SlideShare a Scribd company logo
SQL (Scratch to Advance)
What is SQL?
• SQL stands for Structured Query Language
• SQL lets you access and manipulate databases
• SQL became a standard of the American National Standards Institute
(ANSI) in 1986, and of the International Organization for
Standardization (ISO) in 1987
What is Database?
 A database is a systematic collection of data. They support electronic
storage and manipulation of data. Databases make data management easy.
 Types of Databases
 Here are some popular types of databases.
 Distributed databases:
 A distributed database is a type of database that has contributions from the
common database and information captured by local computers. In this type of
database system, the data is not in one place and is distributed at various
organizations.
Types of Databases:--
 Relational databases:
 This type of database defines database relationships in the form of tables. It is
also called Relational DBMS, which is the most popular DBMS type in the
Database example of the RDBMS system include MySQL, Oracle, and Microsoft
SQL Server database.
 Object-oriented databases:
 This type of computers database supports the storage of all data types. The
is stored in the form of objects. The objects to be held in the database have
attributes and methods that define what to do with the data. PostgreSQL is an
example of an object-oriented relational DBMS.
 Centralized database:
 It is a centralized location, and users from different backgrounds can access
data. This type of computers databases store application procedures that help
users access the data even from a remote location.
 Open-source databases:
 This kind of database stored information related to operations. It is mainly
in the field of marketing, employee relations, customer service, of databases.
 Cloud databases:
 A cloud database is a database which is optimized or built for such a
environment.
 NoSQL databases:
 NoSQL database is used for large sets of distributed data.
 Graph databases:
 A graph-oriented database uses graph theory to store, map, and query
relationships
 OLTP databases:
 OLTP another database type which able to perform fast query processing and
maintaining data integrity in multi-access environments.
 Personal database:
 A personal database is used to store data stored on personal computers that
smaller and easily manageable. The data is mostly used by the same
department of the company and is accessed by a small group of people.
 Multimodal database:
 The multimodal database is a type of data processing platform that supports
multiple data models that define how the certain knowledge and information
a database should be organized and arranged.
 Document/JSON database:
 In a document-oriented database, the data is kept in document collections, usually
using the XML, JSON, BSON formats. One record can store as much data as you want,
in any data type (or types) you prefer.
 Hierarchical:
 This type of DBMS employs the “parent-child” relationship of storing data. Its
is like a tree with nodes representing records and branches representing fields. The
windows registry used in Windows XP is a hierarchical database example.
 Network DBMS:
 This type of DBMS supports many-to-many relations. It usually results in complex
database structures. RDM Server is an example of database management system that
implements the network model.
Databases Components
DBMS
 Database Management System (DBMS) is a collection of programs that enable
its users to access databases, manipulate data, report, and represent data. It
helps to control access to the database.
 Advantages of DBMS
• DBMS offers a variety of techniques to store & retrieve data.
• DBMS serves as an efficient handler to balance the needs of multiple
applications using the same data.
• Uniform administration procedures for data.
 Disadvantage of DBMS
 DBMS may offer plenty of advantages but, it has certain flaws-
• Cost of Hardware and Software of a DBMS is quite high which increases
budget of your organization.
• Most database management systems are often complex systems, so the
training for users to use the DBMS is required.
SQL (Scratch to Advance).pptx

More Related Content

Similar to SQL (Scratch to Advance).pptx

Database management system
Database management systemDatabase management system
Database management system
khagendrabasnet4
 
Database systems introduction
Database systems introductionDatabase systems introduction
Database systems introduction
Balasingham Karthiban
 
DBMS Notes.pdf
DBMS Notes.pdfDBMS Notes.pdf
DBMS Notes.pdf
shubhampatel67739
 
Database and Database Management (DBM): Health Informatics
Database and Database Management (DBM): Health InformaticsDatabase and Database Management (DBM): Health Informatics
Database and Database Management (DBM): Health Informatics
Zulfiquer Ahmed Amin
 
WEB_DATABASE_chapter_4.pptx
WEB_DATABASE_chapter_4.pptxWEB_DATABASE_chapter_4.pptx
WEB_DATABASE_chapter_4.pptx
Koteswari Kasireddy
 
Unit-10.pptx
Unit-10.pptxUnit-10.pptx
Unit-10.pptx
GhanashyamBK1
 
Database Systems Lec 1.pptx
Database Systems Lec 1.pptxDatabase Systems Lec 1.pptx
Database Systems Lec 1.pptx
NishaTariq1
 
Database Management Systems
Database Management SystemsDatabase Management Systems
Unit 1.pptx
Unit 1.pptxUnit 1.pptx
Unit 1.pptx
chatkall46
 
1677091759369776.pdf
1677091759369776.pdf1677091759369776.pdf
1677091759369776.pdf
Janoakre
 
Data-base-system-and-big-data.pptx
Data-base-system-and-big-data.pptxData-base-system-and-big-data.pptx
Data-base-system-and-big-data.pptx
MelchorCleve
 
DBMS introduction
DBMS introductionDBMS introduction
DBMS introduction
BHARATH KUMAR
 
Data base management system
Data base management systemData base management system
Data base management system
ashirafzal1
 
Database systems Handbook dbms.pdf
Database systems Handbook dbms.pdfDatabase systems Handbook dbms.pdf
Database systems Handbook dbms.pdf
Bahria University Islamabad, Pakistan
 
Database systems Handbook dbms.pdf
Database systems Handbook dbms.pdfDatabase systems Handbook dbms.pdf
Database systems Handbook dbms.pdf
Bahria University Islamabad, Pakistan
 
Database systems Handbook dbms.pdf
Database systems Handbook dbms.pdfDatabase systems Handbook dbms.pdf
Database systems Handbook dbms.pdf
Bahria University Islamabad, Pakistan
 
Database systems Handbook.pdf
Database systems Handbook.pdfDatabase systems Handbook.pdf
Database systems Handbook.pdf
Bahria University Islamabad, Pakistan
 
Database systems Handbook.pdf
Database systems Handbook.pdfDatabase systems Handbook.pdf
Database systems Handbook.pdf
Bahria University Islamabad, Pakistan
 
Database systems Handbook 2V.pdf
Database systems Handbook 2V.pdfDatabase systems Handbook 2V.pdf
Database systems Handbook 2V.pdf
Bahria University Islamabad, Pakistan
 

Similar to SQL (Scratch to Advance).pptx (20)

Database management system
Database management systemDatabase management system
Database management system
 
Database systems introduction
Database systems introductionDatabase systems introduction
Database systems introduction
 
DBMS Notes.pdf
DBMS Notes.pdfDBMS Notes.pdf
DBMS Notes.pdf
 
Database and Database Management (DBM): Health Informatics
Database and Database Management (DBM): Health InformaticsDatabase and Database Management (DBM): Health Informatics
Database and Database Management (DBM): Health Informatics
 
WEB_DATABASE_chapter_4.pptx
WEB_DATABASE_chapter_4.pptxWEB_DATABASE_chapter_4.pptx
WEB_DATABASE_chapter_4.pptx
 
Unit-10.pptx
Unit-10.pptxUnit-10.pptx
Unit-10.pptx
 
Database Systems Lec 1.pptx
Database Systems Lec 1.pptxDatabase Systems Lec 1.pptx
Database Systems Lec 1.pptx
 
Database Management Systems
Database Management SystemsDatabase Management Systems
Database Management Systems
 
Unit 1.pptx
Unit 1.pptxUnit 1.pptx
Unit 1.pptx
 
1677091759369776.pdf
1677091759369776.pdf1677091759369776.pdf
1677091759369776.pdf
 
Data-base-system-and-big-data.pptx
Data-base-system-and-big-data.pptxData-base-system-and-big-data.pptx
Data-base-system-and-big-data.pptx
 
DBMS introduction
DBMS introductionDBMS introduction
DBMS introduction
 
Data base management system
Data base management systemData base management system
Data base management system
 
Dbms9
Dbms9Dbms9
Dbms9
 
Database systems Handbook dbms.pdf
Database systems Handbook dbms.pdfDatabase systems Handbook dbms.pdf
Database systems Handbook dbms.pdf
 
Database systems Handbook dbms.pdf
Database systems Handbook dbms.pdfDatabase systems Handbook dbms.pdf
Database systems Handbook dbms.pdf
 
Database systems Handbook dbms.pdf
Database systems Handbook dbms.pdfDatabase systems Handbook dbms.pdf
Database systems Handbook dbms.pdf
 
Database systems Handbook.pdf
Database systems Handbook.pdfDatabase systems Handbook.pdf
Database systems Handbook.pdf
 
Database systems Handbook.pdf
Database systems Handbook.pdfDatabase systems Handbook.pdf
Database systems Handbook.pdf
 
Database systems Handbook 2V.pdf
Database systems Handbook 2V.pdfDatabase systems Handbook 2V.pdf
Database systems Handbook 2V.pdf
 

Recently uploaded

Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptxData_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
AnirbanRoy608946
 
Q1’2024 Update: MYCI’s Leap Year Rebound
Q1’2024 Update: MYCI’s Leap Year ReboundQ1’2024 Update: MYCI’s Leap Year Rebound
Q1’2024 Update: MYCI’s Leap Year Rebound
Oppotus
 
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project PresentationPredicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Boston Institute of Analytics
 
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
NABLAS株式会社
 
一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单
ewymefz
 
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP
 
一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
ewymefz
 
Machine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptxMachine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptx
balafet
 
Opendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptxOpendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptx
Opendatabay
 
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
slg6lamcq
 
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
2023240532
 
一比一原版(CU毕业证)卡尔顿大学毕业证成绩单
一比一原版(CU毕业证)卡尔顿大学毕业证成绩单一比一原版(CU毕业证)卡尔顿大学毕业证成绩单
一比一原版(CU毕业证)卡尔顿大学毕业证成绩单
yhkoc
 
一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单
ewymefz
 
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...
pchutichetpong
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
v3tuleee
 
FP Growth Algorithm and its Applications
FP Growth Algorithm and its ApplicationsFP Growth Algorithm and its Applications
FP Growth Algorithm and its Applications
MaleehaSheikh2
 
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP
 
Adjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTESAdjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTES
Subhajit Sahu
 
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
ahzuo
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
rwarrenll
 

Recently uploaded (20)

Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptxData_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
Data_and_Analytics_Essentials_Architect_an_Analytics_Platform.pptx
 
Q1’2024 Update: MYCI’s Leap Year Rebound
Q1’2024 Update: MYCI’s Leap Year ReboundQ1’2024 Update: MYCI’s Leap Year Rebound
Q1’2024 Update: MYCI’s Leap Year Rebound
 
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project PresentationPredicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
 
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
【社内勉強会資料_Octo: An Open-Source Generalist Robot Policy】
 
一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单
 
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdf
 
一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
一比一原版(IIT毕业证)伊利诺伊理工大学毕业证成绩单
 
Machine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptxMachine learning and optimization techniques for electrical drives.pptx
Machine learning and optimization techniques for electrical drives.pptx
 
Opendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptxOpendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptx
 
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
 
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
 
一比一原版(CU毕业证)卡尔顿大学毕业证成绩单
一比一原版(CU毕业证)卡尔顿大学毕业证成绩单一比一原版(CU毕业证)卡尔顿大学毕业证成绩单
一比一原版(CU毕业证)卡尔顿大学毕业证成绩单
 
一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单
 
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
 
FP Growth Algorithm and its Applications
FP Growth Algorithm and its ApplicationsFP Growth Algorithm and its Applications
FP Growth Algorithm and its Applications
 
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdf
 
Adjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTESAdjusting primitives for graph : SHORT REPORT / NOTES
Adjusting primitives for graph : SHORT REPORT / NOTES
 
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
 

SQL (Scratch to Advance).pptx

  • 1. SQL (Scratch to Advance)
  • 2. What is SQL? • SQL stands for Structured Query Language • SQL lets you access and manipulate databases • SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987
  • 3. What is Database?  A database is a systematic collection of data. They support electronic storage and manipulation of data. Databases make data management easy.  Types of Databases  Here are some popular types of databases.  Distributed databases:  A distributed database is a type of database that has contributions from the common database and information captured by local computers. In this type of database system, the data is not in one place and is distributed at various organizations.
  • 4. Types of Databases:--  Relational databases:  This type of database defines database relationships in the form of tables. It is also called Relational DBMS, which is the most popular DBMS type in the Database example of the RDBMS system include MySQL, Oracle, and Microsoft SQL Server database.  Object-oriented databases:  This type of computers database supports the storage of all data types. The is stored in the form of objects. The objects to be held in the database have attributes and methods that define what to do with the data. PostgreSQL is an example of an object-oriented relational DBMS.
  • 5.  Centralized database:  It is a centralized location, and users from different backgrounds can access data. This type of computers databases store application procedures that help users access the data even from a remote location.  Open-source databases:  This kind of database stored information related to operations. It is mainly in the field of marketing, employee relations, customer service, of databases.
  • 6.  Cloud databases:  A cloud database is a database which is optimized or built for such a environment.  NoSQL databases:  NoSQL database is used for large sets of distributed data.  Graph databases:  A graph-oriented database uses graph theory to store, map, and query relationships
  • 7.  OLTP databases:  OLTP another database type which able to perform fast query processing and maintaining data integrity in multi-access environments.  Personal database:  A personal database is used to store data stored on personal computers that smaller and easily manageable. The data is mostly used by the same department of the company and is accessed by a small group of people.  Multimodal database:  The multimodal database is a type of data processing platform that supports multiple data models that define how the certain knowledge and information a database should be organized and arranged.
  • 8.  Document/JSON database:  In a document-oriented database, the data is kept in document collections, usually using the XML, JSON, BSON formats. One record can store as much data as you want, in any data type (or types) you prefer.  Hierarchical:  This type of DBMS employs the “parent-child” relationship of storing data. Its is like a tree with nodes representing records and branches representing fields. The windows registry used in Windows XP is a hierarchical database example.  Network DBMS:  This type of DBMS supports many-to-many relations. It usually results in complex database structures. RDM Server is an example of database management system that implements the network model.
  • 10. DBMS  Database Management System (DBMS) is a collection of programs that enable its users to access databases, manipulate data, report, and represent data. It helps to control access to the database.  Advantages of DBMS • DBMS offers a variety of techniques to store & retrieve data. • DBMS serves as an efficient handler to balance the needs of multiple applications using the same data. • Uniform administration procedures for data.
  • 11.  Disadvantage of DBMS  DBMS may offer plenty of advantages but, it has certain flaws- • Cost of Hardware and Software of a DBMS is quite high which increases budget of your organization. • Most database management systems are often complex systems, so the training for users to use the DBMS is required.