3. Fraud patterns visible through hour-task mismatch
 4. Utilization macro simplifies HR reporting

19. INTERVIEW TALKING POINTS

·       Why use INTCK vs INTNX

·       Macro vs Data Step logic

·       Fraud detection logic explanation

·       SQL vs PROC MEANS

·       Visualization choice

20. CONCLUSION

This project demonstrates real corporate SAS analytics, combining:

·       HR analytics

·       Productivity modeling

·       Fraud detection

·       Macro automation

·       Statistical validation

This project demonstrates a complete, real-world SAS analytics workflow for managing and monitoring remote employees. Starting from raw data creation, it applies data cleaning, date intelligence, character and numeric functions, macros, SQL, and statistical procedures to derive meaningful insights. Productivity and utilization are quantified using business-driven logic, while fraud detection rules highlight potential misuse of work hours. Procedures like PROC MEANS, PROC UNIVARIATE, PROC FREQ, PROC CORR, and PROC SGPLOT support evidence-based decision-making. Overall, the project reflects how SAS is effectively used in corporate environments for performance tracking, risk identification, and scalable, automated reporting.

INTERVIEW QUESTIONS FOR YOU

1.What is the difference between SET, MERGE, and PROC APPEND in SAS?

2.When would you prefer PROC SQL over DATA step in SAS?

3.What is the difference between INTCK and INTNX functions?

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About the Author:

SAS Learning Hub is a data analytics and SAS programming platform focused on clinical, financial, and real-world data analysis. The content is created by professionals with academic training in Pharmaceutics and hands-on experience in Base SAS, PROC SQL, Macros, SDTM, and ADaM, providing practical and industry-relevant SAS learning resources.

Disclaimer:

The datasets and analysis in this article are created for educational and demonstration purposes only. They do not represent REMOTE WORK data.

Our Mission:

This blog provides industry-focused SAS programming tutorials and analytics projects covering finance, healthcare, and technology.

This project is suitable for:

·  Students learning SAS

·  Data analysts building portfolios

·  Professionals preparing for SAS interviews

·  Bloggers writing about analytics and smart cities

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To deepen your understanding of SAS analytics, please refer to our other data science and industry-focused projects listed below:

1.Can SAS Analytics Decode the Real Impact of Robotics Innovations?

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