SlideShare a Scribd company logo
www.sanjivanimba.org.in
Unit No.3.
DECISION SCIENCE
Presented By:
Dr. V. M. Tidake
Ph. D (Financial Management), MBA(FM), MBA(HRM) BE(Chem)
Dean, EDP & Associate Professor MBA
1
Sanjivani College of Engineering, Kopargaon
Department of MBA
www.sanjivanimba.org.in
www.sanjivanimba.org.in
302-DECISION SCIENCE
Unit No.3 Marko Chain & Simulation
3.2.3 Case 1: Simulation
Presented By:
Dr. V. M. Tidake
Ph. D (Financial Management), MBA(FM), MBA(HRM) BE(Chem)
Dean EDP & Associate Professor MBA
2
Sanjivani College of Engineering, Kopargaon
Department of MBA
www.sanjivanimba.org.in
www.sanjivanimba.org.in
MARKOV CHAIN & SIMULATION
 At the End of the Session Student will be able to
understand-
A. Case 1: Simulation
www.sanjivanimba.org.in
SIMULATION
For the data about the inter arrival time of workers at a tool crib for
collecting the tools and the service time at the tool crib is as follows-
a. Percentage of time the attendant is idle
b. Average waiting time for the workers at the tool crib.
Use following Random Numbers:
For Inter Arrival Time: 10 21 56 74 47
For the Service Time: 65 59 02 71 26
Inter Arrival Time Service Time
Time in Minutes Frequency Time in Minutes Frequency
2 10 1 4
4 6 2 12
6 2 3 10
8 2 4 8
- - 5 6
www.sanjivanimba.org.in
SIMULATION
1) For Inter Arrival Time:
Time in
Minutes
Frequency Probability Cumulative
Probability
Random
Number Interval
2 10 10/20 = 0.50 0.50 00-49
4 6 06/20 = 0.30 0.80 50-79
6 2 02/20 = 0.10 0.90 80-89
8 2 02/20 = 0.10 1.00 90-99
www.sanjivanimba.org.in
SIMULATION
2) For Service Time:
Time in
Minutes
Frequency Probability Cumulative
Probability
Random
Number Interval
1 4 04/40 = 0.10 0.10 00-09
2 12 12/40 = 0.30 0.40 10-39
3 10 10/40 = 0.25 0.65 40-64
4 8 08/40 = 0.20 0.85 65-84
5 6 06/40 = 0.15 1.00 85-99
www.sanjivanimba.org.in
SIMULATION
Simulated Values:
Arrival
Number
Random
Number Inter
Arrival Time
(Simulated)
Inter Arrival
Time
Random
Number
Service Time
(Simulated)
Service Time
1 10 2 65 4
2 21 2 59 3
3 56 4 02 1
4 74 4 71 4
5 47 2 26 2
www.sanjivanimba.org.in
SIMULATION
a. Total Time for which Attendant is Present = 8.18-8.00 = 18 Minutes
% of Time for which Attendant is Idle = 4/18*100 = 22.22%
b. Total Waiting Time for 5 Workers = 5 Minutes
Average Waiting Time for a Worker = 5/5 = 1 Minute.
Arrival
Number
Inter
Arrival
Time
Service
Time
Arrival
Time
Service
Start
Time
Service
End
Time
Waiting
Time
Idle
Time
1 2 4 8.02 8.02 8.06 - 2
2 2 3 8.04 8.06 8.09 2 -
3 4 1 8.08 8.09 8.10 1 -
4 4 4 8.12 8.12 8.16 - 2
5 2 2 8.14 8.16 8.18 2 -
www.sanjivanimba.org.in
EXERCISE
 Solve the Case 1 on Simulation as a classroom
exercise.
www.sanjivanimba.org.in
For More Details Contact
Dr. V M Tidake
tidkevishal@gmail.com
tidkevishalmba@sanjivani.org.in
www.sanjivanimba.org.in
Thank You

More Related Content

What's hot

3.2.4 case 2 simulation
3.2.4 case 2 simulation3.2.4 case 2 simulation
3.2.4 case 2 simulation
Vishal Tidake
 
3.1.7 case 2 markov chain
3.1.7 case 2 markov chain3.1.7 case 2 markov chain
3.1.7 case 2 markov chain
Vishal Tidake
 
3.8 case 3 decision theory
3.8 case 3 decision theory3.8 case 3 decision theory
3.8 case 3 decision theory
Vishal Tidake
 
3.1.4 Steady State Probability
3.1.4 Steady State Probability3.1.4 Steady State Probability
3.1.4 Steady State Probability
Vishal Tidake
 
3.1.6 case 2 steady state probability in markov chain
3.1.6 case 2 steady state probability in markov chain3.1.6 case 2 steady state probability in markov chain
3.1.6 case 2 steady state probability in markov chain
Vishal Tidake
 
3.1.8 comenting markov chain
3.1.8 comenting markov chain3.1.8 comenting markov chain
3.1.8 comenting markov chain
Vishal Tidake
 
3.7 case 2 decision theory
3.7 case 2 decision theory3.7 case 2 decision theory
3.7 case 2 decision theory
Vishal Tidake
 
3.10 case 5 decision theory
3.10 case 5 decision theory3.10 case 5 decision theory
3.10 case 5 decision theory
Vishal Tidake
 
3.5 decion making under uncertainity
3.5 decion making under uncertainity3.5 decion making under uncertainity
3.5 decion making under uncertainity
Vishal Tidake
 
3.1 introduction decision theory
3.1 introduction decision theory3.1 introduction decision theory
3.1 introduction decision theory
Vishal Tidake
 
3.3 various decision models in decision theory
3.3 various decision models in decision theory3.3 various decision models in decision theory
3.3 various decision models in decision theory
Vishal Tidake
 
2.17 hungarian method explanatory case
2.17 hungarian method explanatory case2.17 hungarian method explanatory case
2.17 hungarian method explanatory case
Vishal Tidake
 
3.2 elements in decision theory
3.2 elements in decision theory3.2 elements in decision theory
3.2 elements in decision theory
Vishal Tidake
 
3.4 decision making under risk
3.4 decision making under risk3.4 decision making under risk
3.4 decision making under risk
Vishal Tidake
 
2.19 special case of unbalanced problem in assignment
2.19 special case of unbalanced problem in assignment2.19 special case of unbalanced problem in assignment
2.19 special case of unbalanced problem in assignment
Vishal Tidake
 
"How To Use Plato"
"How To Use Plato""How To Use Plato"
"How To Use Plato"
rozeka01
 
Semanco workshop Theme3 - Beams
Semanco workshop Theme3 - BeamsSemanco workshop Theme3 - Beams
Semanco workshop Theme3 - Beams
ARCSalle
 
2.21 special case of multiple solution in assignment
2.21 special case of multiple solution in assignment2.21 special case of multiple solution in assignment
2.21 special case of multiple solution in assignment
Vishal Tidake
 

What's hot (18)

3.2.4 case 2 simulation
3.2.4 case 2 simulation3.2.4 case 2 simulation
3.2.4 case 2 simulation
 
3.1.7 case 2 markov chain
3.1.7 case 2 markov chain3.1.7 case 2 markov chain
3.1.7 case 2 markov chain
 
3.8 case 3 decision theory
3.8 case 3 decision theory3.8 case 3 decision theory
3.8 case 3 decision theory
 
3.1.4 Steady State Probability
3.1.4 Steady State Probability3.1.4 Steady State Probability
3.1.4 Steady State Probability
 
3.1.6 case 2 steady state probability in markov chain
3.1.6 case 2 steady state probability in markov chain3.1.6 case 2 steady state probability in markov chain
3.1.6 case 2 steady state probability in markov chain
 
3.1.8 comenting markov chain
3.1.8 comenting markov chain3.1.8 comenting markov chain
3.1.8 comenting markov chain
 
3.7 case 2 decision theory
3.7 case 2 decision theory3.7 case 2 decision theory
3.7 case 2 decision theory
 
3.10 case 5 decision theory
3.10 case 5 decision theory3.10 case 5 decision theory
3.10 case 5 decision theory
 
3.5 decion making under uncertainity
3.5 decion making under uncertainity3.5 decion making under uncertainity
3.5 decion making under uncertainity
 
3.1 introduction decision theory
3.1 introduction decision theory3.1 introduction decision theory
3.1 introduction decision theory
 
3.3 various decision models in decision theory
3.3 various decision models in decision theory3.3 various decision models in decision theory
3.3 various decision models in decision theory
 
2.17 hungarian method explanatory case
2.17 hungarian method explanatory case2.17 hungarian method explanatory case
2.17 hungarian method explanatory case
 
3.2 elements in decision theory
3.2 elements in decision theory3.2 elements in decision theory
3.2 elements in decision theory
 
3.4 decision making under risk
3.4 decision making under risk3.4 decision making under risk
3.4 decision making under risk
 
2.19 special case of unbalanced problem in assignment
2.19 special case of unbalanced problem in assignment2.19 special case of unbalanced problem in assignment
2.19 special case of unbalanced problem in assignment
 
"How To Use Plato"
"How To Use Plato""How To Use Plato"
"How To Use Plato"
 
Semanco workshop Theme3 - Beams
Semanco workshop Theme3 - BeamsSemanco workshop Theme3 - Beams
Semanco workshop Theme3 - Beams
 
2.21 special case of multiple solution in assignment
2.21 special case of multiple solution in assignment2.21 special case of multiple solution in assignment
2.21 special case of multiple solution in assignment
 

Similar to 3.2.3 case 1 simulation

4.11 case 1 determination of float & slack in cpm network calculations
4.11 case 1 determination of float & slack in cpm network calculations4.11 case 1 determination of float & slack in cpm network calculations
4.11 case 1 determination of float & slack in cpm network calculations
Vishal Tidake
 
Tomorrow SEMINAR OR.pptx
Tomorrow SEMINAR OR.pptxTomorrow SEMINAR OR.pptx
Tomorrow SEMINAR OR.pptx
TANVEERSINGHSOLANKI
 
Semar mesem presentasi g qcc season 4
Semar mesem presentasi g qcc season 4Semar mesem presentasi g qcc season 4
Semar mesem presentasi g qcc season 4
Arsyah El Kahfi
 
Dual-Band Mobile Phone Jammer
Dual-Band Mobile Phone JammerDual-Band Mobile Phone Jammer
Dual-Band Mobile Phone Jammer
Mohamed Atef
 
Counting What Counts in Contact Centers - Service Level
Counting What Counts in Contact Centers - Service LevelCounting What Counts in Contact Centers - Service Level
Counting What Counts in Contact Centers - Service Level
Hilario Fiandeiro
 
Simulation Project Report
Simulation Project ReportSimulation Project Report
Simulation Project Report
Jasmine Sachdeva
 
Simulation in Operation Research
Simulation in Operation ResearchSimulation in Operation Research
Simulation in Operation Research
Yamini Kahaliya
 
Electrónica: Análisis, diseño y construcción de filtros activos”
Electrónica: Análisis, diseño y construcción de filtros activos”Electrónica: Análisis, diseño y construcción de filtros activos”
Electrónica: Análisis, diseño y construcción de filtros activos”
SANTIAGO PABLO ALBERTO
 
IRJET- A Case Study Approach of Quality Tools in Manufacturing Industry
IRJET- A Case Study Approach of Quality Tools in Manufacturing IndustryIRJET- A Case Study Approach of Quality Tools in Manufacturing Industry
IRJET- A Case Study Approach of Quality Tools in Manufacturing Industry
IRJET Journal
 
Line Balancing In Garments Industry
Line Balancing In Garments IndustryLine Balancing In Garments Industry
Line Balancing In Garments Industry
Md. Mazadul Hasan Shishir
 
Mohamed Ahmed Afifi (16-2179) Master Thesis
Mohamed Ahmed Afifi (16-2179) Master ThesisMohamed Ahmed Afifi (16-2179) Master Thesis
Mohamed Ahmed Afifi (16-2179) Master Thesis
Mohamed Ahmed Afifi
 
CIM report - final
CIM report - finalCIM report - final
CIM report - final
Saurabh Dhuri
 
CIM report - final
CIM report - finalCIM report - final
CIM report - final
Praveen S R
 
CIM Report
CIM ReportCIM Report
CIM Report
Deepak Chandran
 
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian ApproachAutomatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
Spark Summit
 
Light Control System to Save Electricity
Light Control System to Save ElectricityLight Control System to Save Electricity
Light Control System to Save Electricity
MuhammadZain182
 
Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]
Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]
Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]
Friso de Jong
 
Constraint Management, operations management.ppt
Constraint Management, operations management.pptConstraint Management, operations management.ppt
Constraint Management, operations management.ppt
PratyushKumar908783
 
A012430106
A012430106A012430106
A012430106
IOSR Journals
 
computer notes - Data Structures - 10
computer notes - Data Structures - 10computer notes - Data Structures - 10
computer notes - Data Structures - 10
ecomputernotes
 

Similar to 3.2.3 case 1 simulation (20)

4.11 case 1 determination of float & slack in cpm network calculations
4.11 case 1 determination of float & slack in cpm network calculations4.11 case 1 determination of float & slack in cpm network calculations
4.11 case 1 determination of float & slack in cpm network calculations
 
Tomorrow SEMINAR OR.pptx
Tomorrow SEMINAR OR.pptxTomorrow SEMINAR OR.pptx
Tomorrow SEMINAR OR.pptx
 
Semar mesem presentasi g qcc season 4
Semar mesem presentasi g qcc season 4Semar mesem presentasi g qcc season 4
Semar mesem presentasi g qcc season 4
 
Dual-Band Mobile Phone Jammer
Dual-Band Mobile Phone JammerDual-Band Mobile Phone Jammer
Dual-Band Mobile Phone Jammer
 
Counting What Counts in Contact Centers - Service Level
Counting What Counts in Contact Centers - Service LevelCounting What Counts in Contact Centers - Service Level
Counting What Counts in Contact Centers - Service Level
 
Simulation Project Report
Simulation Project ReportSimulation Project Report
Simulation Project Report
 
Simulation in Operation Research
Simulation in Operation ResearchSimulation in Operation Research
Simulation in Operation Research
 
Electrónica: Análisis, diseño y construcción de filtros activos”
Electrónica: Análisis, diseño y construcción de filtros activos”Electrónica: Análisis, diseño y construcción de filtros activos”
Electrónica: Análisis, diseño y construcción de filtros activos”
 
IRJET- A Case Study Approach of Quality Tools in Manufacturing Industry
IRJET- A Case Study Approach of Quality Tools in Manufacturing IndustryIRJET- A Case Study Approach of Quality Tools in Manufacturing Industry
IRJET- A Case Study Approach of Quality Tools in Manufacturing Industry
 
Line Balancing In Garments Industry
Line Balancing In Garments IndustryLine Balancing In Garments Industry
Line Balancing In Garments Industry
 
Mohamed Ahmed Afifi (16-2179) Master Thesis
Mohamed Ahmed Afifi (16-2179) Master ThesisMohamed Ahmed Afifi (16-2179) Master Thesis
Mohamed Ahmed Afifi (16-2179) Master Thesis
 
CIM report - final
CIM report - finalCIM report - final
CIM report - final
 
CIM report - final
CIM report - finalCIM report - final
CIM report - final
 
CIM Report
CIM ReportCIM Report
CIM Report
 
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian ApproachAutomatic Features Generation And Model Training On Spark: A Bayesian Approach
Automatic Features Generation And Model Training On Spark: A Bayesian Approach
 
Light Control System to Save Electricity
Light Control System to Save ElectricityLight Control System to Save Electricity
Light Control System to Save Electricity
 
Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]
Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]
Cen Isss Workshop On Cyber Identity Cwa Cid V1.8[1]
 
Constraint Management, operations management.ppt
Constraint Management, operations management.pptConstraint Management, operations management.ppt
Constraint Management, operations management.ppt
 
A012430106
A012430106A012430106
A012430106
 
computer notes - Data Structures - 10
computer notes - Data Structures - 10computer notes - Data Structures - 10
computer notes - Data Structures - 10
 

More from Vishal Tidake

Working Capital Management.pptx
Working Capital Management.pptxWorking Capital Management.pptx
Working Capital Management.pptx
Vishal Tidake
 
Cash Flow Statement.pptx
Cash Flow Statement.pptxCash Flow Statement.pptx
Cash Flow Statement.pptx
Vishal Tidake
 
2.9 Fund Flow Statement.pptx
2.9 Fund Flow Statement.pptx2.9 Fund Flow Statement.pptx
2.9 Fund Flow Statement.pptx
Vishal Tidake
 
Ratio Analysis.pptx
Ratio Analysis.pptxRatio Analysis.pptx
Ratio Analysis.pptx
Vishal Tidake
 
Chapter 1- Environment of Business Finance.pptx
Chapter 1- Environment of Business Finance.pptxChapter 1- Environment of Business Finance.pptx
Chapter 1- Environment of Business Finance.pptx
Vishal Tidake
 
1.6 key strategies of financial management
1.6 key strategies of financial management1.6 key strategies of financial management
1.6 key strategies of financial management
Vishal Tidake
 
1.5 a's of financial management
1.5 a's of financial management1.5 a's of financial management
1.5 a's of financial management
Vishal Tidake
 
1.4 functions of financial management
1.4 functions of financial management1.4 functions of financial management
1.4 functions of financial management
Vishal Tidake
 
1.3 approaches to finance
1.3 approaches to finance1.3 approaches to finance
1.3 approaches to finance
Vishal Tidake
 
1.2 introduction to financial management
1.2 introduction to financial management1.2 introduction to financial management
1.2 introduction to financial management
Vishal Tidake
 
1.1 introduction to finance
1.1 introduction to finance1.1 introduction to finance
1.1 introduction to finance
Vishal Tidake
 
Accounting standards notes Dr. V M Tidake
Accounting standards notes Dr. V M TidakeAccounting standards notes Dr. V M Tidake
Accounting standards notes Dr. V M Tidake
Vishal Tidake
 
5.2.9 case 1 probability distribution
5.2.9 case 1 probability distribution5.2.9 case 1 probability distribution
5.2.9 case 1 probability distribution
Vishal Tidake
 
5.2.8 case 2 normal probability distribution
5.2.8 case 2 normal probability distribution5.2.8 case 2 normal probability distribution
5.2.8 case 2 normal probability distribution
Vishal Tidake
 
5.2.7 case 1 normal probability distribution
5.2.7 case 1 normal probability distribution5.2.7 case 1 normal probability distribution
5.2.7 case 1 normal probability distribution
Vishal Tidake
 
5.2.6 case 1 poisson probability distribution
5.2.6 case 1 poisson probability distribution5.2.6 case 1 poisson probability distribution
5.2.6 case 1 poisson probability distribution
Vishal Tidake
 
5.2.5 case 2 binomial probability distribution
5.2.5 case 2 binomial probability distribution5.2.5 case 2 binomial probability distribution
5.2.5 case 2 binomial probability distribution
Vishal Tidake
 
5.2.4 case 1 binomial probability distribution
5.2.4 case 1 binomial probability distribution5.2.4 case 1 binomial probability distribution
5.2.4 case 1 binomial probability distribution
Vishal Tidake
 
5.10 case 7 probability
5.10 case 7 probability5.10 case 7 probability
5.10 case 7 probability
Vishal Tidake
 
5.9 case 6 probability
5.9 case 6 probability5.9 case 6 probability
5.9 case 6 probability
Vishal Tidake
 

More from Vishal Tidake (20)

Working Capital Management.pptx
Working Capital Management.pptxWorking Capital Management.pptx
Working Capital Management.pptx
 
Cash Flow Statement.pptx
Cash Flow Statement.pptxCash Flow Statement.pptx
Cash Flow Statement.pptx
 
2.9 Fund Flow Statement.pptx
2.9 Fund Flow Statement.pptx2.9 Fund Flow Statement.pptx
2.9 Fund Flow Statement.pptx
 
Ratio Analysis.pptx
Ratio Analysis.pptxRatio Analysis.pptx
Ratio Analysis.pptx
 
Chapter 1- Environment of Business Finance.pptx
Chapter 1- Environment of Business Finance.pptxChapter 1- Environment of Business Finance.pptx
Chapter 1- Environment of Business Finance.pptx
 
1.6 key strategies of financial management
1.6 key strategies of financial management1.6 key strategies of financial management
1.6 key strategies of financial management
 
1.5 a's of financial management
1.5 a's of financial management1.5 a's of financial management
1.5 a's of financial management
 
1.4 functions of financial management
1.4 functions of financial management1.4 functions of financial management
1.4 functions of financial management
 
1.3 approaches to finance
1.3 approaches to finance1.3 approaches to finance
1.3 approaches to finance
 
1.2 introduction to financial management
1.2 introduction to financial management1.2 introduction to financial management
1.2 introduction to financial management
 
1.1 introduction to finance
1.1 introduction to finance1.1 introduction to finance
1.1 introduction to finance
 
Accounting standards notes Dr. V M Tidake
Accounting standards notes Dr. V M TidakeAccounting standards notes Dr. V M Tidake
Accounting standards notes Dr. V M Tidake
 
5.2.9 case 1 probability distribution
5.2.9 case 1 probability distribution5.2.9 case 1 probability distribution
5.2.9 case 1 probability distribution
 
5.2.8 case 2 normal probability distribution
5.2.8 case 2 normal probability distribution5.2.8 case 2 normal probability distribution
5.2.8 case 2 normal probability distribution
 
5.2.7 case 1 normal probability distribution
5.2.7 case 1 normal probability distribution5.2.7 case 1 normal probability distribution
5.2.7 case 1 normal probability distribution
 
5.2.6 case 1 poisson probability distribution
5.2.6 case 1 poisson probability distribution5.2.6 case 1 poisson probability distribution
5.2.6 case 1 poisson probability distribution
 
5.2.5 case 2 binomial probability distribution
5.2.5 case 2 binomial probability distribution5.2.5 case 2 binomial probability distribution
5.2.5 case 2 binomial probability distribution
 
5.2.4 case 1 binomial probability distribution
5.2.4 case 1 binomial probability distribution5.2.4 case 1 binomial probability distribution
5.2.4 case 1 binomial probability distribution
 
5.10 case 7 probability
5.10 case 7 probability5.10 case 7 probability
5.10 case 7 probability
 
5.9 case 6 probability
5.9 case 6 probability5.9 case 6 probability
5.9 case 6 probability
 

Recently uploaded

06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
Timothy Spann
 
DSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelinesDSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelines
Timothy Spann
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
nuttdpt
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
apvysm8
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
Timothy Spann
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Fernanda Palhano
 
State of Artificial intelligence Report 2023
State of Artificial intelligence Report 2023State of Artificial intelligence Report 2023
State of Artificial intelligence Report 2023
kuntobimo2016
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
jerlynmaetalle
 
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
bopyb
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
roli9797
 
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
nyfuhyz
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
javier ramirez
 
University of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma TranscriptUniversity of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma Transcript
soxrziqu
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
nuttdpt
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
Social Samosa
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
AndrzejJarynowski
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Kiwi Creative
 
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI LicensingA presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
AlessioFois2
 
Population Growth in Bataan: The effects of population growth around rural pl...
Population Growth in Bataan: The effects of population growth around rural pl...Population Growth in Bataan: The effects of population growth around rural pl...
Population Growth in Bataan: The effects of population growth around rural pl...
Bill641377
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
manishkhaire30
 

Recently uploaded (20)

06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
 
DSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelinesDSSML24_tspann_CodelessGenerativeAIPipelines
DSSML24_tspann_CodelessGenerativeAIPipelines
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
 
State of Artificial intelligence Report 2023
State of Artificial intelligence Report 2023State of Artificial intelligence Report 2023
State of Artificial intelligence Report 2023
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
 
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
 
Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
 
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
 
University of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma TranscriptUniversity of New South Wales degree offer diploma Transcript
University of New South Wales degree offer diploma Transcript
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
 
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI LicensingA presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
 
Population Growth in Bataan: The effects of population growth around rural pl...
Population Growth in Bataan: The effects of population growth around rural pl...Population Growth in Bataan: The effects of population growth around rural pl...
Population Growth in Bataan: The effects of population growth around rural pl...
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
 

3.2.3 case 1 simulation