SlideShare a Scribd company logo
1 of 8
BY
Bibek Subedi (066 BCT 506)
Dinesh Subedi (066 BCT 512)
Jivan Nepali (066 BCT 517)
Laxmi Kadariya (066 BCT 518)
BACKGROUND
 Data warehousing ?
is the process of data asset acquisition, organization, and
management.
 Decision Support ?
is the application of managed data assets to business and
clinical decision making needs to achieve business
intelligence
 Business Intelligence (BI) ?
is the transformation of data into information, and through
discovery, transforming that information into knowledge
NEED OF BI IN BANKING SECTOR OF
NEPAL
Competitive Market
High Churn Rates
Massive Data Collection
ATM CARD SKIMMING &
COUNTERFEIT CARD FRAUD A smaller skimmer
that looks just like a
normal card entry slot
and attached to the
ATM rain cover.
OBJECTIVES
Debit card fraud detection
Customer churn behavior prediction
CRM (Customer Relationship
Management) with customer
segmentation
DESIGN APPROACH
PLATFORM & TOOLS
ETL Tool: Korn Shell (ksh) Scripting
Database: Oracle 11g
Presentation/ Front-end Tool: OBIEE
11g
Project Management Tool: Redmine
Version Control Tool: Subversion (svn)
ANY QUESTIONS

More Related Content

What's hot

Business intelligence strategy and roadmap 2018
Business intelligence strategy and roadmap 2018Business intelligence strategy and roadmap 2018
Business intelligence strategy and roadmap 2018Mondy Holten
 
Big Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATION
Big Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATIONBig Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATION
Big Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATIONMatt Stubbs
 
Enfathom Service Overview
Enfathom Service OverviewEnfathom Service Overview
Enfathom Service Overviewbgoverstreet
 
Enfathom Service Overview
Enfathom Service OverviewEnfathom Service Overview
Enfathom Service Overviewcfsanders
 
Integrating BI - Data Warehouse and Big Data
Integrating BI - Data Warehouse and Big DataIntegrating BI - Data Warehouse and Big Data
Integrating BI - Data Warehouse and Big DataAccenture Analytics
 
Analytics and information management.
Analytics and information management.Analytics and information management.
Analytics and information management.Mindtree Ltd.
 
SplunkLive! Splunk for Business Analytics
SplunkLive! Splunk for Business AnalyticsSplunkLive! Splunk for Business Analytics
SplunkLive! Splunk for Business AnalyticsSplunk
 
Semantify Investor Deck
Semantify Investor DeckSemantify Investor Deck
Semantify Investor Deckarjundutt
 
Location Intelligence - the Next Evolution of Business Applications
Location Intelligence - the Next Evolution of Business ApplicationsLocation Intelligence - the Next Evolution of Business Applications
Location Intelligence - the Next Evolution of Business ApplicationsMISNet - Integeo SE Asia
 
From Business Intelligence to Big Data - hack/reduce Dec 2014
From Business Intelligence to Big Data - hack/reduce Dec 2014From Business Intelligence to Big Data - hack/reduce Dec 2014
From Business Intelligence to Big Data - hack/reduce Dec 2014Adam Ferrari
 
Business Intelligence & Reporting are Not the Same
Business Intelligence & Reporting are Not the SameBusiness Intelligence & Reporting are Not the Same
Business Intelligence & Reporting are Not the SameHeath Turner
 
Blueprint for integrating big data analytics and bi
Blueprint for integrating big data analytics and biBlueprint for integrating big data analytics and bi
Blueprint for integrating big data analytics and biDataWorks Summit
 
Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...
Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...
Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...Matt Stubbs
 
Big Data Banking: Customer vs. Accounting
Big Data Banking: Customer vs. AccountingBig Data Banking: Customer vs. Accounting
Big Data Banking: Customer vs. AccountingHenry Sampson
 
Business Intelligence Overview
Business Intelligence OverviewBusiness Intelligence Overview
Business Intelligence OverviewClaudio Menozzi
 

What's hot (20)

Business intelligence strategy and roadmap 2018
Business intelligence strategy and roadmap 2018Business intelligence strategy and roadmap 2018
Business intelligence strategy and roadmap 2018
 
Big Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATION
Big Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATIONBig Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATION
Big Data LDN 2018: CONNECTING SILOS IN REAL-TIME WITH DATA VIRTUALIZATION
 
The evolution of Business Intelligence
The evolution of Business IntelligenceThe evolution of Business Intelligence
The evolution of Business Intelligence
 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
 
Business Intelligence Services | BI Tools
Business Intelligence Services | BI ToolsBusiness Intelligence Services | BI Tools
Business Intelligence Services | BI Tools
 
Enfathom Service Overview
Enfathom Service OverviewEnfathom Service Overview
Enfathom Service Overview
 
Enfathom Service Overview
Enfathom Service OverviewEnfathom Service Overview
Enfathom Service Overview
 
Integrating BI - Data Warehouse and Big Data
Integrating BI - Data Warehouse and Big DataIntegrating BI - Data Warehouse and Big Data
Integrating BI - Data Warehouse and Big Data
 
Analytics and information management.
Analytics and information management.Analytics and information management.
Analytics and information management.
 
SplunkLive! Splunk for Business Analytics
SplunkLive! Splunk for Business AnalyticsSplunkLive! Splunk for Business Analytics
SplunkLive! Splunk for Business Analytics
 
Bi orientations
Bi orientationsBi orientations
Bi orientations
 
Semantify Investor Deck
Semantify Investor DeckSemantify Investor Deck
Semantify Investor Deck
 
Location Intelligence - the Next Evolution of Business Applications
Location Intelligence - the Next Evolution of Business ApplicationsLocation Intelligence - the Next Evolution of Business Applications
Location Intelligence - the Next Evolution of Business Applications
 
From Business Intelligence to Big Data - hack/reduce Dec 2014
From Business Intelligence to Big Data - hack/reduce Dec 2014From Business Intelligence to Big Data - hack/reduce Dec 2014
From Business Intelligence to Big Data - hack/reduce Dec 2014
 
Business Intelligence & Reporting are Not the Same
Business Intelligence & Reporting are Not the SameBusiness Intelligence & Reporting are Not the Same
Business Intelligence & Reporting are Not the Same
 
Blueprint for integrating big data analytics and bi
Blueprint for integrating big data analytics and biBlueprint for integrating big data analytics and bi
Blueprint for integrating big data analytics and bi
 
Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...
Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...
Big Data LDN 2018: SHAPING AN AI-DRIVEN FUTURE WITH AUGMENTED INTELLIGENCE FO...
 
Big Data Banking: Customer vs. Accounting
Big Data Banking: Customer vs. AccountingBig Data Banking: Customer vs. Accounting
Big Data Banking: Customer vs. Accounting
 
Business Intelligence Overview
Business Intelligence OverviewBusiness Intelligence Overview
Business Intelligence Overview
 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
 

Similar to Warehouse based Intelligent Banking Transaction Analysis System

Bank management system PPT.pptx
Bank management system PPT.pptxBank management system PPT.pptx
Bank management system PPT.pptxRaviPatidar59
 
01. Introduction to Data Mining and BI
01. Introduction to Data Mining and BI01. Introduction to Data Mining and BI
01. Introduction to Data Mining and BIAchmad Solichin
 
Finding fraud in large, diverse data sets
Finding fraud in large, diverse data setsFinding fraud in large, diverse data sets
Finding fraud in large, diverse data setsChris Selland
 
Application of Business Intelligence in bank risk management - Dimitar Dilov
Application of Business Intelligence in bank risk management - Dimitar DilovApplication of Business Intelligence in bank risk management - Dimitar Dilov
Application of Business Intelligence in bank risk management - Dimitar DilovInstitute of Contemporary Sciences
 
BI Self-Service Keys to Success and QlikView Overview
BI Self-Service Keys to Success and QlikView OverviewBI Self-Service Keys to Success and QlikView Overview
BI Self-Service Keys to Success and QlikView OverviewSenturus
 
Financial server blue print - Blueprints.pdf
Financial server blue print - Blueprints.pdfFinancial server blue print - Blueprints.pdf
Financial server blue print - Blueprints.pdfRopiudin5
 
Database Shootout: What's best for BI?
Database Shootout: What's best for BI?Database Shootout: What's best for BI?
Database Shootout: What's best for BI?Jos van Dongen
 
Big data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You WantBig data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You WantStuart Miniman
 
DataOps - Big Data and AI World London - March 2020 - Harvinder Atwal
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalDataOps - Big Data and AI World London - March 2020 - Harvinder Atwal
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalHarvinder Atwal
 
Overview of Business Intelligence
Overview of Business IntelligenceOverview of Business Intelligence
Overview of Business IntelligenceParthiv Dixit
 
BSFI Technology Offerings by Value Innovation Labs
BSFI Technology Offerings by Value Innovation LabsBSFI Technology Offerings by Value Innovation Labs
BSFI Technology Offerings by Value Innovation LabsMount Talent Consulting
 
Demystifying BI For Mid-Market Enterprises
Demystifying BI For Mid-Market EnterprisesDemystifying BI For Mid-Market Enterprises
Demystifying BI For Mid-Market EnterprisesJamal_Shah
 
Business Intelligence In Cyber Security | Cyberroot Risk Advisory
Business Intelligence In Cyber Security | Cyberroot Risk AdvisoryBusiness Intelligence In Cyber Security | Cyberroot Risk Advisory
Business Intelligence In Cyber Security | Cyberroot Risk AdvisoryCR Group
 
BI and Predictive analytics 2011 shyam desigan presentation
BI and Predictive analytics 2011 shyam desigan presentationBI and Predictive analytics 2011 shyam desigan presentation
BI and Predictive analytics 2011 shyam desigan presentationShyam Desigan
 
Enfathom service overview
Enfathom service overviewEnfathom service overview
Enfathom service overviewchooylee
 
Journey to a Modern Data Architecture
Journey to a Modern Data ArchitectureJourney to a Modern Data Architecture
Journey to a Modern Data ArchitecturePrecisely
 
Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...
Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...
Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...Craig Milroy
 

Similar to Warehouse based Intelligent Banking Transaction Analysis System (20)

Bank management system PPT.pptx
Bank management system PPT.pptxBank management system PPT.pptx
Bank management system PPT.pptx
 
01. Introduction to Data Mining and BI
01. Introduction to Data Mining and BI01. Introduction to Data Mining and BI
01. Introduction to Data Mining and BI
 
Finding fraud in large, diverse data sets
Finding fraud in large, diverse data setsFinding fraud in large, diverse data sets
Finding fraud in large, diverse data sets
 
Application of Business Intelligence in bank risk management - Dimitar Dilov
Application of Business Intelligence in bank risk management - Dimitar DilovApplication of Business Intelligence in bank risk management - Dimitar Dilov
Application of Business Intelligence in bank risk management - Dimitar Dilov
 
BI Self-Service Keys to Success and QlikView Overview
BI Self-Service Keys to Success and QlikView OverviewBI Self-Service Keys to Success and QlikView Overview
BI Self-Service Keys to Success and QlikView Overview
 
Financial server blue print - Blueprints.pdf
Financial server blue print - Blueprints.pdfFinancial server blue print - Blueprints.pdf
Financial server blue print - Blueprints.pdf
 
Business intelligence
Business intelligenceBusiness intelligence
Business intelligence
 
Database Shootout: What's best for BI?
Database Shootout: What's best for BI?Database Shootout: What's best for BI?
Database Shootout: What's best for BI?
 
Big data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You WantBig data? No. Big Decisions are What You Want
Big data? No. Big Decisions are What You Want
 
DataOps - Big Data and AI World London - March 2020 - Harvinder Atwal
DataOps - Big Data and AI World London - March 2020 - Harvinder AtwalDataOps - Big Data and AI World London - March 2020 - Harvinder Atwal
DataOps - Big Data and AI World London - March 2020 - Harvinder Atwal
 
Overview of Business Intelligence
Overview of Business IntelligenceOverview of Business Intelligence
Overview of Business Intelligence
 
BSFI Technology Offerings by Value Innovation Labs
BSFI Technology Offerings by Value Innovation LabsBSFI Technology Offerings by Value Innovation Labs
BSFI Technology Offerings by Value Innovation Labs
 
Demystifying BI For Mid-Market Enterprises
Demystifying BI For Mid-Market EnterprisesDemystifying BI For Mid-Market Enterprises
Demystifying BI For Mid-Market Enterprises
 
Business Intelligence In Cyber Security | Cyberroot Risk Advisory
Business Intelligence In Cyber Security | Cyberroot Risk AdvisoryBusiness Intelligence In Cyber Security | Cyberroot Risk Advisory
Business Intelligence In Cyber Security | Cyberroot Risk Advisory
 
BI and Predictive analytics 2011 shyam desigan presentation
BI and Predictive analytics 2011 shyam desigan presentationBI and Predictive analytics 2011 shyam desigan presentation
BI and Predictive analytics 2011 shyam desigan presentation
 
Aksh 117 bpd_sd (1)
Aksh 117 bpd_sd (1)Aksh 117 bpd_sd (1)
Aksh 117 bpd_sd (1)
 
KNIME Meetup 2016-04-16
KNIME Meetup 2016-04-16KNIME Meetup 2016-04-16
KNIME Meetup 2016-04-16
 
Enfathom service overview
Enfathom service overviewEnfathom service overview
Enfathom service overview
 
Journey to a Modern Data Architecture
Journey to a Modern Data ArchitectureJourney to a Modern Data Architecture
Journey to a Modern Data Architecture
 
Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...
Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...
Chief Data Architect or Chief Data Officer: Connecting the Enterprise Data Ec...
 

More from Jivan Nepali

Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and Spark
Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and SparkCrystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and Spark
Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and SparkJivan Nepali
 
Library System Implementation with JavaFx
Library System Implementation with JavaFxLibrary System Implementation with JavaFx
Library System Implementation with JavaFxJivan Nepali
 
Cookies: HTTP state management mechanism
Cookies: HTTP state management mechanismCookies: HTTP state management mechanism
Cookies: HTTP state management mechanismJivan Nepali
 
Tourism market segmentation in context of nepal
Tourism market segmentation in context of nepalTourism market segmentation in context of nepal
Tourism market segmentation in context of nepalJivan Nepali
 
Decision Support and Knowledge Based Systems
Decision Support and Knowledge Based SystemsDecision Support and Knowledge Based Systems
Decision Support and Knowledge Based SystemsJivan Nepali
 
Grid computing the grid
Grid computing the gridGrid computing the grid
Grid computing the gridJivan Nepali
 
Restaurant Guide: A GPS based Android App
Restaurant Guide: A GPS based Android AppRestaurant Guide: A GPS based Android App
Restaurant Guide: A GPS based Android AppJivan Nepali
 
Project time management
Project time managementProject time management
Project time managementJivan Nepali
 

More from Jivan Nepali (8)

Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and Spark
Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and SparkCrystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and Spark
Crystal Ball Event Prediction and Log Analysis with Hadoop MapReduce and Spark
 
Library System Implementation with JavaFx
Library System Implementation with JavaFxLibrary System Implementation with JavaFx
Library System Implementation with JavaFx
 
Cookies: HTTP state management mechanism
Cookies: HTTP state management mechanismCookies: HTTP state management mechanism
Cookies: HTTP state management mechanism
 
Tourism market segmentation in context of nepal
Tourism market segmentation in context of nepalTourism market segmentation in context of nepal
Tourism market segmentation in context of nepal
 
Decision Support and Knowledge Based Systems
Decision Support and Knowledge Based SystemsDecision Support and Knowledge Based Systems
Decision Support and Knowledge Based Systems
 
Grid computing the grid
Grid computing the gridGrid computing the grid
Grid computing the grid
 
Restaurant Guide: A GPS based Android App
Restaurant Guide: A GPS based Android AppRestaurant Guide: A GPS based Android App
Restaurant Guide: A GPS based Android App
 
Project time management
Project time managementProject time management
Project time management
 

Recently uploaded

Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management systemChristalin Nelson
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfJemuel Francisco
 
Expanded definition: technical and operational
Expanded definition: technical and operationalExpanded definition: technical and operational
Expanded definition: technical and operationalssuser3e220a
 
How to Manage Engineering to Order in Odoo 17
How to Manage Engineering to Order in Odoo 17How to Manage Engineering to Order in Odoo 17
How to Manage Engineering to Order in Odoo 17Celine George
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Seán Kennedy
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...Nguyen Thanh Tu Collection
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17Celine George
 
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxQ4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxlancelewisportillo
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxHumphrey A Beña
 
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptxDIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptxMichelleTuguinay1
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designMIPLM
 
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)lakshayb543
 
Congestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationCongestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationdeepaannamalai16
 
The State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and FindingsThe State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and FindingsRay Poynter
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataBabyAnnMotar
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfVanessa Camilleri
 
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptxAUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptxiammrhaywood
 

Recently uploaded (20)

YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptxYOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
YOUVE_GOT_EMAIL_PRELIMS_EL_DORADO_2024.pptx
 
Concurrency Control in Database Management system
Concurrency Control in Database Management systemConcurrency Control in Database Management system
Concurrency Control in Database Management system
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
 
Expanded definition: technical and operational
Expanded definition: technical and operationalExpanded definition: technical and operational
Expanded definition: technical and operational
 
How to Manage Engineering to Order in Odoo 17
How to Manage Engineering to Order in Odoo 17How to Manage Engineering to Order in Odoo 17
How to Manage Engineering to Order in Odoo 17
 
Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
 
How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17How to Add Barcode on PDF Report in Odoo 17
How to Add Barcode on PDF Report in Odoo 17
 
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptxLEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
 
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptxQ4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
Q4-PPT-Music9_Lesson-1-Romantic-Opera.pptx
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
 
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptxDIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
DIFFERENT BASKETRY IN THE PHILIPPINES PPT.pptx
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-design
 
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
Visit to a blind student's school🧑‍🦯🧑‍🦯(community medicine)
 
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptxINCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
INCLUSIVE EDUCATION PRACTICES FOR TEACHERS AND TRAINERS.pptx
 
Congestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentationCongestive Cardiac Failure..presentation
Congestive Cardiac Failure..presentation
 
The State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and FindingsThe State of AI in Insights and Research 2024: Results and Findings
The State of AI in Insights and Research 2024: Results and Findings
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped data
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdf
 
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptxAUDIENCE THEORY -CULTIVATION THEORY -  GERBNER.pptx
AUDIENCE THEORY -CULTIVATION THEORY - GERBNER.pptx
 

Warehouse based Intelligent Banking Transaction Analysis System

  • 1. BY Bibek Subedi (066 BCT 506) Dinesh Subedi (066 BCT 512) Jivan Nepali (066 BCT 517) Laxmi Kadariya (066 BCT 518)
  • 2. BACKGROUND  Data warehousing ? is the process of data asset acquisition, organization, and management.  Decision Support ? is the application of managed data assets to business and clinical decision making needs to achieve business intelligence  Business Intelligence (BI) ? is the transformation of data into information, and through discovery, transforming that information into knowledge
  • 3. NEED OF BI IN BANKING SECTOR OF NEPAL Competitive Market High Churn Rates Massive Data Collection
  • 4. ATM CARD SKIMMING & COUNTERFEIT CARD FRAUD A smaller skimmer that looks just like a normal card entry slot and attached to the ATM rain cover.
  • 5. OBJECTIVES Debit card fraud detection Customer churn behavior prediction CRM (Customer Relationship Management) with customer segmentation
  • 7. PLATFORM & TOOLS ETL Tool: Korn Shell (ksh) Scripting Database: Oracle 11g Presentation/ Front-end Tool: OBIEE 11g Project Management Tool: Redmine Version Control Tool: Subversion (svn)