1. Oracle for Data Warehousing

2. Packaged Applications Business Intelligence Performance Management
Today’s Reality
Analytics
Packaged Applications
Business Intelligence
Custom Reporting
Performance Management
Data Replication
Data Migration
Data Warehousing
Data Federation
Data Marts
Data Silos
Data Hubs
Data Access
SQL
Batch Scripts
Custom
Java
Fragmented data silos, data-marts, and data-centric applications are the norm
Inconsistent data, risk from data exceptions; untrustworthy data
Inaccessible information, lack of re-use
Lack of visibility to how information assets are used and leveraged
Poor business insight, incomplete information for decision making
Data Warehouse
Data Mart
SAP, Oracle
PeopleSoft, Siebel,
Custom Apps
Files
Excel
XML
OLTP & ODS
Systems
OLAP 2 2 2

3. What’s the Impact on Your Business?
Fragmented data Silos
Untrustworthy Data
Inaccessible Information
Limited Scalability
Difficult to Manage
Higher Costs
Increased Risk
Poor Decisions
Fragmented data Silos
Higher Costs
Increased Risk
Poor Decision Making
Fragmented data silos, data-marts, and data-centric applications are the norm
Inconsistent data, risk from data exceptions; untrustworthy data
Inaccessible information, lack of re-use
Lack of visibility to how information assets are used and leveraged
Poor business insight, incomplete information for decision making 3 3 3

4. Moving toward a Clean Architecture
APPLICATIONS
ANALYTICS / APPS SERVERS
ORCHESTRATION
MASTER DATA
BPEL PM
CRM APPS
SCM APPS
WEBSITES
FINANCIALS
DISTRIBUTION
CUSTOM APPS
OPERATIONS
ERP APPS
MDM APPLICATIONS
Master
Data
EPM BI
...
BUSINESS INTELLIGENCE
CLUSTERS
ETL
Master Data
Data Warehouse
ETL
ESB

5. Data Warehouse Reference Architecture

6. Oracle’s Integrated Stack
Customer Service
Ad Hoc Analysis
Interactive Dashboards
Performance Management
Reporting & Publishing
Proactive Detection
Data Integration & Management
Data Warehousing
Business Intelligence Foundation
PM and BI Applications
Data Mining
Storage
Compression
OLAP
Predictive
PM Applications
BI Applications
Partitioning
Modeling
Data Federation
Data Quality
ETL/ELT
Data Services
Database and Middle Tier Servers

7. Oracle: #1 in Data Warehousing
Numbers Show Oracle #1 Database (Again).
Oracle Confidential – Do Not Distribute
Source: IDC, August 2010 – “Worldwide Data Warehouse Platform Software 2009 Vendor Shares”

8. Oracle Data Warehouse Customers
Retail
Communications
Financial Services
Manufacturing
Manufacturing
CPG/Healthcare
Transportn/Energy
Leading companies across virtually every industry have chosen Siebel Analytics. Some of the most sophisticated users of analytics technologies—companies like Procter & Gamble and UPS, for example—have standardized on Siebel as their analytics platform.
The benefits these companies are achieving with Siebel Analytics are very significant.
Honeywell, for example, has improved customer satisfaction by 30% and increased deal close rate. They have 1,000+ users at all levels of the organization.
General Motors is using Siebel Analytics to analyze dealer sales, service, and parts data from 21 disparate data sources, providing 1600 users in the field access to complete business insight they need
At Cisco, Siebel Analytics provides 500 top execs with near real-time global picture of business performance and prospects
At Royal Bank of Canada -- Integrates over 14 terabytes of data from checking, credit card, and mortgage systems, delivering multiple analytic applications to thousands of users enterprise wide; Millions saved through improved collections and reduced defaults

9. Oracle Exadata Database Machine Extreme Performance
Fastest growing new product in Oracle’s history
Server & Storage Integrated Hardware & Software Platform
Data Warehousing
OLTP
Consolidation
“After carefully testing several data warehouse platforms, we chose the Oracle Database Machine. Oracle Exadata was able to speed up one of our critical processes from days to minutes.”
Brian Camp
SVP, Infrastructure Services Knowledge Base Marketing

10. Oracle for Data Warehousing
Optimized for strategic warehousing
25 GB/sec IO bandwidth, with up to 50 GB/sec with Flash
Optimized for real-world data loading
Read consistency with the ability to load at 5TB/hr
Optimized for operational warehousing
Advanced indexing capabilities running at 1M IOPS
Optimized for advanced analytics
Integrated OLAP, data mining, spatial and statistics
Optimized for large data sets
10x user data compression

11. Exadata Hardware Architecture
Scaleable Grid of industry standard servers for Compute and Storage
Eliminates long-standing tradeoff between Scalability, Availability, Cost
Database Grid
Intelligent Storage Grid
8 Dual-processor x64 database servers OR
2 Eight-processor x64 database servers
14 High-performance low-cost storage servers
100 TB High Speed disk, or 336 TB High Capacity disk
5.3 TB PCI Flash
Data mirrored across storage servers
InfiniBand Network
Redundant 40Gb/s switches
Unified server & storage network

12. Complete Family Of Database Machines For OLTP, Data Warehousing & Consolidated Workloads
Oracle Exadata X2-2
Oracle Exadata X2-8
Quarter, Half, Full and Multi-Racks
Full and Multi-Racks 12

13. Exadata is Smart Storage
Compute Intensive Processing
Database Server
Compute and memory intensive data processing executes in database servers
Fully-parallelized joins and aggregations
Bandwidth Intensive Searches
Exadata Storage Server
IO-bandwidth intensive database operations executes in storage servers
Exadata Smart Scans and Exadata Storage Indexes filter out data that is not relevant to a query
Database servers and Exadata storage work in conjunction to execute SQL
Exadata cell is smart storage, not a complete database node

14. Exadata Database Processing in Storage
Exadata storage servers implement data intensive processing in storage
Row filtering based on “where” predicate
Column filtering
Join filtering
Incremental backup filtering
Scans on Hybrid Columnar Compressed data
Scans on encrypted data
Data Mining model scoring
10x reduction in data sent to DB servers is common
No application changes needed
Processing is automatic and transparent
Even if cell or disk fails during a query

15. Exadata Flash Extreme Performance
Oracle Database Machine has 5 TB of flash storage
4 high-performance flash cards in every Exadata Storage Server
Smart Flash Cache caches hot data
Not just simple LRU
Knows when to avoid caching to avoid flushing cache
Allows optimization by application table
Oracle is the First Flash Optimized Database 15

16. Oracle Database Machine: Optimized for large scans
10 TB of user data
Requires 10 TB of IO
1 TB
with compression
100 GB
with partition pruning
Subsecond
On Database Machine
20 GB
with Storage Indexes
5 GB
with Smart Scans
2000X less data needs to be processed

17. What does Extreme Performance mean for your business?
Massive data volumes
More granular data
Daily data instead of weekly
Store data instead of account
More history
5 years instead of 1 year
New data sources
Consumer-level data
Entirely new analytics
Queries that were never possible now run in minutes
Near-real-time data loading

18. Oracle Database Machine
Optimized for strategic warehousing
25 GB/sec IO bandwidth, with up to 50 GB/sec with Flash
Optimized for real-world data loading
Read consistency with the ability to load at 5TB/hr
Optimized for operational warehousing
Advanced indexing capabilities running at 1M IOPS
Optimized for advanced analytics
Integrated OLAP, data mining, spatial and statistics
Optimized for large data sets
10x user data compression

19. Fast data loading Access Transform Load
Performant data loading and transformation with in-database ETL
Direct flat file access with external tables
Transformation inside the database with SQL and PL/SQL
Bulk and trickle load
Up to 5 TB/hr of raw data loading on a Database Machine
Access
Transform
Load

20. Transform Data Where Data Resides In-database ETL technology
Extract
Load
Transform
Insert
Data Pump
Transportable Tablespaces
Partition Exchange Loading
Change Data Capture
Distributed Queries
SQL*Loader
External Tables
Table Functions
Multi-Table Insert
MERGE
DML error logging

21. DBFS - Scalable Shared File System
Database Machine comes with DBFS shared Linux file system
Shared storage for ETL staging, scripts, reports and other application files
Files stored as SecureFile LOBs in database tables stored in Exadata
Protected like any DB data – mirroring, DataGuard, Flashback, etc.
5 to 7 GB/sec file system I/O throughput
Load into database using External Tables
Using DBFS, it is possible to implement a shared file system in the Oracle Database Machine. An example use of such a shared file system, would be an ETL Staging Area. In this case, data is copied onto the DBFS in the Exadata Storage Servers using traditional OS utilities (like ftp, scp, rcp) and then ETL load tool can load the data from the DBFS into the database tables using the eternal tables interface.
ETL Files in DBFS
ETL
More File Throughput than High-End NAS Filer 21

22. Real Time Data Integration with Oracle GoldenGate
Real time extracts from
transactional systems
Non-invasive on sources
Continuous streaming load
into ODS Schema of target
Latency in seconds
Source 1
EMP
DEPT
On-Disk Logs
Oracle
GoldenGate
Source 2
EMP
DEPT
Oracle
GoldenGate
On-Disk Logs

23. Oracle is uniquely capable of concurrent query and updates
report
Concurrent small data loads and queries
Looks like... OLTP
Oracle's read consistency
Readers never block writers
Writers never block readers
Queries are always consistent and auditable
No deadlocks
Introduced in Oracle V4 (1982)
Teradata: lock rows for reads and writes to obtain consistency
Budget table
update
Rollback
Segment
Before
Image
update
accurate
report

24. Oracle Database Machine
Optimized for strategic warehousing
25 GB/sec IO bandwidth, with up to 50 GB/sec with Flash
Optimized for real-world data loading
Read consistency with the ability to load at 5TB/hr
Optimized for operational warehousing
Advanced indexing capabilities running at 1M IOPS
Optimized for advanced analytics
Integrated OLAP, data mining, spatial and statistics
Optimized for large data sets
10x user data compression

25. Data Warehouse Reference Architecture
Base data warehouse schema
Atomic-level data, 3nf design
Supports general end-user queries
Data feeds to all dependent systems
Application-specific performance structures
Summary data / materialized views
Dimensional view of data
Supports specific end-users, tools, and applications

26. Data Warehouse Reference Architecture
IO-bandwidth intensive workloads
Random-IO intensive workloads

27. Oracle delivers complete capabilities for tactical warehouse queries
Fast lookups
B-Tree indexes
Dimensional queries
Star query optimizations
Bitmap indexes
Bitmap join indexes
Aggregate management
Materialized Views
Cube-organized materialized views

28. Workload Management for DW Setting Up a Workload Management System
Define Workloads
Filter Exceptions
Manage Resources
Monitor Workloads
Adjust Plans
Execute Workloads
Monitor Workloads
Adjust Workload Plans
IORM
RAC
OEM
DBRM
Define Workload Plans
The RAC piece includes things like:
Services
Server Pools (Grid Infrastructure) to provide elasticity (add servers to pool to increase memory)
Instance Caging (consolidation)
© 2010 Oracle Corporation

29. Workload Management Request Queue Execute Assign Ad-hoc Workload
Each request:
Executes on a RAC Service
Which limits the physical resources
Allows scalability across racks
Assign
Each request assigned to a consumer group:
OS or DB Username
Application or Module
Action within Module
Administrative function
Ad-hoc Workload
Each consumer group has:
Resource Allocation (example: 10% of CPU/IO resources)
Directives (example: 20 active sessions)
Thresholds (example: no jobs longer than 2 min)
Reject
Downgrade
© 2010 Oracle Corporation

30. Workload Management Request Real-Time ETL Batch ETL Analytic Reports
Assign
Execute
Execute
OLTP Requests
Ad-hoc Workload
Queue
Downgrade
Reject
© 2010 Oracle Corporation

31. Workload Management Request Real-Time ETL Queue R-T 10% Batch ETL
Analytic
Reports
Analytic Reports 50%
Queue
Assign
OLTP Requests
OLTP 5%
Reject
Downgrade
Queue
Ad-hoc 25%
Ad-hoc Workload
Queue
© 2010 Oracle Corporation

32. Oracle Database Machine
Optimized for strategic warehousing
25 GB/sec IO bandwidth, with up to 50 GB/sec with Flash
Optimized for real-world data loading
Read consistency with the ability to load at 5TB/hr
Optimized for operational warehousing
Advanced indexing capabilities running at 1M IOPS
Optimized for advanced analytics
Integrated OLAP, data mining, spatial and statistics
Optimized for large data sets
10x user data compression

33. In-database Analytics Bring Algorithms to the Data, Not Data to the Algorithms
Analytic computations done in the database
Dimensional analysis
Statistical analysis
Data Mining
Scalability
Security
Backup & Recovery
Simplicity
OLAP
Statistics
Data Mining

34. Deeper insights from Oracle Data Warehouses
Oracle Spatial: GIS data available for analysis and displayed via MapViewer

35. Deeper insights from Oracle Data Warehouses
Oracle OLAP: Hierarchically aware rankings, shares, alerts and time series calculations are easily defined in the cube and queried by OBIEE using simple and efficient SQL

36. Deeper insights from Oracle Data Warehouses
Hierarchically aware rankings, shares, alerts and time series calculations are easily defined in the cube and queried by OBIEE and other tools using simple and efficient SQL
Oracle Data Mining: Predictions & probabilities are calculated within database and available for reporting using OBIEE

37. Deeper insights from Oracle Data Warehouses
OLAP
Data Mining
Spatial 
In-Database Analytics
Deeper insights for business users
Pervasive benefits across stack
Simple and seamless embedded analytics
Extreme performance and scalability

38. Oracle Database Machine
Optimized for strategic warehousing
25 GB/sec IO bandwidth, with up to 50 GB/sec with Flash
Optimized for real-world data loading
Read consistency with the ability to load at 5TB/hr
Optimized for operational warehousing
Advanced indexing capabilities running at 1M IOPS
Optimized for advanced analytics
Integrated OLAP, data mining, spatial and statistics
Optimized for large data sets
10x user data compression

39. Exadata Hybrid Columnar Compression Highest Capacity, Lowest Cost
Data is organized and compressed by column
Dramatically better compression
Speed Optimized Query Mode for Data Warehousing
10X compression typical
Runs faster because of Exadata offload!
Space Optimized Archival Mode for infrequently accessed data
15X to 50X compression typical
Query
Faster and Simpler
Backup, DR, Caching, Reorg, Clone
Benefits Multiply
© 2010 Oracle Corporation

40. More Data Capacity Systems with Equal User Data
Exadata V2 10x Compression
Systems with Equal User Data
All with Largest Disks, Best Compression
Netezza TwinFin 2x to 4x Compression
EMC VMAX 3x Oracle Compression
Exadata has more disk drives per rack, larger disk drives (2TB) and much better compression. This means that Exadata can hold much more User Data than other systems, and costs much less per user Terabyte.
Exadata User Data per SATA rack with 10x compression is 500TB.
Teradata has fallen very far behind in compression technology which makes them much more costly for large data environments.
Teradata 2580 holds 45 TB per cabinet using max sized 1TB drive and 1.3x compression (taken from Teradata specifications).
A single Exadata rack matches the user data capacity of the largest size Teradata (12s cabinet holding 517 TB user data).
The flagship Teradata 5600 is hold even less data per rack than the There is approximately a 20:1 Ratio of user data per rack comparing Exadata to Teradata 5600.
Netezza Twinfin 32 TB Uncompressed per rack, 128 TB Compressed (assuming their maximum 4x compression).
Teradata x Compression

41. Summary

42. Enterprise Availability
Active Data Guard
RAC
ASM
Secure Backup
WAN
Flashback
Online Redefinition
GoldenGate Replication
Exadata has fully redundant hardware. Redundant servers, redundant storage servers, redundant network. So any component can fail and the system as a whole will keep running.
Our measurements to date show that the hardware failure rate is dominated by disk failures.
The Oracle database software tolerates failures by continuing to run when various hardware components fail. For example Oracle RAC continues to run after server failures. ASM mirrors data across storage servers so that the failure of a storage server does not cause an outage of the system as a whole.
Oracle has unique capabilities for rolling back erroneous changes called flashback. Oracle has unique capabilities for making changes to databases online called online redefinition.
All truly highly available systems should have a remote replica.
Oracle has the industry’s leading technologies for creating and maintaining remote replica databases. Golden gate provides a powerful symmetric replication capability. Active Data Guard provides an extremely high performance and simple way to create a readable remote replica database.
Redundant Hardware
Servers, Storage, Network
Database Level HA
Tolerate failures and changes
Real-Time Active Replica
© 2010 Oracle Corporation 42

43. First Secure Database Machine
Moves decryption from software to hardware
Over 5x faster
Near zero overhead for fully encrypted database
Queries decrypt data at hundreds of Gigabytes/second
© 2010 Oracle Corporation 43

44. Standardized and Simple to Deploy
All Database Machines are the same
Delivered Tested and Ready-to-Run
Highly Optimized
Highly Supportable
No unique configuration issues
Identical to config used by Oracle Engineering
Runs existing OLTP and DW applications
Full 30 years of Oracle DB capabilities
No Exadata certification required
Leverages Oracle ecosystem
Skills, knowledge base, people, partners
Ready- to-Run
Eliminates the complexity of deploying a high performance database system.
Database machines are tested in the factory and delivered ready to run. Because all database machines are the same, their characteristics and operations are well known and understood by Oracle field engineers and support. Each customer will not need to diagnose and resolve unique issues that only occur on their configuration. Performance tuning, and stress testing performed at Oracle is done on the exact same configuration that the customer has ensuring better performance and higher quality.
Applications do not need to be certified against Exadata. Applications that are certified with Oracle Database 11.2 RAC will run against Exadata. Very few applications need to certify the storage subsystem underneath a database, and Exadata fundamentally is the Oracle Database with a very fast storage subsystem.
Deploy in Days, Not Months
© 2010 Oracle Corporation

45. Faster than DW Appliances
50 GB/sec!
Flash
Query Throughput GB/sec Uncompressed Data Single Rack
Faster Throughput from Disk
Much Faster with Flash
50 TB of data fits in Flash
Using 10x Query Compression
Effective Query Throughput on compressed data is even higher
Hundreds of GB/sec
Disk
Teradata
2580
Netezza
TwinFin 12
Exadata V2
Why is Oracle Faster
DB Processing in Storage
Smart Flash Cache
Faster Interconnect (40Gb/sec)
More Disks
Faster Disks (15K RPM)
Exadata simultaneously scans from Flash and Disk to maximum query throughput.
Exadata allows flash directives at the table or partition level easily implementing ILM
Note that the limiting factor to query throughput with compressed flash cache data is generally CPU. The high rate of IO generally moves the bottleneck out of the IO system.

46. Oracle Exadata Momentum Rapid adoption in all geographies and industries

47. Oracle Exadata Database Machine: Changes the Game
Database intelligence and massively parallel scaling in the storage tier
Using state of the art industry standard hardware
Complete, Integrated Data Warehouse, OLTP and consolidation solution
High availability
Enterprise Security
Advanced analytics
Innovative new technologies:
Hybrid Columnar Compression
In-memory parallel execution
FlashFire hardware + flash-optimized software