SlideShare a Scribd company logo
10 SQL SERVER: DOINGCALCULATIONS WITH FUNCTIONS
Mathematical Functions Can mathematical functions be used on my tables? 	Yes. Microsoft SQL Server 2008 provides several mathematical functions such as sum(col), avg(col), min(col), max(col), count(col) etc. In SQL, they are referred to as aggregate functions as they work upon aggregates of rows. Functions Explained: Sum(fieldName): Find the sum of field values of all records Avg(fieldName): Find the average of field values of all records Min(fieldName): Find the minimum of the field values of all records Max(fieldName): Find the maximum of the field values of all records Count(fieldName): Find the number of field values in the table records
Mathematical Functions Consider an Interpol database which contains a table of the biggest robberies that took place this year, all around the world. Now, lets look into the application of math functions over this table.
Mathematical Functions 1. Find the TOTAL booty of all the robberies: Select sum(booty) from robberies; 2. Find the Average booty of all the robberies: Select avg(booty) from robberies; 3. Find the robbery with the maximal booty Select max(booty) from robberies; 4. Find the robbery with the minimal booty Select min(booty) from robberies; 5. Find the number of robbery cases: Select count(booty) from robberies;
Using as condition HEY??? I CANNOT USE THESE FUNCTIONS WITH MY ‘WHERE’ CONDITION??? Microsoft SQL Server 2008 restricts the user to use these functions with ‘WHERE’ conditions. Therefore, to solve our problem three keywords: ‘having’, ‘any’ and ‘in’ select * from tablename having <condition>; select * from tablename where colname=any(cond); select * from tablename where colname in (condition);
Advanced Aggregates IS THERE ANY OTHER MODIFICATION TO THESE FUNCTIONS? 	We can combine these functions with ‘group by’ function for better results. select sum(col1),col2 from tablename group by col2; The above command will find out the sum of each group from column 2  More than one aggregate functions can be used simultaneously, seperated by commas. Eg: select sum(col1), count(col1) from tablename; Consider the example in the next slide.
Advanced Aggregates Consider an employee table: Find the Number of Employees working in each department: Select count(empid), depid from employee; Result:
Additional Functions ,[object Object],Converts the value of fieldName to upper case. Can be used with strings. ,[object Object],Converts the value of fieldName to lowercase. Can be used with strings.
Summary 10. Doing Calculations with functions ,[object Object]
Avg

More Related Content

What's hot

Lesson9
Lesson9Lesson9
random forest regression
random forest regressionrandom forest regression
random forest regression
Akhilesh Joshi
 
Mapreduce: Theory and implementation
Mapreduce: Theory and implementationMapreduce: Theory and implementation
Mapreduce: Theory and implementationSri Prasanna
 
Excel/R
Excel/RExcel/R
multiple linear regression
multiple linear regressionmultiple linear regression
multiple linear regression
Akhilesh Joshi
 
simple linear regression
simple linear regressionsimple linear regression
simple linear regression
Akhilesh Joshi
 
decision tree regression
decision tree regressiondecision tree regression
decision tree regression
Akhilesh Joshi
 
PART 6: FROM GEO INTO YOUR REPORT
PART 6: FROM GEO INTO YOUR REPORTPART 6: FROM GEO INTO YOUR REPORT
PART 6: FROM GEO INTO YOUR REPORT
Andrea Antonello
 
Sql FUNCTIONS
Sql FUNCTIONSSql FUNCTIONS
Sql FUNCTIONS
Abrar ali
 
c++ programming Unit 4 operators
c++ programming Unit 4 operatorsc++ programming Unit 4 operators
c++ programming Unit 4 operators
AAKASH KUMAR
 
Stack linked list
Stack linked listStack linked list
Stack linked listbhargav0077
 
Presentation topic is stick data structure
Presentation topic is stick data structurePresentation topic is stick data structure
Presentation topic is stick data structure
AizazAli21
 
polynomial linear regression
polynomial linear regressionpolynomial linear regression
polynomial linear regression
Akhilesh Joshi
 
knn classification
knn classificationknn classification
knn classification
Akhilesh Joshi
 
PART 3: THE SCRIPTING COMPOSER AND PYTHON
PART 3: THE SCRIPTING COMPOSER AND PYTHONPART 3: THE SCRIPTING COMPOSER AND PYTHON
PART 3: THE SCRIPTING COMPOSER AND PYTHON
Andrea Antonello
 
PART 4: GEOGRAPHIC SCRIPTING
PART 4: GEOGRAPHIC SCRIPTINGPART 4: GEOGRAPHIC SCRIPTING
PART 4: GEOGRAPHIC SCRIPTING
Andrea Antonello
 

What's hot (19)

Lesson9
Lesson9Lesson9
Lesson9
 
random forest regression
random forest regressionrandom forest regression
random forest regression
 
Mapreduce: Theory and implementation
Mapreduce: Theory and implementationMapreduce: Theory and implementation
Mapreduce: Theory and implementation
 
Excel/R
Excel/RExcel/R
Excel/R
 
multiple linear regression
multiple linear regressionmultiple linear regression
multiple linear regression
 
simple linear regression
simple linear regressionsimple linear regression
simple linear regression
 
decision tree regression
decision tree regressiondecision tree regression
decision tree regression
 
PART 6: FROM GEO INTO YOUR REPORT
PART 6: FROM GEO INTO YOUR REPORTPART 6: FROM GEO INTO YOUR REPORT
PART 6: FROM GEO INTO YOUR REPORT
 
Sql FUNCTIONS
Sql FUNCTIONSSql FUNCTIONS
Sql FUNCTIONS
 
c++ programming Unit 4 operators
c++ programming Unit 4 operatorsc++ programming Unit 4 operators
c++ programming Unit 4 operators
 
Stack linked list
Stack linked listStack linked list
Stack linked list
 
R-Excel Integration
R-Excel IntegrationR-Excel Integration
R-Excel Integration
 
Presentation topic is stick data structure
Presentation topic is stick data structurePresentation topic is stick data structure
Presentation topic is stick data structure
 
polynomial linear regression
polynomial linear regressionpolynomial linear regression
polynomial linear regression
 
knn classification
knn classificationknn classification
knn classification
 
PART 3: THE SCRIPTING COMPOSER AND PYTHON
PART 3: THE SCRIPTING COMPOSER AND PYTHONPART 3: THE SCRIPTING COMPOSER AND PYTHON
PART 3: THE SCRIPTING COMPOSER AND PYTHON
 
PART 4: GEOGRAPHIC SCRIPTING
PART 4: GEOGRAPHIC SCRIPTINGPART 4: GEOGRAPHIC SCRIPTING
PART 4: GEOGRAPHIC SCRIPTING
 
Java Week6(B) Notepad
Java Week6(B)   NotepadJava Week6(B)   Notepad
Java Week6(B) Notepad
 
V22 function-1
V22 function-1V22 function-1
V22 function-1
 

Viewers also liked

MS SQL SERVER: Feeding Data Into Database
MS SQL SERVER: Feeding Data Into DatabaseMS SQL SERVER: Feeding Data Into Database
MS SQL SERVER: Feeding Data Into Database
sqlserver content
 
MS Sql Server: Reporting basics
MS Sql  Server: Reporting basicsMS Sql  Server: Reporting basics
MS Sql Server: Reporting basics
sqlserver content
 
MS Sql Server: Reporting introduction
MS Sql Server: Reporting introductionMS Sql Server: Reporting introduction
MS Sql Server: Reporting introduction
sqlserver content
 
MS SQLSERVER:Doing Calculations With Functions
MS SQLSERVER:Doing Calculations With FunctionsMS SQLSERVER:Doing Calculations With Functions
MS SQLSERVER:Doing Calculations With Functions
sqlserver content
 
MS SQL SERVER: Getting Started With Sql Server 2008
MS SQL SERVER: Getting Started With Sql Server 2008MS SQL SERVER: Getting Started With Sql Server 2008
MS SQL SERVER: Getting Started With Sql Server 2008
sqlserver content
 
MS SQL SERVER: Creating A Database
MS SQL SERVER: Creating A DatabaseMS SQL SERVER: Creating A Database
MS SQL SERVER: Creating A Database
sqlserver content
 
Control Flow Using SSIS
Control Flow Using SSISControl Flow Using SSIS
Control Flow Using SSIS
Ram Kedem
 
SQL Server 2012 and SharePoint 2010: Reporting Nirvana
SQL Server 2012 and SharePoint 2010: Reporting NirvanaSQL Server 2012 and SharePoint 2010: Reporting Nirvana
SQL Server 2012 and SharePoint 2010: Reporting Nirvana
Randy Williams
 
SSRS integration with share point
SSRS integration with share pointSSRS integration with share point
SSRS integration with share point
Jacob Chang
 
Scrum sử dụng Team Foundation Server 2012
Scrum sử dụng Team Foundation Server 2012Scrum sử dụng Team Foundation Server 2012
Scrum sử dụng Team Foundation Server 2012
Quang Nguyễn Bá
 
Data Warehouse Design Considerations
Data Warehouse Design ConsiderationsData Warehouse Design Considerations
Data Warehouse Design Considerations
Ram Kedem
 
SSIS Basic Data Flow
SSIS Basic Data FlowSSIS Basic Data Flow
SSIS Basic Data Flow
Ram Kedem
 
Introduction to Microsoft SQL Server 2008 R2 Analysis Service
Introduction to Microsoft SQL Server 2008 R2 Analysis ServiceIntroduction to Microsoft SQL Server 2008 R2 Analysis Service
Introduction to Microsoft SQL Server 2008 R2 Analysis ServiceQuang Nguyễn Bá
 
Data Warehouse Basics
Data Warehouse BasicsData Warehouse Basics
Data Warehouse Basics
Ram Kedem
 
SSIS Incremental ETL process
SSIS Incremental ETL processSSIS Incremental ETL process
SSIS Incremental ETL process
Ram Kedem
 
Introduction to Business Intelligence in Microsoft SQL Server 2008 R2
Introduction to Business Intelligence in Microsoft SQL Server 2008 R2Introduction to Business Intelligence in Microsoft SQL Server 2008 R2
Introduction to Business Intelligence in Microsoft SQL Server 2008 R2Quang Nguyễn Bá
 
TDD - Test Driven Dvelopment | Test First Design
TDD -  Test Driven Dvelopment | Test First DesignTDD -  Test Driven Dvelopment | Test First Design
TDD - Test Driven Dvelopment | Test First Design
Quang Nguyễn Bá
 
Building SSRS 2008 large scale solutions
Building SSRS 2008 large scale solutionsBuilding SSRS 2008 large scale solutions
Building SSRS 2008 large scale solutions
Denny Lee
 
MS SQLSERVER:Manipulating Database
MS SQLSERVER:Manipulating DatabaseMS SQLSERVER:Manipulating Database
MS SQLSERVER:Manipulating Database
sqlserver content
 
Introduction to Microsoft SQL Server 2008 R2 Integration Services
Introduction to Microsoft SQL Server 2008 R2 Integration ServicesIntroduction to Microsoft SQL Server 2008 R2 Integration Services
Introduction to Microsoft SQL Server 2008 R2 Integration ServicesQuang Nguyễn Bá
 

Viewers also liked (20)

MS SQL SERVER: Feeding Data Into Database
MS SQL SERVER: Feeding Data Into DatabaseMS SQL SERVER: Feeding Data Into Database
MS SQL SERVER: Feeding Data Into Database
 
MS Sql Server: Reporting basics
MS Sql  Server: Reporting basicsMS Sql  Server: Reporting basics
MS Sql Server: Reporting basics
 
MS Sql Server: Reporting introduction
MS Sql Server: Reporting introductionMS Sql Server: Reporting introduction
MS Sql Server: Reporting introduction
 
MS SQLSERVER:Doing Calculations With Functions
MS SQLSERVER:Doing Calculations With FunctionsMS SQLSERVER:Doing Calculations With Functions
MS SQLSERVER:Doing Calculations With Functions
 
MS SQL SERVER: Getting Started With Sql Server 2008
MS SQL SERVER: Getting Started With Sql Server 2008MS SQL SERVER: Getting Started With Sql Server 2008
MS SQL SERVER: Getting Started With Sql Server 2008
 
MS SQL SERVER: Creating A Database
MS SQL SERVER: Creating A DatabaseMS SQL SERVER: Creating A Database
MS SQL SERVER: Creating A Database
 
Control Flow Using SSIS
Control Flow Using SSISControl Flow Using SSIS
Control Flow Using SSIS
 
SQL Server 2012 and SharePoint 2010: Reporting Nirvana
SQL Server 2012 and SharePoint 2010: Reporting NirvanaSQL Server 2012 and SharePoint 2010: Reporting Nirvana
SQL Server 2012 and SharePoint 2010: Reporting Nirvana
 
SSRS integration with share point
SSRS integration with share pointSSRS integration with share point
SSRS integration with share point
 
Scrum sử dụng Team Foundation Server 2012
Scrum sử dụng Team Foundation Server 2012Scrum sử dụng Team Foundation Server 2012
Scrum sử dụng Team Foundation Server 2012
 
Data Warehouse Design Considerations
Data Warehouse Design ConsiderationsData Warehouse Design Considerations
Data Warehouse Design Considerations
 
SSIS Basic Data Flow
SSIS Basic Data FlowSSIS Basic Data Flow
SSIS Basic Data Flow
 
Introduction to Microsoft SQL Server 2008 R2 Analysis Service
Introduction to Microsoft SQL Server 2008 R2 Analysis ServiceIntroduction to Microsoft SQL Server 2008 R2 Analysis Service
Introduction to Microsoft SQL Server 2008 R2 Analysis Service
 
Data Warehouse Basics
Data Warehouse BasicsData Warehouse Basics
Data Warehouse Basics
 
SSIS Incremental ETL process
SSIS Incremental ETL processSSIS Incremental ETL process
SSIS Incremental ETL process
 
Introduction to Business Intelligence in Microsoft SQL Server 2008 R2
Introduction to Business Intelligence in Microsoft SQL Server 2008 R2Introduction to Business Intelligence in Microsoft SQL Server 2008 R2
Introduction to Business Intelligence in Microsoft SQL Server 2008 R2
 
TDD - Test Driven Dvelopment | Test First Design
TDD -  Test Driven Dvelopment | Test First DesignTDD -  Test Driven Dvelopment | Test First Design
TDD - Test Driven Dvelopment | Test First Design
 
Building SSRS 2008 large scale solutions
Building SSRS 2008 large scale solutionsBuilding SSRS 2008 large scale solutions
Building SSRS 2008 large scale solutions
 
MS SQLSERVER:Manipulating Database
MS SQLSERVER:Manipulating DatabaseMS SQLSERVER:Manipulating Database
MS SQLSERVER:Manipulating Database
 
Introduction to Microsoft SQL Server 2008 R2 Integration Services
Introduction to Microsoft SQL Server 2008 R2 Integration ServicesIntroduction to Microsoft SQL Server 2008 R2 Integration Services
Introduction to Microsoft SQL Server 2008 R2 Integration Services
 

Similar to MS SQL SERVER: Doing Calculations With Functions

2. mathematical functions in excel
2. mathematical functions in excel2. mathematical functions in excel
2. mathematical functions in excel
Dr. Prashant Vats
 
database_set_operations_&_function.pptx
database_set_operations_&_function.pptxdatabase_set_operations_&_function.pptx
database_set_operations_&_function.pptx
tanvirkhanfahim
 
Introduction to oracle functions
Introduction to oracle functionsIntroduction to oracle functions
Introduction to oracle functions
Nitesh Singh
 
Chapter9 more on database and sql
Chapter9 more on database and sqlChapter9 more on database and sql
Chapter9 more on database and sql
KV(AFS) Utarlai, Barmer (Rajasthan)
 
Ms excel commands
Ms excel commandsMs excel commands
Ms excel commands
DiyaVerma14
 
Intro to tsql unit 10
Intro to tsql   unit 10Intro to tsql   unit 10
Intro to tsql unit 10Syed Asrarali
 
Data Transformation
Data TransformationData Transformation
Data Transformation
ArmanArafatAnik
 
Structured query language(sql)
Structured query language(sql)Structured query language(sql)
Structured query language(sql)
Huda Alameen
 
My SQL.pptx
My SQL.pptxMy SQL.pptx
My SQL.pptx
KieveBarreto1
 
C++
C++C++
The Ring programming language version 1.8 book - Part 94 of 202
The Ring programming language version 1.8 book - Part 94 of 202The Ring programming language version 1.8 book - Part 94 of 202
The Ring programming language version 1.8 book - Part 94 of 202
Mahmoud Samir Fayed
 
Sql Queries
Sql QueriesSql Queries
Sql Querieswebicon
 
ADVANCE ITT BY PRASAD
ADVANCE ITT BY PRASADADVANCE ITT BY PRASAD
ADVANCE ITT BY PRASAD
PADYALAMAITHILINATHA
 
The Ring programming language version 1.5.2 book - Part 175 of 181
The Ring programming language version 1.5.2 book - Part 175 of 181The Ring programming language version 1.5.2 book - Part 175 of 181
The Ring programming language version 1.5.2 book - Part 175 of 181
Mahmoud Samir Fayed
 
MySQL-commands.pdf
MySQL-commands.pdfMySQL-commands.pdf
MySQL-commands.pdf
ssuserc5aa74
 
Advance excel
Advance excelAdvance excel
Advance excel
SiddheshHadge
 

Similar to MS SQL SERVER: Doing Calculations With Functions (20)

2. mathematical functions in excel
2. mathematical functions in excel2. mathematical functions in excel
2. mathematical functions in excel
 
Introduction to Oracle Functions--(SQL)--Abhishek Sharma
Introduction to Oracle Functions--(SQL)--Abhishek SharmaIntroduction to Oracle Functions--(SQL)--Abhishek Sharma
Introduction to Oracle Functions--(SQL)--Abhishek Sharma
 
database_set_operations_&_function.pptx
database_set_operations_&_function.pptxdatabase_set_operations_&_function.pptx
database_set_operations_&_function.pptx
 
Introduction to oracle functions
Introduction to oracle functionsIntroduction to oracle functions
Introduction to oracle functions
 
Chapter9 more on database and sql
Chapter9 more on database and sqlChapter9 more on database and sql
Chapter9 more on database and sql
 
Ms excel commands
Ms excel commandsMs excel commands
Ms excel commands
 
Intro to tsql unit 10
Intro to tsql   unit 10Intro to tsql   unit 10
Intro to tsql unit 10
 
Data Transformation
Data TransformationData Transformation
Data Transformation
 
Structured query language(sql)
Structured query language(sql)Structured query language(sql)
Structured query language(sql)
 
My SQL.pptx
My SQL.pptxMy SQL.pptx
My SQL.pptx
 
C++
C++C++
C++
 
Mysql1
Mysql1Mysql1
Mysql1
 
The Ring programming language version 1.8 book - Part 94 of 202
The Ring programming language version 1.8 book - Part 94 of 202The Ring programming language version 1.8 book - Part 94 of 202
The Ring programming language version 1.8 book - Part 94 of 202
 
Sql Queries
Sql QueriesSql Queries
Sql Queries
 
Sql wksht-3
Sql wksht-3Sql wksht-3
Sql wksht-3
 
ADVANCE ITT BY PRASAD
ADVANCE ITT BY PRASADADVANCE ITT BY PRASAD
ADVANCE ITT BY PRASAD
 
The Ring programming language version 1.5.2 book - Part 175 of 181
The Ring programming language version 1.5.2 book - Part 175 of 181The Ring programming language version 1.5.2 book - Part 175 of 181
The Ring programming language version 1.5.2 book - Part 175 of 181
 
MySQL-commands.pdf
MySQL-commands.pdfMySQL-commands.pdf
MySQL-commands.pdf
 
Advance excel
Advance excelAdvance excel
Advance excel
 
Excel.useful fns
Excel.useful fnsExcel.useful fns
Excel.useful fns
 

More from sqlserver content

MS SQL SERVER: Using the data mining tools
MS SQL SERVER: Using the data mining toolsMS SQL SERVER: Using the data mining tools
MS SQL SERVER: Using the data mining tools
sqlserver content
 
MS SQL SERVER: SSIS and data mining
MS SQL SERVER: SSIS and data miningMS SQL SERVER: SSIS and data mining
MS SQL SERVER: SSIS and data mining
sqlserver content
 
MS SQL SERVER: Programming sql server data mining
MS SQL SERVER:  Programming sql server data miningMS SQL SERVER:  Programming sql server data mining
MS SQL SERVER: Programming sql server data mining
sqlserver content
 
MS SQL SERVER: Olap cubes and data mining
MS SQL SERVER:  Olap cubes and data miningMS SQL SERVER:  Olap cubes and data mining
MS SQL SERVER: Olap cubes and data mining
sqlserver content
 
MS SQL SERVER: Microsoft time series algorithm
MS SQL SERVER: Microsoft time series algorithmMS SQL SERVER: Microsoft time series algorithm
MS SQL SERVER: Microsoft time series algorithm
sqlserver content
 
MS SQL SERVER: Microsoft sequence clustering and association rules
MS SQL SERVER: Microsoft sequence clustering and association rulesMS SQL SERVER: Microsoft sequence clustering and association rules
MS SQL SERVER: Microsoft sequence clustering and association rules
sqlserver content
 
MS SQL SERVER: Neural network and logistic regression
MS SQL SERVER: Neural network and logistic regressionMS SQL SERVER: Neural network and logistic regression
MS SQL SERVER: Neural network and logistic regression
sqlserver content
 
MS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithmMS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithmsqlserver content
 
MS SQL SERVER: Decision trees algorithm
MS SQL SERVER: Decision trees algorithmMS SQL SERVER: Decision trees algorithm
MS SQL SERVER: Decision trees algorithm
sqlserver content
 
MS SQL Server: Data mining concepts and dmx
MS SQL Server: Data mining concepts and dmxMS SQL Server: Data mining concepts and dmx
MS SQL Server: Data mining concepts and dmx
sqlserver content
 
MS Sql Server: Reporting models
MS Sql Server: Reporting modelsMS Sql Server: Reporting models
MS Sql Server: Reporting models
sqlserver content
 
MS Sql Server: Reporting manipulating data
MS Sql Server: Reporting manipulating dataMS Sql Server: Reporting manipulating data
MS Sql Server: Reporting manipulating data
sqlserver content
 
MS Sql Server: Datamining Introduction
MS Sql Server: Datamining IntroductionMS Sql Server: Datamining Introduction
MS Sql Server: Datamining Introduction
sqlserver content
 
MS Sql Server: Business Intelligence
MS Sql Server: Business IntelligenceMS Sql Server: Business Intelligence
MS Sql Server: Business Intelligence
sqlserver content
 
MS SQLSERVER:Feeding Data Into Database
MS SQLSERVER:Feeding Data Into DatabaseMS SQLSERVER:Feeding Data Into Database
MS SQLSERVER:Feeding Data Into Database
sqlserver content
 
MS SQLSERVER:Deleting A Database
MS SQLSERVER:Deleting A DatabaseMS SQLSERVER:Deleting A Database
MS SQLSERVER:Deleting A Database
sqlserver content
 
MS SQLSERVER:Customizing Your D Base Design
MS SQLSERVER:Customizing Your D Base DesignMS SQLSERVER:Customizing Your D Base Design
MS SQLSERVER:Customizing Your D Base Design
sqlserver content
 
MS SQLSERVER:Creating Views
MS SQLSERVER:Creating ViewsMS SQLSERVER:Creating Views
MS SQLSERVER:Creating Views
sqlserver content
 
MS SQLSERVER:Creating A Database
MS SQLSERVER:Creating A DatabaseMS SQLSERVER:Creating A Database
MS SQLSERVER:Creating A Database
sqlserver content
 
MS SQLSERVER:Advanced Query Concepts Copy
MS SQLSERVER:Advanced Query Concepts   CopyMS SQLSERVER:Advanced Query Concepts   Copy
MS SQLSERVER:Advanced Query Concepts Copy
sqlserver content
 

More from sqlserver content (20)

MS SQL SERVER: Using the data mining tools
MS SQL SERVER: Using the data mining toolsMS SQL SERVER: Using the data mining tools
MS SQL SERVER: Using the data mining tools
 
MS SQL SERVER: SSIS and data mining
MS SQL SERVER: SSIS and data miningMS SQL SERVER: SSIS and data mining
MS SQL SERVER: SSIS and data mining
 
MS SQL SERVER: Programming sql server data mining
MS SQL SERVER:  Programming sql server data miningMS SQL SERVER:  Programming sql server data mining
MS SQL SERVER: Programming sql server data mining
 
MS SQL SERVER: Olap cubes and data mining
MS SQL SERVER:  Olap cubes and data miningMS SQL SERVER:  Olap cubes and data mining
MS SQL SERVER: Olap cubes and data mining
 
MS SQL SERVER: Microsoft time series algorithm
MS SQL SERVER: Microsoft time series algorithmMS SQL SERVER: Microsoft time series algorithm
MS SQL SERVER: Microsoft time series algorithm
 
MS SQL SERVER: Microsoft sequence clustering and association rules
MS SQL SERVER: Microsoft sequence clustering and association rulesMS SQL SERVER: Microsoft sequence clustering and association rules
MS SQL SERVER: Microsoft sequence clustering and association rules
 
MS SQL SERVER: Neural network and logistic regression
MS SQL SERVER: Neural network and logistic regressionMS SQL SERVER: Neural network and logistic regression
MS SQL SERVER: Neural network and logistic regression
 
MS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithmMS SQL SERVER: Microsoft naive bayes algorithm
MS SQL SERVER: Microsoft naive bayes algorithm
 
MS SQL SERVER: Decision trees algorithm
MS SQL SERVER: Decision trees algorithmMS SQL SERVER: Decision trees algorithm
MS SQL SERVER: Decision trees algorithm
 
MS SQL Server: Data mining concepts and dmx
MS SQL Server: Data mining concepts and dmxMS SQL Server: Data mining concepts and dmx
MS SQL Server: Data mining concepts and dmx
 
MS Sql Server: Reporting models
MS Sql Server: Reporting modelsMS Sql Server: Reporting models
MS Sql Server: Reporting models
 
MS Sql Server: Reporting manipulating data
MS Sql Server: Reporting manipulating dataMS Sql Server: Reporting manipulating data
MS Sql Server: Reporting manipulating data
 
MS Sql Server: Datamining Introduction
MS Sql Server: Datamining IntroductionMS Sql Server: Datamining Introduction
MS Sql Server: Datamining Introduction
 
MS Sql Server: Business Intelligence
MS Sql Server: Business IntelligenceMS Sql Server: Business Intelligence
MS Sql Server: Business Intelligence
 
MS SQLSERVER:Feeding Data Into Database
MS SQLSERVER:Feeding Data Into DatabaseMS SQLSERVER:Feeding Data Into Database
MS SQLSERVER:Feeding Data Into Database
 
MS SQLSERVER:Deleting A Database
MS SQLSERVER:Deleting A DatabaseMS SQLSERVER:Deleting A Database
MS SQLSERVER:Deleting A Database
 
MS SQLSERVER:Customizing Your D Base Design
MS SQLSERVER:Customizing Your D Base DesignMS SQLSERVER:Customizing Your D Base Design
MS SQLSERVER:Customizing Your D Base Design
 
MS SQLSERVER:Creating Views
MS SQLSERVER:Creating ViewsMS SQLSERVER:Creating Views
MS SQLSERVER:Creating Views
 
MS SQLSERVER:Creating A Database
MS SQLSERVER:Creating A DatabaseMS SQLSERVER:Creating A Database
MS SQLSERVER:Creating A Database
 
MS SQLSERVER:Advanced Query Concepts Copy
MS SQLSERVER:Advanced Query Concepts   CopyMS SQLSERVER:Advanced Query Concepts   Copy
MS SQLSERVER:Advanced Query Concepts Copy
 

Recently uploaded

Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
SOFTTECHHUB
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
James Anderson
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
Ana-Maria Mihalceanu
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
RinaMondal9
 
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object CalisthenicsElevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
Dorra BARTAGUIZ
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Neo4j
 
By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024
Pierluigi Pugliese
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
Alpen-Adria-Universität
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Prayukth K V
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neo4j
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
DianaGray10
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
Matthew Sinclair
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
mikeeftimakis1
 
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptxSecstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
nkrafacyberclub
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
BookNet Canada
 
PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
Ralf Eggert
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Neo4j
 

Recently uploaded (20)

Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
 
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR EventsMonitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
 
Elevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object CalisthenicsElevating Tactical DDD Patterns Through Object Calisthenics
Elevating Tactical DDD Patterns Through Object Calisthenics
 
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdfFIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
 
By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024By Design, not by Accident - Agile Venture Bolzano 2024
By Design, not by Accident - Agile Venture Bolzano 2024
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
 
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptxSecstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
 
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...Transcript: Selling digital books in 2024: Insights from industry leaders - T...
Transcript: Selling digital books in 2024: Insights from industry leaders - T...
 
PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
 

MS SQL SERVER: Doing Calculations With Functions

  • 1. 10 SQL SERVER: DOINGCALCULATIONS WITH FUNCTIONS
  • 2. Mathematical Functions Can mathematical functions be used on my tables? Yes. Microsoft SQL Server 2008 provides several mathematical functions such as sum(col), avg(col), min(col), max(col), count(col) etc. In SQL, they are referred to as aggregate functions as they work upon aggregates of rows. Functions Explained: Sum(fieldName): Find the sum of field values of all records Avg(fieldName): Find the average of field values of all records Min(fieldName): Find the minimum of the field values of all records Max(fieldName): Find the maximum of the field values of all records Count(fieldName): Find the number of field values in the table records
  • 3. Mathematical Functions Consider an Interpol database which contains a table of the biggest robberies that took place this year, all around the world. Now, lets look into the application of math functions over this table.
  • 4. Mathematical Functions 1. Find the TOTAL booty of all the robberies: Select sum(booty) from robberies; 2. Find the Average booty of all the robberies: Select avg(booty) from robberies; 3. Find the robbery with the maximal booty Select max(booty) from robberies; 4. Find the robbery with the minimal booty Select min(booty) from robberies; 5. Find the number of robbery cases: Select count(booty) from robberies;
  • 5. Using as condition HEY??? I CANNOT USE THESE FUNCTIONS WITH MY ‘WHERE’ CONDITION??? Microsoft SQL Server 2008 restricts the user to use these functions with ‘WHERE’ conditions. Therefore, to solve our problem three keywords: ‘having’, ‘any’ and ‘in’ select * from tablename having <condition>; select * from tablename where colname=any(cond); select * from tablename where colname in (condition);
  • 6. Advanced Aggregates IS THERE ANY OTHER MODIFICATION TO THESE FUNCTIONS? We can combine these functions with ‘group by’ function for better results. select sum(col1),col2 from tablename group by col2; The above command will find out the sum of each group from column 2 More than one aggregate functions can be used simultaneously, seperated by commas. Eg: select sum(col1), count(col1) from tablename; Consider the example in the next slide.
  • 7. Advanced Aggregates Consider an employee table: Find the Number of Employees working in each department: Select count(empid), depid from employee; Result:
  • 8.
  • 9.
  • 10. Avg
  • 15.