SlideShare ist ein Scribd-Unternehmen logo
1 von 13
DATA WAREHOUSING – BANKING SECTOR
SYBASE IQ - PNB BANK
G.NEELESH
Roll No: 28
MBA 1st semister
DATA WAREHOUSING (DW), WHAT IS
IT?
1. It is combining data from multiple and usually
varied sources into one comprehensive and easily
manipulated database.
2. DW includes queries, analysis and reporting.
Because data warehousing creates one database
in the end, the number of sources can be anything
you want it to be, provided that the system can
handle the volume, of course.
3. The final result, however, is homogeneous data,
which can be more easily manipulated.
WHY DATA WAREHOUSING (DW)?
DW is commonly used by companies to analyze trends over time.
In other words, companies may very well use data warehousing to view day-to-
day operations, but its primary function is facilitating strategic planning resulting
from long-term data overviews.
From such overviews, business models, forecasts, and other reports and
projections can be made.
DW is not the be-all and end-all for storing all of a company's data. Rather, data
warehousing is used to house the necessary data for specific analysis.
WHY “DATA WAREHOUSING (DW)” IS
PREVALENT IN BANKING?
A. Banks worldwide use DW solutions normally for profitability analysis
and to enhance their risk management capability.
B. Customer Relationship Management (CRM) solutions are also being
increasingly deployed by banks to enhance their ability to manage and
grow their customer base in the most desired manner.
SYBASE IQ
Let us learn about Sybase IQ by the following:
1. What is Sybase IQ?
2. Why do organizations need Sybase IQ?
3. What is unique about Sybase IQ?
1. WHAT IS SYBASE IQ?
•Sybase IQ is a highly optimized analytics server, designed specifically to deliver
ultra-high-speed business intelligence and reporting on standard hardware and
operating systems.
•Sybase IQ is architected for analytics—not transactions—with a structure.
•The patented indexing makes it the preeminent choice for data warehousing
and reporting.
•Sybase IQ provides a reduction in disk and CPU requirements (by reducing I/O
bottlenecks) compared to traditional systems that have to be retro-fitted to
support DataWarehousing and Analytics.
2. WHY DO ORGANIZATIONS NEED
SYBASE IQ?
Most organizations are
struggling to deal with
data management and
data growth. As data
explodes, so does the
cost of managing that
data.
They apply more
processing power to
deal with very large
databases and
increasing numbers
of users, with low
cost.
Although the “hard
costs” of storage are
decreasing, the
“soft costs”
associated with
maintaining data
are substantial.
Sybase IQ resolves
all these business
pains.
3. WHAT IS UNIQUE ABOUT
SYBASE IQ?
Faster—Delivers ad
hoc query
performance up to
100 times faster than
a traditional systems.
LowerTCO—Requires
less storage by
compressing raw
data up to 70%, while
traditionally
databases explode
data by 150-500%.
Easier—Easier to
maintain than
traditional databases
and does not require
time and resource
intensive tuning to
obtain excellent
performance.
More Scalable—
Offers near linear
user and data
scalability to support
thousands of users
and terabytes of data.
PNB BANK
PNB bank is one of India’s largest nationalised bank.The bank has a network
of 1,308 branches and 3,950 ATMs as well as robust Internet banking.
PNB Bank offers a wide range of banking products and financial services to
corporate and retail customers through a variety of delivery channels and
through its specialized subsidiaries and affiliates in the areas of investment
banking, life and non-life insurance, venture
capital and asset management.
PNB BANK – SYBASE IQ
In India, PNB bank is the pioneer in implementing a data warehousing (DW) solution, which is
powered by Sybase IQ, a highly optimized business intelligence, analytics and data
warehousing solution for delivering dramatically faster results at a low cost.
Previously, the bank was dependent on its DW from “Teradata”.With dramatic growth in its
users, amount of data, and source stations, etc., the increasing cost of scaling and
maintenance and mounting system unavailability posed difficulties for the bank.To resolve
these recurring problems, the bank undertook a migration of the enterprise data warehouse
fromTeradata to Sybase IQ.
Applauding the strength of Sybase IQ, PravirVohra, GroupChiefTechnology Officer, says,
“Our business requirements were addressed well with minimum infrastructure. Sybase IQ is
an excellent product.”
SYBASE IQ – THE PREFERRED
CHOICE
PNB Bank was using “Teradata” for its data warehouse.The closed box architecture ofTeradata
imposed restrictions on scalability. Secondly, querying and loading could not happen
simultaneously. Queries could only be run during business hours because the loading of data
had to take place during off-business hours.The queries did not reflect the most current data.
These issues compelled PNB Bank to look for more efficient and flexible solutions.The solution
would have to address not only current issues, but accommodate future growth expectations
and business requirements.
During this rigorous testing, Sybase IQ delivered faster results on independent hardware and
operating systems with minimum infrastructure.
TRANSFORMATION OF DATA TO
SYBASE IQ
Data from approximately 14 source systems is extracted and loaded on to the
writer node of Sybase IQ, hosted on IBM System p-series hardware.The
enterprise SAN storage is connected to both the reader and write node and
the business users run queries on the reader node of Sybase IQ.The prime
challenge faced by the Sybase team was that ICICI Bank wanted the
migration to be transparent to business users.
More than threeTerabyte of data was required to be moved into Sybase IQ,
typically requiring a large amount of time and storage using traditional
systems. However, Sybase IQ achieved an exceptional speed of two million
records per second, so data loading with Sybase IQ took a mere two days.
The entire migration process for the new system took less than three
months.
The simplicity of the system is exhibited by the fact that DBAs, developers
and business users were running on the new system after only a five day
training session.
FUNCTIONALITY OF SYBASE IQ IN PNB
BANK
1. The source systems maintain data from various divisions of ICICI Bank like its
Retail Banking (liabilities and assets), call centre, Internet Banking and Demat
units, supporting over 3.5TB of data.
2. Using Sybase IQ’s unique concurrent user scalability, ICICI Bank now supports
over 150 users without any performance degradation.
3. Sybase IQ drastically reduced query time. Queries that used to take over four
hours before, now complete in a quarter of the time.
4. Additionally, system maintenance has been streamlined and can be carried out
by “in-house developers”.
5. With theTeradata warehouse, loading scripts were run, which made the system
difficult to modify and maintain. However, with the new system, load
automation has been achieved through Sybase IQ stored procedures.

Weitere ähnliche Inhalte

Was ist angesagt?

Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...
Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...
Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...Denodo
 
Can data virtualization uphold performance with complex queries?
Can data virtualization uphold performance with complex queries?Can data virtualization uphold performance with complex queries?
Can data virtualization uphold performance with complex queries?Denodo
 
Data Works Summit Munich 2017 - Worldpay - Multi Tenancy Clusters
Data Works Summit Munich 2017 - Worldpay - Multi Tenancy ClustersData Works Summit Munich 2017 - Worldpay - Multi Tenancy Clusters
Data Works Summit Munich 2017 - Worldpay - Multi Tenancy ClustersDavid Walker
 
Pervasive analytics through data & analytic centricity
Pervasive analytics through data & analytic centricityPervasive analytics through data & analytic centricity
Pervasive analytics through data & analytic centricityCloudera, Inc.
 
Gartner magic quadrant for data warehouse database management systems
Gartner magic quadrant for data warehouse database management systemsGartner magic quadrant for data warehouse database management systems
Gartner magic quadrant for data warehouse database management systemsparamitap
 
Hitachi Unified Storage VM Flash -- Datasheet
Hitachi Unified Storage VM Flash -- DatasheetHitachi Unified Storage VM Flash -- Datasheet
Hitachi Unified Storage VM Flash -- DatasheetHitachi Vantara
 
Traditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overviewTraditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overviewNagaraj Yerram
 
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
 
DATA WAREHOUSING
DATA WAREHOUSINGDATA WAREHOUSING
DATA WAREHOUSINGKing Julian
 
Anexinet Big Data Solutions
Anexinet Big Data SolutionsAnexinet Big Data Solutions
Anexinet Big Data SolutionsMark Kromer
 
Accelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and VisualizationAccelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and VisualizationDenodo
 
Data Virtualization: An Essential Component of a Cloud Data Lake
Data Virtualization: An Essential Component of a Cloud Data LakeData Virtualization: An Essential Component of a Cloud Data Lake
Data Virtualization: An Essential Component of a Cloud Data LakeDenodo
 
A More Efficient Way to Automate Cloud Infrastructure Solution Profile
A More Efficient Way to Automate Cloud Infrastructure Solution ProfileA More Efficient Way to Automate Cloud Infrastructure Solution Profile
A More Efficient Way to Automate Cloud Infrastructure Solution ProfileHitachi Vantara
 
A-B-C Strategies for File and Content Brochure
A-B-C Strategies for File and Content BrochureA-B-C Strategies for File and Content Brochure
A-B-C Strategies for File and Content BrochureHitachi Vantara
 
Modern data warehouse
Modern data warehouseModern data warehouse
Modern data warehouseStephen Alex
 
Enterprise resource planning system & data warehousing implementation
Enterprise resource planning system & data warehousing implementationEnterprise resource planning system & data warehousing implementation
Enterprise resource planning system & data warehousing implementationSumya Abdelrazek
 
From Traditional Data Warehouse To Real Time Data Warehouse
From Traditional Data Warehouse To Real Time Data WarehouseFrom Traditional Data Warehouse To Real Time Data Warehouse
From Traditional Data Warehouse To Real Time Data WarehouseOsama Hussein
 
IOUG93 - Technical Architecture for the Data Warehouse - Presentation
IOUG93 - Technical Architecture for the Data Warehouse - PresentationIOUG93 - Technical Architecture for the Data Warehouse - Presentation
IOUG93 - Technical Architecture for the Data Warehouse - PresentationDavid Walker
 
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...Analyst View of Data Virtualization: Conversations with Boulder Business Inte...
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...Denodo
 

Was ist angesagt? (20)

Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...
Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...
Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...
 
Can data virtualization uphold performance with complex queries?
Can data virtualization uphold performance with complex queries?Can data virtualization uphold performance with complex queries?
Can data virtualization uphold performance with complex queries?
 
Data Works Summit Munich 2017 - Worldpay - Multi Tenancy Clusters
Data Works Summit Munich 2017 - Worldpay - Multi Tenancy ClustersData Works Summit Munich 2017 - Worldpay - Multi Tenancy Clusters
Data Works Summit Munich 2017 - Worldpay - Multi Tenancy Clusters
 
Pervasive analytics through data & analytic centricity
Pervasive analytics through data & analytic centricityPervasive analytics through data & analytic centricity
Pervasive analytics through data & analytic centricity
 
Gartner magic quadrant for data warehouse database management systems
Gartner magic quadrant for data warehouse database management systemsGartner magic quadrant for data warehouse database management systems
Gartner magic quadrant for data warehouse database management systems
 
Hitachi Unified Storage VM Flash -- Datasheet
Hitachi Unified Storage VM Flash -- DatasheetHitachi Unified Storage VM Flash -- Datasheet
Hitachi Unified Storage VM Flash -- Datasheet
 
Traditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overviewTraditional Data-warehousing / BI overview
Traditional Data-warehousing / BI overview
 
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...
 
DATA WAREHOUSING
DATA WAREHOUSINGDATA WAREHOUSING
DATA WAREHOUSING
 
Anexinet Big Data Solutions
Anexinet Big Data SolutionsAnexinet Big Data Solutions
Anexinet Big Data Solutions
 
Accelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and VisualizationAccelerate Self-Service Analytics with Data Virtualization and Visualization
Accelerate Self-Service Analytics with Data Virtualization and Visualization
 
Data Virtualization: An Essential Component of a Cloud Data Lake
Data Virtualization: An Essential Component of a Cloud Data LakeData Virtualization: An Essential Component of a Cloud Data Lake
Data Virtualization: An Essential Component of a Cloud Data Lake
 
A More Efficient Way to Automate Cloud Infrastructure Solution Profile
A More Efficient Way to Automate Cloud Infrastructure Solution ProfileA More Efficient Way to Automate Cloud Infrastructure Solution Profile
A More Efficient Way to Automate Cloud Infrastructure Solution Profile
 
A-B-C Strategies for File and Content Brochure
A-B-C Strategies for File and Content BrochureA-B-C Strategies for File and Content Brochure
A-B-C Strategies for File and Content Brochure
 
Hadoop & Data Warehouse
Hadoop & Data Warehouse Hadoop & Data Warehouse
Hadoop & Data Warehouse
 
Modern data warehouse
Modern data warehouseModern data warehouse
Modern data warehouse
 
Enterprise resource planning system & data warehousing implementation
Enterprise resource planning system & data warehousing implementationEnterprise resource planning system & data warehousing implementation
Enterprise resource planning system & data warehousing implementation
 
From Traditional Data Warehouse To Real Time Data Warehouse
From Traditional Data Warehouse To Real Time Data WarehouseFrom Traditional Data Warehouse To Real Time Data Warehouse
From Traditional Data Warehouse To Real Time Data Warehouse
 
IOUG93 - Technical Architecture for the Data Warehouse - Presentation
IOUG93 - Technical Architecture for the Data Warehouse - PresentationIOUG93 - Technical Architecture for the Data Warehouse - Presentation
IOUG93 - Technical Architecture for the Data Warehouse - Presentation
 
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...Analyst View of Data Virtualization: Conversations with Boulder Business Inte...
Analyst View of Data Virtualization: Conversations with Boulder Business Inte...
 

Ähnlich wie Neelesh it assignment

DWH: stop wasting time!
DWH: stop wasting time!DWH: stop wasting time!
DWH: stop wasting time!Sadas
 
Traditional BI vs. Business Data Lake – A Comparison
Traditional BI vs. Business Data Lake – A ComparisonTraditional BI vs. Business Data Lake – A Comparison
Traditional BI vs. Business Data Lake – A ComparisonCapgemini
 
Database in banking industries
Database in banking industriesDatabase in banking industries
Database in banking industriesnajammm007
 
Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)Denodo
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceVijayMohan Vasu
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceVijayMohan Vasu
 
Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.Denodo
 
Business Intelligence Solution on Windows Azure
Business Intelligence Solution on Windows AzureBusiness Intelligence Solution on Windows Azure
Business Intelligence Solution on Windows AzureInfosys
 
Traditional data word
Traditional data wordTraditional data word
Traditional data wordorcoxsm
 
Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida
Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida  Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida
Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida CLARA CAMPROVIN
 
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORTSAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORTSybase Türkiye
 
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)Denodo
 
SAP IQ 16 Product Annoucement
SAP IQ 16 Product AnnoucementSAP IQ 16 Product Annoucement
SAP IQ 16 Product AnnoucementDobler Consulting
 
Analytics on system z final
Analytics on system z finalAnalytics on system z final
Analytics on system z finalPeter Schouboe
 
KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data VirtualizationKASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data VirtualizationDenodo
 

Ähnlich wie Neelesh it assignment (20)

DWH: stop wasting time!
DWH: stop wasting time!DWH: stop wasting time!
DWH: stop wasting time!
 
Traditional BI vs. Business Data Lake – A Comparison
Traditional BI vs. Business Data Lake – A ComparisonTraditional BI vs. Business Data Lake – A Comparison
Traditional BI vs. Business Data Lake – A Comparison
 
Database in banking industries
Database in banking industriesDatabase in banking industries
Database in banking industries
 
Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)Introduction to Modern Data Virtualization 2021 (APAC)
Introduction to Modern Data Virtualization 2021 (APAC)
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligence
 
Introduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligenceIntroduction to data warehousing and business intelligence
Introduction to data warehousing and business intelligence
 
Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.Why Data Virtualization? An Introduction.
Why Data Virtualization? An Introduction.
 
Business Intelligence Solution on Windows Azure
Business Intelligence Solution on Windows AzureBusiness Intelligence Solution on Windows Azure
Business Intelligence Solution on Windows Azure
 
Traditional data word
Traditional data wordTraditional data word
Traditional data word
 
Accelerating Data Warehouse Modernization
Accelerating Data Warehouse ModernizationAccelerating Data Warehouse Modernization
Accelerating Data Warehouse Modernization
 
Data warehousing
Data warehousingData warehousing
Data warehousing
 
Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida
Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida  Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida
Jet Reports es la herramienta para construir el mejor BI y de forma mas rapida
 
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORTSAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
SAP REAL TIME DATA PLATFORM WITH SYBASE SUPPORT
 
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
Bridging the Last Mile: Getting Data to the People Who Need It (APAC)
 
ESGYN Overview
ESGYN OverviewESGYN Overview
ESGYN Overview
 
SAP IQ 16 Product Annoucement
SAP IQ 16 Product AnnoucementSAP IQ 16 Product Annoucement
SAP IQ 16 Product Annoucement
 
The new EDW
The new EDWThe new EDW
The new EDW
 
Analytics on system z final
Analytics on system z finalAnalytics on system z final
Analytics on system z final
 
KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data VirtualizationKASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
KASHTECH AND DENODO: ROI and Economic Value of Data Virtualization
 
NZS-4532 - Bringing Historical Data to Life with IBMs SMF Data Engine
NZS-4532 - Bringing Historical Data to Life with IBMs SMF Data EngineNZS-4532 - Bringing Historical Data to Life with IBMs SMF Data Engine
NZS-4532 - Bringing Historical Data to Life with IBMs SMF Data Engine
 

Kürzlich hochgeladen

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businesspanagenda
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Jeffrey Haguewood
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAndrey Devyatkin
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
Ransomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfRansomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfOverkill Security
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWERMadyBayot
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
Cyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdfCyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdfOverkill Security
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfOrbitshub
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Zilliz
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 

Kürzlich hochgeladen (20)

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Ransomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfRansomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdf
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Cyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdfCyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 

Neelesh it assignment

  • 1. DATA WAREHOUSING – BANKING SECTOR SYBASE IQ - PNB BANK G.NEELESH Roll No: 28 MBA 1st semister
  • 2. DATA WAREHOUSING (DW), WHAT IS IT? 1. It is combining data from multiple and usually varied sources into one comprehensive and easily manipulated database. 2. DW includes queries, analysis and reporting. Because data warehousing creates one database in the end, the number of sources can be anything you want it to be, provided that the system can handle the volume, of course. 3. The final result, however, is homogeneous data, which can be more easily manipulated.
  • 3. WHY DATA WAREHOUSING (DW)? DW is commonly used by companies to analyze trends over time. In other words, companies may very well use data warehousing to view day-to- day operations, but its primary function is facilitating strategic planning resulting from long-term data overviews. From such overviews, business models, forecasts, and other reports and projections can be made. DW is not the be-all and end-all for storing all of a company's data. Rather, data warehousing is used to house the necessary data for specific analysis.
  • 4. WHY “DATA WAREHOUSING (DW)” IS PREVALENT IN BANKING? A. Banks worldwide use DW solutions normally for profitability analysis and to enhance their risk management capability. B. Customer Relationship Management (CRM) solutions are also being increasingly deployed by banks to enhance their ability to manage and grow their customer base in the most desired manner.
  • 5. SYBASE IQ Let us learn about Sybase IQ by the following: 1. What is Sybase IQ? 2. Why do organizations need Sybase IQ? 3. What is unique about Sybase IQ?
  • 6. 1. WHAT IS SYBASE IQ? •Sybase IQ is a highly optimized analytics server, designed specifically to deliver ultra-high-speed business intelligence and reporting on standard hardware and operating systems. •Sybase IQ is architected for analytics—not transactions—with a structure. •The patented indexing makes it the preeminent choice for data warehousing and reporting. •Sybase IQ provides a reduction in disk and CPU requirements (by reducing I/O bottlenecks) compared to traditional systems that have to be retro-fitted to support DataWarehousing and Analytics.
  • 7. 2. WHY DO ORGANIZATIONS NEED SYBASE IQ? Most organizations are struggling to deal with data management and data growth. As data explodes, so does the cost of managing that data. They apply more processing power to deal with very large databases and increasing numbers of users, with low cost. Although the “hard costs” of storage are decreasing, the “soft costs” associated with maintaining data are substantial. Sybase IQ resolves all these business pains.
  • 8. 3. WHAT IS UNIQUE ABOUT SYBASE IQ? Faster—Delivers ad hoc query performance up to 100 times faster than a traditional systems. LowerTCO—Requires less storage by compressing raw data up to 70%, while traditionally databases explode data by 150-500%. Easier—Easier to maintain than traditional databases and does not require time and resource intensive tuning to obtain excellent performance. More Scalable— Offers near linear user and data scalability to support thousands of users and terabytes of data.
  • 9. PNB BANK PNB bank is one of India’s largest nationalised bank.The bank has a network of 1,308 branches and 3,950 ATMs as well as robust Internet banking. PNB Bank offers a wide range of banking products and financial services to corporate and retail customers through a variety of delivery channels and through its specialized subsidiaries and affiliates in the areas of investment banking, life and non-life insurance, venture capital and asset management.
  • 10. PNB BANK – SYBASE IQ In India, PNB bank is the pioneer in implementing a data warehousing (DW) solution, which is powered by Sybase IQ, a highly optimized business intelligence, analytics and data warehousing solution for delivering dramatically faster results at a low cost. Previously, the bank was dependent on its DW from “Teradata”.With dramatic growth in its users, amount of data, and source stations, etc., the increasing cost of scaling and maintenance and mounting system unavailability posed difficulties for the bank.To resolve these recurring problems, the bank undertook a migration of the enterprise data warehouse fromTeradata to Sybase IQ. Applauding the strength of Sybase IQ, PravirVohra, GroupChiefTechnology Officer, says, “Our business requirements were addressed well with minimum infrastructure. Sybase IQ is an excellent product.”
  • 11. SYBASE IQ – THE PREFERRED CHOICE PNB Bank was using “Teradata” for its data warehouse.The closed box architecture ofTeradata imposed restrictions on scalability. Secondly, querying and loading could not happen simultaneously. Queries could only be run during business hours because the loading of data had to take place during off-business hours.The queries did not reflect the most current data. These issues compelled PNB Bank to look for more efficient and flexible solutions.The solution would have to address not only current issues, but accommodate future growth expectations and business requirements. During this rigorous testing, Sybase IQ delivered faster results on independent hardware and operating systems with minimum infrastructure.
  • 12. TRANSFORMATION OF DATA TO SYBASE IQ Data from approximately 14 source systems is extracted and loaded on to the writer node of Sybase IQ, hosted on IBM System p-series hardware.The enterprise SAN storage is connected to both the reader and write node and the business users run queries on the reader node of Sybase IQ.The prime challenge faced by the Sybase team was that ICICI Bank wanted the migration to be transparent to business users. More than threeTerabyte of data was required to be moved into Sybase IQ, typically requiring a large amount of time and storage using traditional systems. However, Sybase IQ achieved an exceptional speed of two million records per second, so data loading with Sybase IQ took a mere two days. The entire migration process for the new system took less than three months. The simplicity of the system is exhibited by the fact that DBAs, developers and business users were running on the new system after only a five day training session.
  • 13. FUNCTIONALITY OF SYBASE IQ IN PNB BANK 1. The source systems maintain data from various divisions of ICICI Bank like its Retail Banking (liabilities and assets), call centre, Internet Banking and Demat units, supporting over 3.5TB of data. 2. Using Sybase IQ’s unique concurrent user scalability, ICICI Bank now supports over 150 users without any performance degradation. 3. Sybase IQ drastically reduced query time. Queries that used to take over four hours before, now complete in a quarter of the time. 4. Additionally, system maintenance has been streamlined and can be carried out by “in-house developers”. 5. With theTeradata warehouse, loading scripts were run, which made the system difficult to modify and maintain. However, with the new system, load automation has been achieved through Sybase IQ stored procedures.