SlideShare a Scribd company logo
1 of 15
What is Database Datawarehouse Data Mining 1 A Ashutosh Mishra Presentation.
Data & Information The word data is plural of datum , though data commonly represents both singular & plural forms. Data are raw facts or observations typically about physical phenomena or business transactions. Specifically , data are objective measurements of attributes of entities such as people , place , things etc. Data that has been converted into meaningful  & useful context for specific end users is termed as information.                          -management information systems by James O’Brien 2 A  Ashutosh  Mishra  Presentation .
Database A collection of information organized in such a way that a computer program can quickly select desired pieces of data. You can think of a database as an electronic filing system. -Webopedia Computer Dictionary A Database is a structured collection of data which is managed to meet the needs of a community of users.                        -Wikipedia.com A database is  an integrated collection of  logically related records or objects. An object consists of data values describing the attributes of  an entity. -management information systems by James O’Brien 3 A  Ashutosh  Mishra  Presentation .
Datawarehouse A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. The term was coined by W. H. Inmon. -Whatis.com A data warehouse is a repository of an organization's electronically stored data. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata. -wikipedia.com 4 A  Ashutosh  Mishra  Presentation .
Data Mining Data mining is the process of sorting through large amounts of data and picking out relevant information. -wikipedia.com In data mining , the data in the data warehouse are processed to identify key factors and trends in historical patterns of business activity. -management information system by James O’Brien 5 A  Ashutosh  Mishra  Presentation .
Pictorial Representation 6 A  Ashutosh  Mishra  Presentation .
Aspect of Marketing 7 A  Ashutosh  Mishra  Presentation .
8 A  Ashutosh  Mishra  Presentation .
9 A  Ashutosh  Mishra  Presentation .
Should you build a Datawarehouse or a Marketing Database? Which is the better vehicle to increase profits by building relationships with your customers and understanding their motivations: a data warehouse or a marketing database? Alexandra Morehouse , and Daniel St. John worked together on database marketing projects for American Express for fifteen years.  Eighteen months ago they joined the California State Automobile Association as VP for Membership Relationship Development and Director of Database Marketing respectively. Their assignment: build a data warehouse. They were given a budget of $17 - $22 million. 10 A  Ashutosh  Mishra  Presentation .
11 A  Ashutosh  Mishra  Presentation .
Probably the most important lesson learned was that the “start small and start fast” approach really worked well. Instead of taking two years to build a giant warehouse, the team had a functioning marketing database up and running in six weeks. Concentrating on fifteen users for testing was a brilliant stroke. These users furnished valuable feedback to the organizers, rather than having users taking their gripes to management in the development phase. -Arthur Middleton Hughes 12 A  Ashutosh  Mishra  Presentation .
References Webopedia.com                                    Mgmt. Infor. System by James O’Brien Wikipedia.com			(College of Business Administration Whatis.com			Northern Arizona University) SPSS.com				4th. Edition , Irwin McGrawHill Smartfocus.com			Galgotia Publications Pvt. Ltd. Further reading : Data Mining for Marketing Applications (Paper) Wendy GerstenKoenraadVanhoof  Daimler Chrysler AG                                            University Centre of Limburg  Research &Tech.                                                   Universitaire Campus   PO Box 2360,89013 Ulm,Germany                   3590 Diepenbeek, Belgium 13 A  Ashutosh  Mishra  Presentation .
"We are drowning in information but starved for knowledge."-- John Naisbitt www.brainybetty.com
Thank you. Presented by  Ashutosh Mishra MBA  1st. sem

More Related Content

What's hot

Data Warehousing and Mining
Data Warehousing and MiningData Warehousing and Mining
Data Warehousing and Miningethantelaviv
 
Introduction to-data-mining chapter 1
Introduction to-data-mining  chapter 1Introduction to-data-mining  chapter 1
Introduction to-data-mining chapter 1Mahmoud Alfarra
 
Intro to big data and applications - day 1
Intro to big data and applications - day 1Intro to big data and applications - day 1
Intro to big data and applications - day 1Parviz Vakili
 
Big Data Analytics for Dodd-Frank
Big Data Analytics for Dodd-FrankBig Data Analytics for Dodd-Frank
Big Data Analytics for Dodd-FrankDataWorks Summit
 
Big data and data mining
Big data and data miningBig data and data mining
Big data and data miningEmran Hossain
 
Introduction to Data Mining and Data Warehousing
Introduction to Data Mining and Data WarehousingIntroduction to Data Mining and Data Warehousing
Introduction to Data Mining and Data WarehousingKamal Acharya
 
Lecture 1 introduction to data warehouse
Lecture 1 introduction to data warehouseLecture 1 introduction to data warehouse
Lecture 1 introduction to data warehouseShani729
 
Data mining services
Data mining servicesData mining services
Data mining servicesRashmiS08
 
BIG DATA BY SAIKIRAN PANJALA
BIG DATA BY SAIKIRAN PANJALABIG DATA BY SAIKIRAN PANJALA
BIG DATA BY SAIKIRAN PANJALASaikiran Panjala
 
Everis big data_wilson_v1.4
Everis big data_wilson_v1.4Everis big data_wilson_v1.4
Everis big data_wilson_v1.4wilson_lucas
 
Business intelligence and data warehousing
Business intelligence and data warehousingBusiness intelligence and data warehousing
Business intelligence and data warehousingOZ Assignment help
 
Big Data v. Small data - Rules to thumb for 2015
Big Data v. Small data - Rules to thumb for 2015Big Data v. Small data - Rules to thumb for 2015
Big Data v. Small data - Rules to thumb for 2015Visart
 
Data-Ed Webinar: Demystifying Big Data
Data-Ed Webinar: Demystifying Big Data Data-Ed Webinar: Demystifying Big Data
Data-Ed Webinar: Demystifying Big Data DATAVERSITY
 
3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...PROWEBSCRAPER
 
Data mining and data warehousing
Data mining and data warehousingData mining and data warehousing
Data mining and data warehousingSatya P. Joshi
 

What's hot (20)

Data Warehousing and Mining
Data Warehousing and MiningData Warehousing and Mining
Data Warehousing and Mining
 
Introduction to-data-mining chapter 1
Introduction to-data-mining  chapter 1Introduction to-data-mining  chapter 1
Introduction to-data-mining chapter 1
 
Data mining
Data miningData mining
Data mining
 
Intro to big data and applications - day 1
Intro to big data and applications - day 1Intro to big data and applications - day 1
Intro to big data and applications - day 1
 
Big Data Analytics for Dodd-Frank
Big Data Analytics for Dodd-FrankBig Data Analytics for Dodd-Frank
Big Data Analytics for Dodd-Frank
 
Big data and data mining
Big data and data miningBig data and data mining
Big data and data mining
 
Introduction to Data Mining and Data Warehousing
Introduction to Data Mining and Data WarehousingIntroduction to Data Mining and Data Warehousing
Introduction to Data Mining and Data Warehousing
 
Big data
Big dataBig data
Big data
 
Dm unit i r16
Dm unit i   r16Dm unit i   r16
Dm unit i r16
 
Lecture 1 introduction to data warehouse
Lecture 1 introduction to data warehouseLecture 1 introduction to data warehouse
Lecture 1 introduction to data warehouse
 
Data mining services
Data mining servicesData mining services
Data mining services
 
BIG DATA BY SAIKIRAN PANJALA
BIG DATA BY SAIKIRAN PANJALABIG DATA BY SAIKIRAN PANJALA
BIG DATA BY SAIKIRAN PANJALA
 
Everis big data_wilson_v1.4
Everis big data_wilson_v1.4Everis big data_wilson_v1.4
Everis big data_wilson_v1.4
 
Fraud and Risk in Big Data
Fraud and Risk in Big DataFraud and Risk in Big Data
Fraud and Risk in Big Data
 
Business intelligence and data warehousing
Business intelligence and data warehousingBusiness intelligence and data warehousing
Business intelligence and data warehousing
 
Data mining
Data miningData mining
Data mining
 
Big Data v. Small data - Rules to thumb for 2015
Big Data v. Small data - Rules to thumb for 2015Big Data v. Small data - Rules to thumb for 2015
Big Data v. Small data - Rules to thumb for 2015
 
Data-Ed Webinar: Demystifying Big Data
Data-Ed Webinar: Demystifying Big Data Data-Ed Webinar: Demystifying Big Data
Data-Ed Webinar: Demystifying Big Data
 
3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...3 pillars of big data : structured data, semi structured data and unstructure...
3 pillars of big data : structured data, semi structured data and unstructure...
 
Data mining and data warehousing
Data mining and data warehousingData mining and data warehousing
Data mining and data warehousing
 

Similar to Marketing and concepts of database.

Business Intelligence
Business IntelligenceBusiness Intelligence
Business IntelligenceSukirti Garg
 
Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...
Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...
Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...Medicaps University
 
Different Types Of Fact Tables
Different Types Of Fact TablesDifferent Types Of Fact Tables
Different Types Of Fact TablesJill Crawford
 
Introduction to business analyticsand historidal overview.pptx
Introduction to business analyticsand historidal overview.pptxIntroduction to business analyticsand historidal overview.pptx
Introduction to business analyticsand historidal overview.pptxSambarajuRavalika
 
Business Intelligence Module 1
Business Intelligence Module 1Business Intelligence Module 1
Business Intelligence Module 1Home
 
Small data vs. Big data : back to the basics
Small data vs. Big data : back to the basicsSmall data vs. Big data : back to the basics
Small data vs. Big data : back to the basicsAhmed Banafa
 
Data Warehouse: A Primer
Data Warehouse: A PrimerData Warehouse: A Primer
Data Warehouse: A PrimerIJRTEMJOURNAL
 
The Data Warehouse Essays
The Data Warehouse EssaysThe Data Warehouse Essays
The Data Warehouse EssaysMelissa Moore
 
Big data analytics in banking sector
Big data analytics in banking sectorBig data analytics in banking sector
Big data analytics in banking sectorAnil Rana
 
Business_Analytics_Presentation_Luke_Caratan
Business_Analytics_Presentation_Luke_CaratanBusiness_Analytics_Presentation_Luke_Caratan
Business_Analytics_Presentation_Luke_CaratanLuke Caratan
 
Information Resources Management
Information Resources ManagementInformation Resources Management
Information Resources ManagementAchmad Solichin
 

Similar to Marketing and concepts of database. (20)

Business Intelligence
Business IntelligenceBusiness Intelligence
Business Intelligence
 
Abstract
AbstractAbstract
Abstract
 
Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...
Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...
Data Warehousing (Need,Application,Architecture,Benefits), Data Mart, Schema,...
 
Big data vs datawarehousing
Big data vs datawarehousingBig data vs datawarehousing
Big data vs datawarehousing
 
Big data vs datawarehousing
Big data vs datawarehousingBig data vs datawarehousing
Big data vs datawarehousing
 
Different Types Of Fact Tables
Different Types Of Fact TablesDifferent Types Of Fact Tables
Different Types Of Fact Tables
 
Introduction to business analyticsand historidal overview.pptx
Introduction to business analyticsand historidal overview.pptxIntroduction to business analyticsand historidal overview.pptx
Introduction to business analyticsand historidal overview.pptx
 
Visual Data Mining
Visual Data MiningVisual Data Mining
Visual Data Mining
 
Business Intelligence Module 1
Business Intelligence Module 1Business Intelligence Module 1
Business Intelligence Module 1
 
Small data vs. Big data : back to the basics
Small data vs. Big data : back to the basicsSmall data vs. Big data : back to the basics
Small data vs. Big data : back to the basics
 
Visual Data Mining
Visual Data MiningVisual Data Mining
Visual Data Mining
 
Data Warehouse: A Primer
Data Warehouse: A PrimerData Warehouse: A Primer
Data Warehouse: A Primer
 
The Data Warehouse Essays
The Data Warehouse EssaysThe Data Warehouse Essays
The Data Warehouse Essays
 
Big data analytics in banking sector
Big data analytics in banking sectorBig data analytics in banking sector
Big data analytics in banking sector
 
Data Management
Data ManagementData Management
Data Management
 
Business_Analytics_Presentation_Luke_Caratan
Business_Analytics_Presentation_Luke_CaratanBusiness_Analytics_Presentation_Luke_Caratan
Business_Analytics_Presentation_Luke_Caratan
 
Big data
Big dataBig data
Big data
 
Information Resources Management
Information Resources ManagementInformation Resources Management
Information Resources Management
 
Lecture1-IS322(Data&InfoMang-introduction)
Lecture1-IS322(Data&InfoMang-introduction)Lecture1-IS322(Data&InfoMang-introduction)
Lecture1-IS322(Data&InfoMang-introduction)
 
Lecture1 is322 data&infomanag(introduction)(old curr)
Lecture1 is322 data&infomanag(introduction)(old curr)Lecture1 is322 data&infomanag(introduction)(old curr)
Lecture1 is322 data&infomanag(introduction)(old curr)
 

More from Ashutosh Mishra

Supply Chain Infrastructure
Supply Chain InfrastructureSupply Chain Infrastructure
Supply Chain InfrastructureAshutosh Mishra
 
International Marketing Research:Complete Aspect.
International Marketing Research:Complete Aspect.International Marketing Research:Complete Aspect.
International Marketing Research:Complete Aspect.Ashutosh Mishra
 
Project Management:Life Cycle & Phases.
Project Management:Life Cycle & Phases.Project Management:Life Cycle & Phases.
Project Management:Life Cycle & Phases.Ashutosh Mishra
 
Environmental Scanning:complete concept.
Environmental Scanning:complete concept.Environmental Scanning:complete concept.
Environmental Scanning:complete concept.Ashutosh Mishra
 
Creative Advertising at it's best.
Creative Advertising at it's best.Creative Advertising at it's best.
Creative Advertising at it's best.Ashutosh Mishra
 
Organization Structure & Details
Organization Structure & DetailsOrganization Structure & Details
Organization Structure & DetailsAshutosh Mishra
 
Goodwill of a company-Accounting aspect.
Goodwill of a company-Accounting aspect.Goodwill of a company-Accounting aspect.
Goodwill of a company-Accounting aspect.Ashutosh Mishra
 
Demand Theory-Managerial Economics
Demand Theory-Managerial EconomicsDemand Theory-Managerial Economics
Demand Theory-Managerial EconomicsAshutosh Mishra
 
Standard Costing:The complete concept.
Standard Costing:The complete concept.Standard Costing:The complete concept.
Standard Costing:The complete concept.Ashutosh Mishra
 
Financial Leverage:complete concept
Financial Leverage:complete conceptFinancial Leverage:complete concept
Financial Leverage:complete conceptAshutosh Mishra
 

More from Ashutosh Mishra (11)

Supply Chain Infrastructure
Supply Chain InfrastructureSupply Chain Infrastructure
Supply Chain Infrastructure
 
International Marketing Research:Complete Aspect.
International Marketing Research:Complete Aspect.International Marketing Research:Complete Aspect.
International Marketing Research:Complete Aspect.
 
Project Management:Life Cycle & Phases.
Project Management:Life Cycle & Phases.Project Management:Life Cycle & Phases.
Project Management:Life Cycle & Phases.
 
Environmental Scanning:complete concept.
Environmental Scanning:complete concept.Environmental Scanning:complete concept.
Environmental Scanning:complete concept.
 
Creative Advertising at it's best.
Creative Advertising at it's best.Creative Advertising at it's best.
Creative Advertising at it's best.
 
Organization Structure & Details
Organization Structure & DetailsOrganization Structure & Details
Organization Structure & Details
 
Goodwill of a company-Accounting aspect.
Goodwill of a company-Accounting aspect.Goodwill of a company-Accounting aspect.
Goodwill of a company-Accounting aspect.
 
Demand Theory-Managerial Economics
Demand Theory-Managerial EconomicsDemand Theory-Managerial Economics
Demand Theory-Managerial Economics
 
Learning in nutshell.
Learning in nutshell.Learning in nutshell.
Learning in nutshell.
 
Standard Costing:The complete concept.
Standard Costing:The complete concept.Standard Costing:The complete concept.
Standard Costing:The complete concept.
 
Financial Leverage:complete concept
Financial Leverage:complete conceptFinancial Leverage:complete concept
Financial Leverage:complete concept
 

Recently uploaded

Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersRaghuram Pandurangan
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESSALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESmohitsingh558521
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxLoriGlavin3
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demoHarshalMandlekar2
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
What is Artificial Intelligence?????????
What is Artificial Intelligence?????????What is Artificial Intelligence?????????
What is Artificial Intelligence?????????blackmambaettijean
 
A Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersA Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersNicole Novielli
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 

Recently uploaded (20)

Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
Generative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information DevelopersGenerative AI for Technical Writer or Information Developers
Generative AI for Technical Writer or Information Developers
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESSALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
 
Sample pptx for embedding into website for demo
Sample pptx for embedding into website for demoSample pptx for embedding into website for demo
Sample pptx for embedding into website for demo
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
What is Artificial Intelligence?????????
What is Artificial Intelligence?????????What is Artificial Intelligence?????????
What is Artificial Intelligence?????????
 
A Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software DevelopersA Journey Into the Emotions of Software Developers
A Journey Into the Emotions of Software Developers
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 

Marketing and concepts of database.

  • 1. What is Database Datawarehouse Data Mining 1 A Ashutosh Mishra Presentation.
  • 2. Data & Information The word data is plural of datum , though data commonly represents both singular & plural forms. Data are raw facts or observations typically about physical phenomena or business transactions. Specifically , data are objective measurements of attributes of entities such as people , place , things etc. Data that has been converted into meaningful & useful context for specific end users is termed as information. -management information systems by James O’Brien 2 A Ashutosh Mishra Presentation .
  • 3. Database A collection of information organized in such a way that a computer program can quickly select desired pieces of data. You can think of a database as an electronic filing system. -Webopedia Computer Dictionary A Database is a structured collection of data which is managed to meet the needs of a community of users. -Wikipedia.com A database is an integrated collection of logically related records or objects. An object consists of data values describing the attributes of an entity. -management information systems by James O’Brien 3 A Ashutosh Mishra Presentation .
  • 4. Datawarehouse A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. The term was coined by W. H. Inmon. -Whatis.com A data warehouse is a repository of an organization's electronically stored data. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata. -wikipedia.com 4 A Ashutosh Mishra Presentation .
  • 5. Data Mining Data mining is the process of sorting through large amounts of data and picking out relevant information. -wikipedia.com In data mining , the data in the data warehouse are processed to identify key factors and trends in historical patterns of business activity. -management information system by James O’Brien 5 A Ashutosh Mishra Presentation .
  • 6. Pictorial Representation 6 A Ashutosh Mishra Presentation .
  • 7. Aspect of Marketing 7 A Ashutosh Mishra Presentation .
  • 8. 8 A Ashutosh Mishra Presentation .
  • 9. 9 A Ashutosh Mishra Presentation .
  • 10. Should you build a Datawarehouse or a Marketing Database? Which is the better vehicle to increase profits by building relationships with your customers and understanding their motivations: a data warehouse or a marketing database? Alexandra Morehouse , and Daniel St. John worked together on database marketing projects for American Express for fifteen years. Eighteen months ago they joined the California State Automobile Association as VP for Membership Relationship Development and Director of Database Marketing respectively. Their assignment: build a data warehouse. They were given a budget of $17 - $22 million. 10 A Ashutosh Mishra Presentation .
  • 11. 11 A Ashutosh Mishra Presentation .
  • 12. Probably the most important lesson learned was that the “start small and start fast” approach really worked well. Instead of taking two years to build a giant warehouse, the team had a functioning marketing database up and running in six weeks. Concentrating on fifteen users for testing was a brilliant stroke. These users furnished valuable feedback to the organizers, rather than having users taking their gripes to management in the development phase. -Arthur Middleton Hughes 12 A Ashutosh Mishra Presentation .
  • 13. References Webopedia.com Mgmt. Infor. System by James O’Brien Wikipedia.com (College of Business Administration Whatis.com Northern Arizona University) SPSS.com 4th. Edition , Irwin McGrawHill Smartfocus.com Galgotia Publications Pvt. Ltd. Further reading : Data Mining for Marketing Applications (Paper) Wendy GerstenKoenraadVanhoof Daimler Chrysler AG University Centre of Limburg Research &Tech. Universitaire Campus PO Box 2360,89013 Ulm,Germany 3590 Diepenbeek, Belgium 13 A Ashutosh Mishra Presentation .
  • 14. "We are drowning in information but starved for knowledge."-- John Naisbitt www.brainybetty.com
  • 15. Thank you. Presented by Ashutosh Mishra MBA 1st. sem