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  • Analytic World and Oracles Approach

    Tolga YILDIRIM - BI Presales Manager (EE-CIS)

  • Despite pressure on IT spending

    Gartner EXP Worldwide Survey of More than 1,600 CIOs Shows IT Budgets in 2010 to be at 2005 Levels

    Gartner Press Release - January 19, 2010

    Business Intelligence remains a top priority

    2Copyright 2010 Oracle Confidential 2 OCDM Technical Training

    Top 3 Business Priorities for 2010

    1. Business process improvement

    2. Reducing Enterprise Costs

    3. Increasing the use of Information/Analytics

    Business Intelligence remains a top priority

  • Q: Why cant I get access to the

    data I need for decision making ?

    Q: Why do I have so many duplicate

    copies of data? Much of it is inaccurate!

    Q: Why are my applications

    referring to last weeks numbers?

    Information Management Challenges

    3

    Trusted Information

    Accurate

    Consistent

    Quality

    Accessible Information

    Available

    Secure

    Reliable

    Up-to-Date Information

    Fast access

    Multiple sources

    Actionable

  • Performance Management

    Custom Reporting

    PackagedApplications

    BusinessIntelligence

    Analytics

    Data FederationData MartsData Silos Data Hubs

    DataMigration

    DataReplication

    Data Warehousing

    Todays Reality Not planned, not consistent, not secure, difficult to change, etc..

    4 4

    OLTP & ODSSystems

    DataWarehouseData Mart

    SAP, OraclePeopleSoft, Siebel,

    Custom Apps

    FilesExcelXML

    Federation

    Custom

    Data Marts

    Data AccessData Silos

    SQLBatch Scripts

    Data Hubs

    OLAP

    Java

  • SOLUTION IS;

    Enterprise Data Warehouse

    environment instead of having

    departmental reporting silos

    Single BI tool to satisfy all reporting

    5

    Single BI tool to satisfy all reporting

    needs

  • WHAT IS DATA WAREHOUSE?

    A data warehouse (DW) is a database used for

    reporting. The data is offloaded from the

    operational systems for reporting. The main

    source of the data is cleaned, transformed,

    catalogued and made available for use by

    6

    catalogued and made available for use by

    managers and other business professionals

    for data mining, online analytical processing,

    market research and decision support.

  • Challenge: Much More Data to AnalyzeData Warehouse Size and Growth

    7

    Source: TDWI Next Generation Data Warehouse Platforms Report, 2009

  • Challenge: User Requirements Not MetHigh Churn in Data Warehouse Platforms

    8

    Source: TDWI Next Generation Data Warehouse Platforms Report, 2009

  • Reference ArchitectureMajor Components

    9

  • Reference ArchitectureMajor Components Data Sources

    10

  • Reference ArchitectureMajor Components Information Management

    11

  • Reference ArchitectureMajor Components Information Access

    12

  • Reference ArchitectureLoad Process from sources

    13

  • Reference ArchitectureLoad Process to Data Warehouse

    14

  • Reference ArchitectureInformation Provisioning

    15

  • EXADATA - ORACLEEXADATA - ORACLE

    Sales Analysis

    Forecasting

    Inventory Analysis

    OLAP

    Moving toward a Clean Architecture

    OBIEEFoundationInteractive Dashboards

    Ad-hoc Analysis

    Reporting &Publishing

    16

    Inventory Analysis

    Market Basket

    Analysis

    Loss Analysis

    Customer Loyalty

    Analysis

    Data Mining

    GoldenGate Oracle Data Integrator

    Scorecards

    Detect& Alert

    Office Integration

    ESSBASE

  • EXADATA - ORACLEEXADATA - ORACLE

    Sales Analysis

    Forecasting

    Inventory Analysis

    OLAP

    Moving toward a Clean Architecture

    EXALYTICS

    17

    Inventory Analysis

    Market Basket

    Analysis

    Loss Analysis

    Customer Loyalty

    Analysis

    Data Mining

    GoldenGate Oracle Data Integrator

    TimesTen for Exalytics

    Memory Optimized Essbase

    OBI Foundation

  • 18

    Oracle Golden Gate

  • Oracle GoldenGate : One Line SummaryThe Solution for Enterprise-Wide Real-Time Data Needs

    Real-timeinformation

    Database and applications, Mixed sources, distributed

    systems, legacy, OLTP, OLAP

    Mission Critical Applications & Data, Business

    Intelligence, Reporting for

    19

    Oracle GoldenGate delivers real-time access of real-time information, enabling companies to dramatically improve the availability, reliability, and performance

    of critical data across enterprise systems.

    OLTP, OLAP Reporting for Customers, Partners & Employees

    Real-time Access

  • 20

    Exadata as Ideal Platform for DW

  • Oracle Exadata Database MachineThe Ideal Data Warehousing Platform

    Improve query performance by 10x

    Better insight into customer requirements

    Expand revenue opportunities

    Consolidate OLTP and analytic workloads

    Lower admin and maintenance costs

    21

    Lower admin and maintenance costs

    Reduce points of failure

    Integrate analytics and data mining

    Complex and predictive analytics

    Lower risk

    Streamline deployment

    One support contact

  • Why is Exadata Fast?

    Exadata off-loads data intensive processing to the storage Row filtering based on where predicate

    Column filtering

    Join filtering

    Incremental backup filtering

    Storage Indexing

    Scans on encrypted data

    22

    Data Mining model scoring

    Database Machine delivers a high speed IO subsystem

    Exadata delivers smart flash cache for all workloads

  • Select sum(sales)where salesdate=22-Jan-2010B

    Return entire Sales table

    Traditional Query

    What Were Yesterdays

    Sales?

    23

    Sum

    Data is pushed to database server for processing

    I/O rates are limited by speed and number of disk drives

    Network bandwidth is strained, limiting performance and concurrency

    Discard most of

    sales table

  • Select sum(sales)where salesdate=22-Jan-2010B

    Return Sales for Jan 22 2010

    Exadata Smart ScanImprove Query Performance by 10x or More

    What Were Yesterdays

    Sales?

    24

    Sum

    Off-load data intensive processing to Exadata Storage Server

    Exadata Storage Server only returns relevant rows and columns

    Wide Infiniband connections eliminate network bottlenecks

  • Exadata Storage IndexTransparent I/O Elimination with No Overhead

    Exadata Storage Indexes maintains summary information about table data in memory

    Stores MIN and MAX values of filter columns

    Typically one index entry for every MB of disk

    Eliminates disk I/Os if MIN and MAX can never match where clause of a query

    Negative index

    Completely automatic and transparent

    2525

    Order_date Ship_date Cust_ID

    Prod_ID

    Amount

    03-SEP-2009 19-SEP-2009 10075 32932 10,000.00

    03-SEP-2009 05-SEP-2009 20098 20098 20,000.00

    03-SEP-2009 07-OCT-2009 10089 20010 15,000.00

    03-SEP-2009 01-OCT-2009 20100 10000 35,000.00

    03-SEP-2009 19-OCT-2009 80300 30000 10,000.00

    03-SEP-2009 03-NOV-2009 10000 2030 40,000.00

    MIN ship_date = 01-OCT-2009MAX ship_date = 03-NOV-2009

    Select * from orders where ship_date < 31-SEP-2009

    Only first set of rows can match

    MIN ship_date = 19-SEP-2009MAX ship_date = 07-OCT-2009

  • Exadata CompressionReduce Disk Space Requirements

    1.4x

    2.5 xOracle

    Oracle

    Advanced

    Compression

    26

    3x

    10x15x

    2.5 x

    UncompressedData

    Data Warehouse Appliances

    OLTP Data

    DW Data

    Archive Data

    Oracle

    Hybrid

    Columnar

    Compression

    Compression

  • 27

    Advanced Analytics

  • Built-in Analytics Secure, Scalable Platform for Advanced Analytics

    Oracle Data Mining

    Oracle OLAPAnalyze and summarize

    28

    Complex and predictive analytics embedded into Oracle Database 11g

    Reduce cost of additional hardware, management resources

    Improve performance by eliminating data movement and duplication

    Oracle Data MiningUncover and predict

  • Summary ManagementImprove Response Time with Materialized Views

    DateSQL Query Sales by Date

    Sales by Product

    Sales by Region

    Sales by Channel

    Region

    Query Rewrite

    29

    Pre-summarized information stored within Oracle Database 11g

    Separate database object, transparent to queries

    Supports sophisticated transparent query rewrite

    Fast incremental refresh of changed data

    Products Channel

    Materialized ViewsRelational Star

    Schema

  • Region Date

    Cube Organized Materialized Views

    SQL Query

    Automatic

    Query Rewrite

    Summaries

    30

    Exposes Oracle OLAP cubes as relational materialized views

    Provides SQL access to data stored in an OLAP cubes

    Any BI tool or SQL application can leverage OLAP cubes

    Products Channel

    Automatic Refresh

  • Oracle Data MiningFind Hidden Patterns, Make Predictions

    Retail Financial Services

    Customer Segmentation

    Response Modeling

    Credit Scoring

    Possibility of default

    Communications Utilities

    Customer churn

    Network intrusion