<Insert Picture Here>




Maximizing Return for your Data Warehouse
Agenda


• Top Business Imperatives and Data
  Requirements to Succeed                      <Insert Picture Here>

• Data Warehouse Basics and Challenges
   • The Purpose of Data Warehouse
   • Why Real-Time Data Warehouse for BI?
• Real-Time Data Integration Considerations
   • Traditional Vs Real-time Data Warehouse
   • Data Quality & Profiling
• Oracle Data Integration Solution
• Customer Case Studies




                                                                2
Top Business Imperatives and Data
 Requirements to Succeed
 Access to Timely, Trusted, and Consistent data

                    Operational & Analytical
                    Business Applications


                               Risk      CRM / Direct
              Improve       Management    Marketing
                                                         Mergers &
              Decisions &                               Acquisitions
              Regulatory
              Compliance
Real-Time                                                        Data Quality
Data
Integration                                                   Data
                 DataMart /     MDM /
                                                           Migration &
                 BI                        DWH / BI       Consolidation
                                 BI


                              IT Projects

                                                                                3
Why Real-Time DataWarehouse for BI?


1. Business Driver:                Real-Time= Relevant
                                   and actionable
  To compete more effectively      information
     by using better insights in
     day to day operations and
                                     Improved insights for
     strategic decisions             operational decision
                                     making

2. Technical Driver
                                        Better customer service
  To move away from batch               and cost savings via
     ETL jobs and eliminate             operational efficiencies
     the impact it has on the IT
     infrastructure                        Increased profitability,
                                           customer retention, and
                                           competitive advantage



                                                                      4
Integration Challenges
Fragmented Approach

                                        Analytics                                   Business
                                                                 Packaged          Intelligence
 Custom
Reporting                                                       Applications
                                            Accessibility                                                    Enterprise
                                                                                                            Performance

                                               Data
                                             Replication
                       Data
                     Migration                                                     Data
                                                                                Warehousing

         Up-To-Date
  Data Silos                          Data Marts                 Data Hubs
                                                                                              Trusted
                                                                                                    Data
                                                                                                  Federation

                                                                                                                  Data Access

         information  Batch Scripts
                                                       Custom
                                                                                   SQL
                                                                                          InformationJava




     OLTP & ODS                                        Oracle, PeopleSoft,     Files, Excel              OLAP
      Systems           Data Warehouse,
                        Data Warehouse,
                         Data Warehouse,                  Siebel, SAP,             XML
                             Data Mart
                             Data Mart
                             Data Mart                   Custom Apps



               High Cost of                        Lack of clean,                  Multiple standards,
                Custom Coding                       consistent data                 disciplines


                                                                                                                                5
Data Warehouse and It’s Process
A centralized repository containing comprehensive detailed and
summary data that provides a complete view of customers,
suppliers, business processes, and transactions, from a
historical perspective with little volatility.

             Typically loaded on a nightly basis with batch extracts from source
             transaction processing systems such as CRM, ERP, etc to support reporting
             and analysis.
  Sources                                              Target

                                              DATA WAREHOUSE
  ERP/
  CRM




                        Integrate                DM1            DM2
                      Data Cleansing   Load
                                                 DM3            DM4
            Extract       Data
    RDBMS




                       Enrichment

                        Transform

                                                Analytical Reporting
                                                 Ad-hoc Reporting
                                                   Dashboards
                                                    Scorecards


                                                                                     6
Business Drivers For a Modern Data Integration
        Platform & Real-Time DWH
Demand for Continuous, Real-Time,
Trusted Information

                                               Real-Time
                                               Enterprise

Continuous Availability                                                               Real-Time Data
for 24/7 Global Operations                                             for Intelligence & Operations

• Continuous uptime in event of disaster                        • Up-to-the second data for operations
• No downtime during planned outage                         • Access to timely information for analysis
• Low-impact data capture for integration                            • Data distribution across regions




                                            Trusted Information
                                     • Consistent with other systems
                                           •High data integrity



                                                                                                    7
Traditional Vs Real-Time Data Warehouse

       Traditional Data Warehouse             Real-Time Data Warehouse
                                                                       Transformation & Quality
                                                                             (ETL / ELT &
                                                                           Data Cleansing)

                ETL + CDC
                                                             Real-Time
    Legacy,                                                  Continuous Feeds
    Packaged                   Enterprise
    Apps,                      Data             Legacy,
    OLTP                       Warehouse        Packaged              Enterprise Data
    Databases                                   Apps, OLTP            Warehouse/MDM




•   Day+ old data                           • Timely, relevant data are continuous
                                              feed from operational systems
•   Batch data extracts within specified
                                            • No batch windows on OLTP
    “off business hours”                    • Sub-second latency
•   A middle-tier server for                • No impact on source systems
    transformations                         • Read-consistent changed data with
                                              referential integrity
•   Process interruptions impact data
                                            • Transformations at capture, delivery or
    recoverability                            within the database

                                                                                              8
Oracle Complete Data Integration
           Solution
Oracle Data Integration: 3 Key Products
         Addressing operational and strategic analysis


                                                                   Oracle Data Quality
    Oracle Data Integrator         Oracle GoldenGate                   & Profiling
•      E-LT                    •    Real-Time data            •     Discover data
•      Bulk data movement           capture and delivery            problems
•      Complex                 •    Low impact and non-       •     Global data cleansing
       transformation               invasive                  •     Data standardization
•      Easy to use GUI         •    Transactional integrity   •     Fuzzy matching
       design                  •    Guaranteed delivery       •     Heterogeneous
•      Data lineage & impact   •    Delivers continuous
       analysis                     availability
•      Heterogeneous           •    Heterogeneous



       Accessibility            Up-to-Date Information            Trusted Information



                                                                                         10
Oracle Data Integrator Enterprise Edition
       Optimized E-LT for Improved Performance




    Legacy
   Sources

                           E-LT Transformation          Any Data
                           vs. E-T-L                    Warehouse
Application                Declarative Set-based
  Sources
                           design
                           Pluggable Knowledge          Any
                           Modules                      Planning
                                                        System
  OLTP DB                  Hot-pluggable Architecture
  Sources

                           Change Data Capture for
                           Dynamic Updates

                                                                   11
Data Warehouse Bulk Loading w/E-LT
  Fastest ELT Solution for your Data Warehouse
                                Solution
                                    • ODI for bulk loading Data Warehouse
Extract
                                    • Run ODI Agent within Data
                                      Warehouse JVM
                                    • Fastest possible data
     Load                             transformations
                                    • Heterogeneous and loads any 3rd
                                      party data warehouse.

                                Benefits
     Transform
                                    • No extra ETL servers
                                    • RDBMS Specific Knowledge
                                      Modules
                                    • Exploit DW RDBMS Optimizer
                                    • Easier to deploy than conventional
                                      ETL tools
                                    • Faster time to market
                                    • Enforce DW Best Practices


                                                                           12
Optimized for Exadata
Fastest E-L-T Processing


                • Massively parallel high volume hardware to
                  quickly process vast amounts of data
       OLAP         • Exadata runs data intensive processing
                      directly in storage

                • Most complete analytic capabilities
                    • OLAP, Statistics, Spatial, Data Mining, Real-time
                      transactional ETL, Efficient point queries
        ELT
                • Powerful warehouse specific optimizations
                    • Flexible Partitioning, Bitmap Indexing, Join indexing,
                      Materialized Views, Result Cache

    Data Mining •   E-LT runs 20X faster only with Oracle

        New


                                                                               13
ODI is Faster
Up to 7TB per hour of real world data loading and complex transformations
                                 ODI ELT (on Exadata)
                                  ODI scales with Exadata
                                  ODI runs on Exadata – no ETL hardware required
                                  Common administration, monitoring and
                                   management
                                  All the benefits of rapid tools-based ETL
                                   development

                                 Conventional ETL
                                  As data sets grow additional hardware ($$) needed
                                  ETL parallel optimization and design ($$$) is heavily
                                  dependent on resources available to the ETL system
                                  Poor performance – transformations take place
                                  outside of database, require staging tables
                                  Lack of light-weight architecture for rapid data
                                  loading
                                  ETL engine hardware resources only used for ETL
                                  Hardware not co located, multiple vendors
                                  Different management, monitoring and administration
                                  from database and BI infrastructure ($$)


                                                                                   14
Differentiator: E-LT Architecture
     High Performance
Conventional: Separate ETL Server               Conventional ETL Architecture
  • Proprietary ETL Engine
  • Poor Performance                                  Extract       Transform    Load
  • High Costs for Separate Standalone Server


Oracle: No New Servers
  • Lower Cost: Leverage Compute Resources &
    Partition Workload efficiently
  • Efficient: Exploits Database Optimizer
  • Fast: Exploits Native Bulk Load & Other
    Database Interfaces                         Next Generation Architecture
  • Scalable: Scales as you add Processors to
    Source or Target
                                                        “E-LT”
Benefits                                           Transform                     Transform
  Optimal Performance & Scalability                            Extract   Load

  Better Hardware Leverage
  Easier to Manage & Lower Cost

                                                                                             15
Oracle Data Profiling and Quality
 Integrated Data Profiling and Quality for Customer Data

             Oracle Data Profiling, Oracle Data Quality

              Metadata Profiling of Source & Target

Any Source    Duplicate Detection, Matching & Merging
System
              Global Address Cleansing

              Data Control and Visibility                    Any Data
                                                            Warehouse
              Optimized for Customer/Party Data                 &
                                                              MDM


                Oracle Data Integrator Enterprise Edition
                                                             Any
                                                             Planning
                                                             System




                                                                    16
Oracle Data Quality
Ensure Data Quality as Part of the Integration Process
Best-in-class data quality and profiling for
integration processes
                                                ODI EE


                                        Better Data Visibility
                                        Tighter Data Control
                                        Greater Data Accuracy




Visual Data Quality      Oracle Data Profiling        Oracle Data Quality
Tools

                           Metadata Profiling          Duplicate Detection,
                           of Source & Target          Matching & Merging


                                                                              17
Sample Data Quality Issues

COMPLETENESS                      Completeness
                                   What data is
                                   missing or
CONFORMITY                         unusable?


CONSISTENCY     Consistency
               What data values
               give conflicting
DUPLICATION     information?

                                                          Accuracy              Conformity
ACCURACY                                                                    What data is stored
                                                         What data is
                                                      incorrect or out of   in a non-standard
                                                            date?                 format?


                                                     Duplication
                                                  What data records
                                                   or attributes are
                                                      repeated?




                                                                                             18
Oracle GoldenGate
 Enterprise-wide Solution for Real Time Data Needs



                             Zero Downtime
                                                      New DB/
                             Migration and           OS/HW/App
                             Upgrades

                              Active-Active High Fully Active         • Reduce Costs
                              Availability     Distributed Database

          Log Based, Real-                                            • Lower Risks
         Time Change Data
              Capture         Query Offloading        Reporting         • Achieve
             Oracle                                   Database
           GoldenGate
                                                                        Operational
                                              ETL                       Excellence
                                    ODS                EDW
                                      ETL


Heterogeneous                      Real-time BI        EDW
Source Systems

                             Data Distribution Global Data Centers


                               SOA/EDA


                                                                                       19
Data Movement plus Real-Time
Oracle GoldenGate provides low-impact capture, routing, transformation,
and delivery of transactional data across heterogeneous environments in
                                 real time


     Key Differentiators:

            Performance          Non-intrusive, low-impact, sub-second latency



       Flexible and Extensible   Open, modular architecture - Supports
                                 heterogeneous sources and targets


              Reliable           Maintains transactional integrity - Resilient
                                 against interruptions and failures




                                                                                 20
Oracle GoldenGate Architecture
       Designed for Speed, Flexibility and Reliability


                  Trail                                    Trail
        Capture                                                    Delivery
                                    LAN/WAN
                                    Internet

                                    TCP/IP

      Source                                                              Target
Oracle & Non-Oracle               Bi-directional                   Oracle & Non-Oracle
    Database(s)                                                        Database(s)

  •   Real-time change data capture, routing and delivery across
      heterogeneous systems
  •   Non-invasive , log-based change data capture for minimal impact on
      infrastructure
  •   Transactional integrity and guaranteed data delivery across regions
  •   Bi-directional replication and support for different replication topologies

                                                                                    21
Oracle Complete Data Integration Solution Usage
     Complete, Flexible, Integrated



       Source OLTP
                                                                     BI
        Database                      DR, Query,                Reporting Tool
                                      Reporting
SCM Apps                                                  Real-time               Historic
                                                          Analytics               Analytics
                     Real-Time Feed
Operations                                         ODI/
                     Oracle             ODS        ODP/ODQ
                     GoldenGate
CRM Apps                                           Transform
                                                   & Cleanse
                     Oracle                                               EDW
                     GoldenGate
Financials                              Staging
                     Batch or                                         Oracle Exadata
                     Real-Time Feed                                     or Teradata
ERP Apps
                                                                      or Netezza, etc




                                                                                              22
Customer Case Studies
Customer Example
          Leading online retailer offering a wide variety of high-quality, brand-
          name merchandise at discount prices and manufacturers, distributors
          and other retailers an alternative sales channel.




          Challenges & Objectives                               Solution & Benefits

Need to enable sales, finance, marketing and   Oracle GoldenGate captures real-time change data
merchandising teams with near real-time data   from ecommerce and auction systems. Oracle Data
                                               Integrator is used for highly complex transformations
                                               and data loading to user tables
Required to have business insight on company   Resulted in updated, current Teradata data warehouse
performance meeting target metrics             providing critical business intelligence for decision
                                               making
Need to be able to handle high-volume data     Complete, accurate data to give LOBs a trusted view of
loading and transformation requirements like   business progress, etc.
1.2M+ SKUs, 5M+ daily transactions, 300+
users

                                                                                                        24
Overstock.com

         Supply                               Demand




Manufacturers                                           Consumers

                      350,000 sq. ft.   User
                      Fulfillment       Friendly
                      Warehouse         Web Front End
 Distributors                                           Small
                  •   Information-sensitive business    Businesses

                  •   Demanding Business Community
                  •   Pricing, Forecasting
                  •   Rapid Growth

                                                                    25
Overstock.com
    Innovations in Data Warehousing




Traditional Framework                    Emerging Framework
• Batch extracts/feeds from              • Near real-time feeds from
  operational systems                      operational systems
• Transformations in ETL engine on       • Thin middle tier with E-LT
  the middle tier                        • Transformations on the database
• Bulk load to the data warehouse          platform
• Large nightly batch, user online day   • Small mini-batches throughout the
                                           day




                                                                               26
Overstock.com
Enterprise Solution for Enhanced Intelligence




                                                27
Overstock.com: Innovations in Data Integration
Speed translates to Improved Opportunities


                    • Batch windows nearly eliminated

                    • Low-latency data provides new opportunities
                       • Trigger/event campaigns
                       • Personalization, scoring, ranking
                       • Marketing and merchandising improvements

                    • Improved Customer Service
                       • Now ranked #2 in the nation
                       • Operational improvements in scoring and
                         logistics led to amazing results
                       • Upgraded Oracle 9i Database without business
                         interruption



                                                                        28
Lifetouch Portrait Studios Inc
• Serve the portraiture needs of 2M Guests annually
• 730 Photographic studios across the country

We preserve memories
and help our guest
tell their unique story…




FLASH! Digital Portraits
The Studio at Target
JCPenney Portraits



                                                      29
Better Customer Insight with Oracle Data
  Quality
                              Business Challenges
                               Implement a single, high-quality and consistent view of each
                                customer to be available throughout the organization
                               Streamline the sharing of customer data across all the
                                customer facing applications
                               Improve the accuracy of customer data to provide a better
                                visibility and to elevate the customer relationships.


Oracle Solution                                     Return on Investment
 Implemented Oracle Data Quality for                Improved customer data quality by a
  Data Integrator to cleanse customer                 minimum of 25%
  data.                                              Studio workflow performance
 Combined Oracle solution with                       improved by 10% resulting in higher
  Oracle Database, MySQL and Oracle                   customer satisfaction and retention
  Data Integrator for every data                     Accurate and complete customer data
  movement and the overall                            into data warehouse enabled better
  orchestration of the process                        customer segmentation and targeted
                                                      marketing campaign
                                                     Reduced the time and budget required
                                                      to implement data quality processes.



                                                                                               30
Benefits
• Improved customer service with real time guest and appointment
  data enabling improved Studio efficiencies
   • Studio workflow performance improvement of 10%
   • Higher guest satisfaction and retention

• Accurate and complete guest data in the Data Warehouse
  enabling
   • Improved guest segmentation
   • Improved targeted marketing campaigns

• Cleansed and unique guest profiles shared across primary
  applications resulting in a minimum of 25% improved data quality.

• Expected reduction of technical resource hours in implementing
  custom code, and performing manual data quality implementation
  and audits.

• Time and budget saved with implementing ODI/ODQ solution vs.
  building functionality internally.

                                                                      31
Benefits of Real-Time DW with Oracle
Cut Costs, Reduce Risk, and Revolutionize Business Insight


   Cut Costs and Improve Efficiencies.

   • Move only the changed data from redo logs and reduce source and
     network overhead
   • Shorten implementation times from months to weeks using pre-
     packaged integrations to well-known applications, sources and targets.



   Reduce Risk, Ensure Continuity

   • Eliminate performance impact on source systems
   • Reduce the risk of missed orders, poor customer interactions, missed
     opportunities through improved recoverability, data quality



   Improve Business Insight

   • Enable near real-time decision making with real-time data flows
   • Combine real-time data with historical context for better insights



                                                                              32
Questions

Talk IT_ Oracle_김태완_110831

  • 1.
    <Insert Picture Here> MaximizingReturn for your Data Warehouse
  • 2.
    Agenda • Top BusinessImperatives and Data Requirements to Succeed <Insert Picture Here> • Data Warehouse Basics and Challenges • The Purpose of Data Warehouse • Why Real-Time Data Warehouse for BI? • Real-Time Data Integration Considerations • Traditional Vs Real-time Data Warehouse • Data Quality & Profiling • Oracle Data Integration Solution • Customer Case Studies 2
  • 3.
    Top Business Imperativesand Data Requirements to Succeed Access to Timely, Trusted, and Consistent data Operational & Analytical Business Applications Risk CRM / Direct Improve Management Marketing Mergers & Decisions & Acquisitions Regulatory Compliance Real-Time Data Quality Data Integration Data DataMart / MDM / Migration & BI DWH / BI Consolidation BI IT Projects 3
  • 4.
    Why Real-Time DataWarehousefor BI? 1. Business Driver: Real-Time= Relevant and actionable To compete more effectively information by using better insights in day to day operations and Improved insights for strategic decisions operational decision making 2. Technical Driver Better customer service To move away from batch and cost savings via ETL jobs and eliminate operational efficiencies the impact it has on the IT infrastructure Increased profitability, customer retention, and competitive advantage 4
  • 5.
    Integration Challenges Fragmented Approach Analytics Business Packaged Intelligence Custom Reporting Applications Accessibility Enterprise Performance Data Replication Data Migration Data Warehousing Up-To-Date Data Silos Data Marts Data Hubs Trusted Data Federation Data Access information Batch Scripts Custom SQL InformationJava OLTP & ODS Oracle, PeopleSoft, Files, Excel OLAP Systems Data Warehouse, Data Warehouse, Data Warehouse, Siebel, SAP, XML Data Mart Data Mart Data Mart Custom Apps High Cost of Lack of clean, Multiple standards, Custom Coding consistent data disciplines 5
  • 6.
    Data Warehouse andIt’s Process A centralized repository containing comprehensive detailed and summary data that provides a complete view of customers, suppliers, business processes, and transactions, from a historical perspective with little volatility. Typically loaded on a nightly basis with batch extracts from source transaction processing systems such as CRM, ERP, etc to support reporting and analysis. Sources Target DATA WAREHOUSE ERP/ CRM Integrate DM1 DM2 Data Cleansing Load DM3 DM4 Extract Data RDBMS Enrichment Transform Analytical Reporting Ad-hoc Reporting Dashboards Scorecards 6
  • 7.
    Business Drivers Fora Modern Data Integration Platform & Real-Time DWH Demand for Continuous, Real-Time, Trusted Information Real-Time Enterprise Continuous Availability Real-Time Data for 24/7 Global Operations for Intelligence & Operations • Continuous uptime in event of disaster • Up-to-the second data for operations • No downtime during planned outage • Access to timely information for analysis • Low-impact data capture for integration • Data distribution across regions Trusted Information • Consistent with other systems •High data integrity 7
  • 8.
    Traditional Vs Real-TimeData Warehouse Traditional Data Warehouse Real-Time Data Warehouse Transformation & Quality (ETL / ELT & Data Cleansing) ETL + CDC Real-Time Legacy, Continuous Feeds Packaged Enterprise Apps, Data Legacy, OLTP Warehouse Packaged Enterprise Data Databases Apps, OLTP Warehouse/MDM • Day+ old data • Timely, relevant data are continuous feed from operational systems • Batch data extracts within specified • No batch windows on OLTP “off business hours” • Sub-second latency • A middle-tier server for • No impact on source systems transformations • Read-consistent changed data with referential integrity • Process interruptions impact data • Transformations at capture, delivery or recoverability within the database 8
  • 9.
    Oracle Complete DataIntegration Solution
  • 10.
    Oracle Data Integration:3 Key Products Addressing operational and strategic analysis Oracle Data Quality Oracle Data Integrator Oracle GoldenGate & Profiling • E-LT • Real-Time data • Discover data • Bulk data movement capture and delivery problems • Complex • Low impact and non- • Global data cleansing transformation invasive • Data standardization • Easy to use GUI • Transactional integrity • Fuzzy matching design • Guaranteed delivery • Heterogeneous • Data lineage & impact • Delivers continuous analysis availability • Heterogeneous • Heterogeneous Accessibility Up-to-Date Information Trusted Information 10
  • 11.
    Oracle Data IntegratorEnterprise Edition Optimized E-LT for Improved Performance Legacy Sources E-LT Transformation Any Data vs. E-T-L Warehouse Application Declarative Set-based Sources design Pluggable Knowledge Any Modules Planning System OLTP DB Hot-pluggable Architecture Sources Change Data Capture for Dynamic Updates 11
  • 12.
    Data Warehouse BulkLoading w/E-LT Fastest ELT Solution for your Data Warehouse Solution • ODI for bulk loading Data Warehouse Extract • Run ODI Agent within Data Warehouse JVM • Fastest possible data Load transformations • Heterogeneous and loads any 3rd party data warehouse. Benefits Transform • No extra ETL servers • RDBMS Specific Knowledge Modules • Exploit DW RDBMS Optimizer • Easier to deploy than conventional ETL tools • Faster time to market • Enforce DW Best Practices 12
  • 13.
    Optimized for Exadata FastestE-L-T Processing • Massively parallel high volume hardware to quickly process vast amounts of data OLAP • Exadata runs data intensive processing directly in storage • Most complete analytic capabilities • OLAP, Statistics, Spatial, Data Mining, Real-time transactional ETL, Efficient point queries ELT • Powerful warehouse specific optimizations • Flexible Partitioning, Bitmap Indexing, Join indexing, Materialized Views, Result Cache Data Mining • E-LT runs 20X faster only with Oracle New 13
  • 14.
    ODI is Faster Upto 7TB per hour of real world data loading and complex transformations ODI ELT (on Exadata)  ODI scales with Exadata  ODI runs on Exadata – no ETL hardware required  Common administration, monitoring and management  All the benefits of rapid tools-based ETL development Conventional ETL  As data sets grow additional hardware ($$) needed  ETL parallel optimization and design ($$$) is heavily dependent on resources available to the ETL system  Poor performance – transformations take place outside of database, require staging tables  Lack of light-weight architecture for rapid data loading  ETL engine hardware resources only used for ETL  Hardware not co located, multiple vendors  Different management, monitoring and administration from database and BI infrastructure ($$) 14
  • 15.
    Differentiator: E-LT Architecture High Performance Conventional: Separate ETL Server Conventional ETL Architecture • Proprietary ETL Engine • Poor Performance Extract Transform Load • High Costs for Separate Standalone Server Oracle: No New Servers • Lower Cost: Leverage Compute Resources & Partition Workload efficiently • Efficient: Exploits Database Optimizer • Fast: Exploits Native Bulk Load & Other Database Interfaces Next Generation Architecture • Scalable: Scales as you add Processors to Source or Target “E-LT” Benefits Transform Transform Optimal Performance & Scalability Extract Load Better Hardware Leverage Easier to Manage & Lower Cost 15
  • 16.
    Oracle Data Profilingand Quality Integrated Data Profiling and Quality for Customer Data Oracle Data Profiling, Oracle Data Quality Metadata Profiling of Source & Target Any Source Duplicate Detection, Matching & Merging System Global Address Cleansing Data Control and Visibility Any Data Warehouse Optimized for Customer/Party Data & MDM Oracle Data Integrator Enterprise Edition Any Planning System 16
  • 17.
    Oracle Data Quality EnsureData Quality as Part of the Integration Process Best-in-class data quality and profiling for integration processes ODI EE Better Data Visibility Tighter Data Control Greater Data Accuracy Visual Data Quality Oracle Data Profiling Oracle Data Quality Tools Metadata Profiling Duplicate Detection, of Source & Target Matching & Merging 17
  • 18.
    Sample Data QualityIssues COMPLETENESS Completeness What data is missing or CONFORMITY unusable? CONSISTENCY Consistency What data values give conflicting DUPLICATION information? Accuracy Conformity ACCURACY What data is stored What data is incorrect or out of in a non-standard date? format? Duplication What data records or attributes are repeated? 18
  • 19.
    Oracle GoldenGate Enterprise-wideSolution for Real Time Data Needs Zero Downtime New DB/ Migration and OS/HW/App Upgrades Active-Active High Fully Active • Reduce Costs Availability Distributed Database Log Based, Real- • Lower Risks Time Change Data Capture Query Offloading Reporting • Achieve Oracle Database GoldenGate Operational ETL Excellence ODS EDW ETL Heterogeneous Real-time BI EDW Source Systems Data Distribution Global Data Centers SOA/EDA 19
  • 20.
    Data Movement plusReal-Time Oracle GoldenGate provides low-impact capture, routing, transformation, and delivery of transactional data across heterogeneous environments in real time Key Differentiators: Performance Non-intrusive, low-impact, sub-second latency Flexible and Extensible Open, modular architecture - Supports heterogeneous sources and targets Reliable Maintains transactional integrity - Resilient against interruptions and failures 20
  • 21.
    Oracle GoldenGate Architecture Designed for Speed, Flexibility and Reliability Trail Trail Capture Delivery LAN/WAN Internet TCP/IP Source Target Oracle & Non-Oracle Bi-directional Oracle & Non-Oracle Database(s) Database(s) • Real-time change data capture, routing and delivery across heterogeneous systems • Non-invasive , log-based change data capture for minimal impact on infrastructure • Transactional integrity and guaranteed data delivery across regions • Bi-directional replication and support for different replication topologies 21
  • 22.
    Oracle Complete DataIntegration Solution Usage Complete, Flexible, Integrated Source OLTP BI Database DR, Query, Reporting Tool Reporting SCM Apps Real-time Historic Analytics Analytics Real-Time Feed Operations ODI/ Oracle ODS ODP/ODQ GoldenGate CRM Apps Transform & Cleanse Oracle EDW GoldenGate Financials Staging Batch or Oracle Exadata Real-Time Feed or Teradata ERP Apps or Netezza, etc 22
  • 23.
  • 24.
    Customer Example Leading online retailer offering a wide variety of high-quality, brand- name merchandise at discount prices and manufacturers, distributors and other retailers an alternative sales channel. Challenges & Objectives Solution & Benefits Need to enable sales, finance, marketing and Oracle GoldenGate captures real-time change data merchandising teams with near real-time data from ecommerce and auction systems. Oracle Data Integrator is used for highly complex transformations and data loading to user tables Required to have business insight on company Resulted in updated, current Teradata data warehouse performance meeting target metrics providing critical business intelligence for decision making Need to be able to handle high-volume data Complete, accurate data to give LOBs a trusted view of loading and transformation requirements like business progress, etc. 1.2M+ SKUs, 5M+ daily transactions, 300+ users 24
  • 25.
    Overstock.com Supply Demand Manufacturers Consumers 350,000 sq. ft. User Fulfillment Friendly Warehouse Web Front End Distributors Small • Information-sensitive business Businesses • Demanding Business Community • Pricing, Forecasting • Rapid Growth 25
  • 26.
    Overstock.com Innovations in Data Warehousing Traditional Framework Emerging Framework • Batch extracts/feeds from • Near real-time feeds from operational systems operational systems • Transformations in ETL engine on • Thin middle tier with E-LT the middle tier • Transformations on the database • Bulk load to the data warehouse platform • Large nightly batch, user online day • Small mini-batches throughout the day 26
  • 27.
    Overstock.com Enterprise Solution forEnhanced Intelligence 27
  • 28.
    Overstock.com: Innovations inData Integration Speed translates to Improved Opportunities • Batch windows nearly eliminated • Low-latency data provides new opportunities • Trigger/event campaigns • Personalization, scoring, ranking • Marketing and merchandising improvements • Improved Customer Service • Now ranked #2 in the nation • Operational improvements in scoring and logistics led to amazing results • Upgraded Oracle 9i Database without business interruption 28
  • 29.
    Lifetouch Portrait StudiosInc • Serve the portraiture needs of 2M Guests annually • 730 Photographic studios across the country We preserve memories and help our guest tell their unique story… FLASH! Digital Portraits The Studio at Target JCPenney Portraits 29
  • 30.
    Better Customer Insightwith Oracle Data Quality Business Challenges  Implement a single, high-quality and consistent view of each customer to be available throughout the organization  Streamline the sharing of customer data across all the customer facing applications  Improve the accuracy of customer data to provide a better visibility and to elevate the customer relationships. Oracle Solution Return on Investment  Implemented Oracle Data Quality for  Improved customer data quality by a Data Integrator to cleanse customer minimum of 25% data.  Studio workflow performance  Combined Oracle solution with improved by 10% resulting in higher Oracle Database, MySQL and Oracle customer satisfaction and retention Data Integrator for every data  Accurate and complete customer data movement and the overall into data warehouse enabled better orchestration of the process customer segmentation and targeted marketing campaign  Reduced the time and budget required to implement data quality processes. 30
  • 31.
    Benefits • Improved customerservice with real time guest and appointment data enabling improved Studio efficiencies • Studio workflow performance improvement of 10% • Higher guest satisfaction and retention • Accurate and complete guest data in the Data Warehouse enabling • Improved guest segmentation • Improved targeted marketing campaigns • Cleansed and unique guest profiles shared across primary applications resulting in a minimum of 25% improved data quality. • Expected reduction of technical resource hours in implementing custom code, and performing manual data quality implementation and audits. • Time and budget saved with implementing ODI/ODQ solution vs. building functionality internally. 31
  • 32.
    Benefits of Real-TimeDW with Oracle Cut Costs, Reduce Risk, and Revolutionize Business Insight Cut Costs and Improve Efficiencies. • Move only the changed data from redo logs and reduce source and network overhead • Shorten implementation times from months to weeks using pre- packaged integrations to well-known applications, sources and targets. Reduce Risk, Ensure Continuity • Eliminate performance impact on source systems • Reduce the risk of missed orders, poor customer interactions, missed opportunities through improved recoverability, data quality Improve Business Insight • Enable near real-time decision making with real-time data flows • Combine real-time data with historical context for better insights 32
  • 33.