1. Oracle BI Applications - Architecture

2. The following is intended to outline our general product direction
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

3. Oracle BI Applications Analytische Anwendungen auf Basis von BI Suite EE
Ad-hoc Auswertungen
Proaktive Benach- richtigungen
MS Office
Plug-in
Reporting &
Publishing
Interaktive
Dashboards
Mobile
Auswertungen
Web Services
Oracle BI Anwendungen
Vertrieb
Service & Contact Center
Marketing
Auftrags Management & Fulfillment
Liefer- kette
Finanz
Personal
Gemeinsames unternehmensübergreifendes Datenmodell
Auf Basis von BI EE Suite
Vordefinierte Hierarchien, Pfade, Sicherheit, Dashboards, Berichte
It is a complete, end-to-end BI environment covering the BI platform and pre-packaged analytic applications.
The platform includes a server and end user tools such as dashboards, query and analysis, enterprise reporting, disconnected access to the data -- all supported by a unified, model-centric server architecture.
On top of this platform, we have a set of analytic applications consuming the operational data sources and delivering greater insight to larger user communities across the organization via dashboards, query and analysis, alerts, briefing books, and disconnected mode - the same tools we mentioned under the BI platform.
Basierend auf Industriestandards
IVR, ACD, CTI
Hyperion
MS Excel
Andere Quellen
Vordefiniertes
ETL
Adapter

4. Oracle BI Applications Architecture
Administration
Oracle BI Presentation Services
Dashboards by Role
Reports, Analysis / Analytic Workflows
Metadata
Role Based Dashboards
Analytic Workflow
Guided Navigation
Security / Visibility
Alerts & Proactive Delivery
Metrics / KPIs
Logical to Physical Abstraction Layer
Calculations and Metrics Definition
Visibility & Personalization
Dynamic SQL Generation
Logical Model / Subject Areas
Oracle BI Server
Physical Map
Direct Access to Source Data
Data Warehouse /
Data Model
Abstracted Data Model
Conformed Dimensions
Heterogeneous Database support
Database specific indexing
ETL
Load Process
Staging Area
Extraction Process
DAC
Highly Parallel
Multistage and Customizable
Deployment Modularity
Oracle
SAP R/3
Siebel
PSFT
EDW
Federated Data Sources
Other

5. ETL Overview Load Extract Federated Data Sources Administration
Oracle BI Presentation Services
Dashboards by Role
Reports, Analysis / Analytic Workflows
Metadata
Load
Extract
SAP
PeopleSoft
Source Independent Layer
Staging Tables
Other
Siebel
OLTP
Oracle
Power
Connect
SQL
App Layer
ABAP
Oracle Data
Warehouse
Metrics / KPIs
Logical Model / Subject Areas
Oracle BI Server
Physical Map
Direct Access to Source Data
Data Warehouse /
Data Model
ETL
Load Process
Staging Area
Extraction Process
DAC
DAC
Key ETL components and features we support
Batch ETL
Recently Low Latency ETL ie to refresh the warehouse with a very low latency
The ETL process is divided into 2 major sub-processes
Extraction
Load
The architecture seeks to keep all source specific logic in the extract layer
Thus supporting a new version or a new adapter requires writing only extract layer
Over the years we have done significant performance tuning on various areas for all platforms in terms of use of bulk loaders/database specific indexing etc
Lastly DAC is a critical tool for us used for application installation, administration, ETL scheduling and monitoring
Oracle
SAP R/3
Siebel
PSFT
EDW
Federated Data Sources
Other

6. Data Extraction and Load Process
SAP
PeopleSoft
Source Independent Layer
Staging Tables
Other
Siebel
OLTP
Oracle
Power
Connect
SQL
App Layer
ABAP
Oracle Data
Warehouse
Extraction Modes
Direct Database Access
Siebel
Oracle
PowerConnects technology
SAP
PeopleSoft
Universal Business Adapters
Used for sources with no pre-packaged business adapter
Transforms and loads data from universal sources through a flat file interface
Supply flat file(s) or tables meeting a defined standard format
Reduces implementation and maintenance significantly compared to building full ETL solution from scratch
Lets talk about the various extraction modes …
Universal
Used for legacy and non supported sources
Expect data in a standard flat file or database table format
Once the data is extracted, the load process performs all subsequent processing

7. Data Warehouse Application Console (DAC)
DAC is a metadata driven administration and deployment tool for ETL and data warehouse objects
Used by warehouse developers and ETL Administrator
Application Configuration
Manages metadata-driven task dependencies and relationships
Allows creating custom ETL execution plans
Allows for dry-run development and testing
Execution
Enables parallel loading for high performance ETL
Facilitates in index management and database statistics collection
Automates change capture for Siebel OLTP
Assists in capturing deleted records
Fine grain restartability
Monitoring
Enables remote admin and monitoring
Provides runtime metadata validation checks
Provides in-context documentation
DAC
Background – There are a variety of things to be deployed and managed in a data warehouse
DW objects (tables/indices)
ETL Code
Seed data
Variety of configurations for ETL etc
This is our tool to administer/install/maintain and monitor ETL runs
Also used by ETL administrators in production to monitor and restart jobs
Significant TCO and performance improvements since DAC was released. Several customers have improved their ETL run timings several times

8. Physical Data Model Overview
Administration
Oracle BI Presentation Services
Dashboards by Role
Reports, Analysis / Analytic Workflows
Metadata
Modular enterprise-wide data warehouse data model with conformed dimensions
Sales, Service, Marketing, Distribution, Finance, Workforce, Operations and Procurement
Integrate data from multiple data sources
Code Standardization
Real-time ready
Transaction data stored in most granular fashion
Tracks historical changes
Supports multi-currency, multi-languages
Implemented and optimized for Oracle, SQL Server, IBM UDB/390, Teradata
Metrics / KPIs
Logical Model / Subject Areas
Oracle BI Server
Physical Map
Direct Access to Source Data
Data Warehouse /
Data Model
ETL
Load Process
Staging Area
Extraction Process
DAC
The data model is a dimensional model
Can load data from multiple sources
One of the key methods to conform data from various sources is “code standardization” ie define and convert source specific codes into a normalized warehouse code. Eg Invoice Types etc
Supports all 4 major databases and has been tested and optimized for all of them
Oracle
SAP R/3
Siebel
PSFT
EDW
Federated Data Sources
Other

9. Selected Key Entities of Business Analytics Warehouse
Sales
Opportunities
Quotes
Pipeline
Order Management
Sales Order Lines
Sales Schedule Lines
Bookings
Pick Lines
Billings
Backlogs
Marketing
Campaigns
Responses
Marketing Costs
Supply Chain
Purchase Order Lines
Purchase Requisition Lines
Purchase Order Receipts
Inventory Balance
Inventory Transactions
Finance
Receivables
Payables
General Ledger
COGS
Call Center
ACD Events
Rep Activities
Contact-Rep Snapshot
Targets and Benchmark
IVR Navigation History
Service
Service Requests
Activities
Agreements
Workforce
Compensation
Employee Profile
Employee Events
Pharma
Prescriptions
Syndicated Market Data
Financials
Financial Assets
Insurance Claims
Public Sector
Benefits
Cases
Incidents
Leads
Conformed Dimensions
Customer
Products
Suppliers
Internal Organizations
Customer Locations
Customer Contacts
GL Accounts
Employee
Sales Reps
Service Reps
Partners
Campaign
Offers
Cost Centers
Profit Centers
This slide provides an overview of the width of content in the warehouse, going all the way from Marketing/Sales to Backoffice and HR analytics
There is a single logical model on the warehouse, enabling cross process metrics and calculations
Examples of processes
Sales  Lead to order; Order to cash
Supply Chain  Requisition to Check; Dock to Stock
Service Open to close a trouble ticket
Call Center  Origination to termination of a call, whether handled by a person, a machine, or both
Financials  used to keep score
Let's discuss these processes in more detail. As we go through them, you'll see all the way that Analytics can add value.
Modular DW Data Warehouse Data Model includes:
~350 Fact Tables
~550 Dimension Tables
~5,200 prebuilt Metrics
(2,500+ are derived metrics)
~15,000 Data Elements

10. Server Repository Overview
Administration
Oracle BI Presentation Services
Dashboards by Role
Reports, Analysis / Analytic Workflows
Metadata
Multi-layered Abstraction
Separation of physical, logical and presentation layers
Logical modeling builds upon complex physical data structures
Logical model independent of physical data sources, i.e. same logical model can be remapped quickly to another data source
Metrics / KPIs
Multi-pass complex calculated metrics (across multiple fact tables)
One Logical Fact can span several table sources including aggregates and real-time partitions
Level based metrics
Aggregate navigation
Federation of queries
Security and visibility
Prebuilt hierarchy drills and cross dimensional drills
Metrics / KPIs
Logical Model / Subject Areas
Physical Map
Oracle BI Server
Direct Access to Source Data
Data Warehouse /
Data Model
ETL
Load Process
Staging Area
Extraction Process
DAC
Move the focus to Oracle BI Applications Repository Metadata
To re-emphasize, Analytics server is model centric and report centric. This is the place where the model is built and not reports/dashboards
The model consists of
Logical Model
Has all dimensions/facts/metrics
Physical Model
Logical to Physical Mappings
Aggregates/Federation (Revenue for employee)
Security and Visibility
Dimensions and drills etc
Oracle
SAP R/3
Siebel
PSFT
EDW
Federated Data Sources
Other

11. Metrics and Calculations
The applications provide several complex metrics defined logically with an expression builder
Share base (e.g. % share of one product sales over all products sales)
Indexes (e.g. this division’s performance as a ratio of all divisions)
Cross subject area metrics (across Sales and Workforce, e.g. Revenue per employee)
Variances (e.g. Budget vs Actual)
Time series metrics
MTD/YTD/Running balances/MAVG (e.g. Revenue Chg % YTD)
Period Ago Metrics (e.g. Revenue YAGO)
Snapshot at any point of time support (e.g. # Open Service Requests)
The applications provide a variety of rich metrics.
Raw numbers do not provide enough value unless a context is created around them. Context could be a comparison, % growth, time series or index
Emphasize that all of these are built logically.
Can provide DSO any point of time
Use aggregates for performance enhancements
All of these can be done logically
without adding data model/ ETL complexity

12. Data and Content Security
How do you get in?
Authentication
Internal
External, e.g. SSO, LDAP/DB authentication, NT Login
What parts of the application can you see?
Dashboard, page, subject area and column visibility
What data can you see?
Row and Organizational level Visibility
E.g. My Team’s Opportunities / Accounts
Dimension and Fact based security
Both fact queries and dimensional browsing queries are secured, e.g. Consumer Good Product Management seeing their product revenues and their product opportunities
Column security
Certain columns may not be visible to certain users
A – Variety of authentication modes are supported
B – User access to various elements of apps can be controlled
C – Row level visibility etc
Easy to set up by application administrator

13. Localization / Globalization
Dynamic Language Conversion (localized to 16 languages)
Chinese (Simplified), Chinese (Traditional), Czech, Danish, Dutch, English (US), Finnish, French, German, Italian, Japanese, Korean, Portuguese (European), Portuguese (Brazilian), Spanish, Swedish
Codepage / Unicode support
Dynamic Time Zone translations
All timestamps are stored in warehouse stored as UTC
Custom labeling and naming support / Flex Field Naming
Column Names can be dynamically named
We support 16 languages for the applications
Another key feature is flex field naming and custom naming
E.g. product hierarchy

14. Oracle BI Presentation Services Reports, Analysis / Analytic Workflows
Web Catalog Overview
Administration
Oracle BI Presentation Services
Dashboards by Role
Reports, Analysis / Analytic Workflows
Metadata
Role based dashboards
Covering more than 100 roles
Navigation
Most reports have at least one level of navigation embedded
Drill to details from many interactive elements, e.g. chart segments
Guided Navigation
Conditional navigational links
Analytic Workflows
Action Links
Direct navigation from record to transactional while maintaining context
Alerts
Scheduled and Conditional iBots
Highlighting
Conditional highlighting that provides context on metrics (is it good or bad?)
Metrics / KPIs
Logical Model / Subject Areas
Oracle BI Server
Physical Map
Direct Access to Source Data
Data Warehouse /
Data Model
ETL
Load Process
Staging Area
Extraction Process
DAC
The key end user delivery mode is dashboards besides the ad-hoc tool called Answers which is used by more savvy users
The dashboards are very interactive and alive (not static html) pages. There are various ways a user interacts to a dashboard
Navigation, ie jump to another report or view with the context
Guided Navigation – conditional navigation which appears on fulfillment of some condition
Action Links : to transactional system
Alerts : Delivered via scheduler ie scheduled reports
Highlighting etc
Oracle
SAP R/3
Siebel
PSFT
EDW
Federated Data Sources
Other

15. More than just Dashboards & Reports
Guided Navigation
Enables users to quickly navigate a standard path of analytical discovery specific to their function and role
Enhances usability and lowers learning curve for new users
Conditional Navigation
Appears only when conditions are met and alerts users to potential out of ordinary conditions that require attention
Guides users to next logical step of analytical discovery

16. More than just Dashboards & Reports
Action Links
Direct navigation from record to transactional while maintaining context
Take Action immediately without navigating to a different screen

17. Deployment Options Standalone Dashboards
Portal integration via JSR-168/WSRP

18. Deployment Options
Embedded in transactional system, within a dashboard view

19. Deployment Options Embedded in transactional system
Contextually within a transactional view

20. Deployment Options Embedded in transactional system
Analytics results within a transactional applet
Profitability is calculated from Total Revenue and Costs (from Financial system)
Cost To Serve is calculated from costs gathered from CTI systems, Service Systems, etc.