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Enhancing the Performance and Analytic Content of the Data Warehouse Using Oracle OLAP Option. Bud Endress, Director of Product Management - OLAP September 5, 2008.

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enhancing the performance and analytic content of the data warehouse using oracle olap option

Enhancing the Performance and Analytic Content of the Data Warehouse Using Oracle OLAP Option

Bud Endress, Director of Product Management - OLAP

September 5, 2008

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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.

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olap in the data warehouse
OLAP in the Data Warehouse

Use Oracle OLAP to enhance your data warehouse

  • Simplified summary management
  • ‘Speed of thought’ query performance
  • Advanced time series analysis and analytic content
  • Centralized management of data, meta data, calculations and security

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olap in the data warehouse1
OLAP in the Data Warehouse

Every data warehouse can benefit from Oracle OLAP

  • Every business intelligence tool accesses summary data
  • Every business user wants excellent query performance in both static and exploratory BI applications
  • Every business user will benefit from rich analytic content

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olap in the data warehouse2
OLAP in the Data Warehouse

Embedded Oracle OLAP is preferred by IT to external solutions

  • Use the database you already own
  • Use the BI tools they already own
  • Use Oracle skills you already have
  • Embedded Oracle OLAP is secure and enterprise ready

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olap in the data warehouse3
OLAP in the Data Warehouse
  • Ask yourself the following questions
    • Do you use business intelligence tools?
      • Oracle BI EE, Business Objects, Cognos, MicroStrategy, etc.?
    • Would business users benefit from
      • Significantly improved query performance?
      • Rich analytic content?
    • Would IT benefit from
      • Fast, efficient updates of data sets?
      • Fewer servers to manage?
      • Consolidating stand alone OLAP servers into the database?

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oracle olap option
Oracle OLAP Option
  • A summary management solution for SQL based business intelligence applications
    • An alternative to table-based materialized views, offering improved query performance and fast, incremental update
  • A full featured multidimensional OLAP server
    • Excellent query performance for ad-hoc / unpredictable query
    • Enhances the analytic content of Business intelligence application
    • Fast, incremental updates of data sets

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olap option
OLAP Option
  • An embedded OLAP solution
    • Runs within Oracle Database Enterprise Edition
    • Data are stored in Oracle data files
    • Meta data in the Oracle Data Dictionary
    • Fully compatible with RAC / Grid computing

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olap option1
OLAP Option
  • A secure solution
    • Oracle users are OLAP users
    • SQL GRANT / REVOKE on OLAP cubes and dimensions
    • Compatible with Virtual Private Database
    • Fine Grained Cube Security

Oracle Authentication

SQL Cube Access Control

Virtual Private Database

Fine Grained Cube Security

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olap option2
OLAP Option
  • An open solution
    • Oracle cubes and dimensions are queried using
      • SQL
      • PL / SQL
      • Oracle OLAP API
    • Transparent access as cube-organized materialized view
      • SQL

SELECT

time,

product,

customer,

sales_ytd

FROM

sales_cube

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olap option3
OLAP Option
  • A content rich solution
    • Rich aggregations
    • Time series
    • Indices and market shares
    • Rankings
    • Forecasting
    • Allocations
    • Statistics
  • Calculations are embeddedin the database
    • Centrally managed for consistency
    • Accessible by any application

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olap option4
Predictable query environment

Predefined reports

Predefined calculations

Less exploration of data

Exploratory query environment

Users define reports

Users access any data

Users define calculations

More users amplify this effect

OLAP Option
  • OLAP cubes are optimized for ad-hoc, exploratory usage patterns

Static Reporting

Self Service Reportingand Analysis

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olap option5
OLAP cubes offer excellent performance for unpredictable query patterns

Appropriate for bothstatic and exploratoryreporting

Advantages increaseas reporting becomesmore exploratory

OLAP Option

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olap option6
OLAP Cubes offer fast, incremental updates of data sets

Manage all summaries in a single database object

Fast, incrementalmaterialized view refresh

Incremental / fastaggregation

Cost-basedaggregation

OLAP Option

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olap option7
OLAP Cubes offer fast, incremental updates of data sets

Manage all summaries in a single database object

Fast, incrementalmaterialized view refresh

Incremental / fastaggregation

Cost-basedaggregation

OLAP Option

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olap option8
OLAP Option
  • One cube can be used as
    • A summary management solution to SQL-based business intelligence applications as cube-organized materialized views
    • A analytically rich data source to SQL-based business intelligence applications as SQL cube-views
    • A full-featured multidimensional cube, servicing dimensionally oriented business intelligence applications

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sql query of olap cubes
SQL Query of OLAP Cubes

BI Application

BI Application

SQL

SQL

CubeMaterializedViews

Cube Views

Automatic Query Rewrite

Oracle Cube

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one cube dimensional or sql tools single version of the truth

Metadata

Data

Business Rules

One Cube, Dimensional or SQL ToolsSingle version of the truth

OLAP Query

Extract, Load

& Transform (ELT)

SQL Query

Centrally managed data, meta data and business rules

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cube organized materialized views
Cube Organized Materialized Views
  • Transparently enhance the query performance of BI applications
    • Data is managed in an Oracle cube
      • Fast query
      • Fast refresh
      • Manage a single cube instead of 10’s, 100’s or 1,000’s of table-based materialized views
    • Applications query base / detail relational tables
      • Oracle automatically rewrites SQL queries to OLAP cubes
      • Access to summary data in the cube is fully transparent

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materialized views typical mv architecture today
Materialized ViewsTypical MV Architecture Today

BI Application

  • Users expect excellent query response for all summary queries
    • Might require 10’s, 100’s or even 1,000’s of materialized views
    • Difficult to manage
    • Longer build and update times

Automatic Query Rewrite

SELECT SUM(sales)GROUP BY quarter, brand,region, channel

Summary Data: Collections of Materialized Views

Fact Table: Sales by Day, Item, Customer and Channel

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cube organized materialized views automatic query rewrite
Cube-Organized Materialized ViewsAutomatic Query Rewrite

BI Application

  • A single cube manages summaries for all groupings in the model
  • A cube can be represented as a cube-organized materialized view
  • Oracle automatically rewrites summary queries to the cube
  • A singe cube can replace 10’s, 100’s or 1,000’s of materialized views

Automatic Query Rewrite

SELECT SUM(sales)GROUP BY quarter, brand,region, channel

Fact Table: Sales by Day, Item, Customer and Channel

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slide23

Typical query issued by Oracle Business Intelligence Enterprise Edition.

Query is automatically rewritten by Oracle to access summary data in the cube-organized materialized view.

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cube organized materialized views fast incremental mv refresh
Cube-Organized Materialized ViewsFast, Incremental MV Refresh

BI Application

  • A single cube is refreshed using MV refresh system
    • Fast, incremental update from MV logs.
    • Fast, incremental aggregation within the cube.
    • Efficient management of sparse data sets.
    • Replaces 10’s, 100’s or even 1,000’s of table-based MVs

SELECT SUM(sales)GROUP BY quarter, brand,region, channel

MV Refresh

Fact Table: Sales by Day, Item, Customer and Channel

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cube organized materialized views1
Cube Organized Materialized Views
  • An excellent summary management solution for business intelligence tools such as BI EE, MicroStrategy, Cognos and Business Objects
  • Cube organized materialized views are similar to materialized views on pre-built tables
    • Cube organized materialized views are meta data only – they do not store data; data comes from the cube
  • A common implementation will be to leave detail data in tables and create the cube at aggregate levels
    • E.g. tables with day, customer and cube with month, zip code

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cube organized materialized views case study
Cube Organized Materialized ViewsCase Study
  • Compares performance of table-based materialized views with cube-organized materialized views with goals of:
    • Improving query performance of SQL-based BI tools
    • Reducing build/update times
  • Source data
    • Fast moving consumer goods company data
    • 7 dimensions
    • 20 million fact rows

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cube organized materialized views case study1
Cube Organized Materialized ViewsCase Study
  • Methodology
    • Indexes and materialized views were created as per Oracle SQL Access Advisor recommendations.
      • 124 materialized views
      • 198 indexes
    • Oracle cube and cube-organized materialized views were created by DBA.
      • 1 compressed cube
      • Pre-aggregated to 20%
    • 1469 test queries

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cube organized materialized views case study2
Cube Organized Materialized ViewsCase Study
  • Measurements
    • Time to load data and prepare it for query
      • MVs: Create MVs, create indexes and compute statistics
      • Cube: Load data and aggregate.
    • Query performance
      • Run the same 1469 queries against MVs and cube.

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olap cubes views sql query of oracle cubes
OLAP Cubes ViewsSQL Query of Oracle Cubes
  • Cube is represented as star schema of relational views
  • Dimension and fact views
  • Detail and summary fact rows
  • Rich analytic fact columns
  • OLAP Cube Includes
  • All levels of summarization
  • Rich analytical calculations

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empowering any sql based tool simple sql queries advanced cube content
Empowering Any SQL-Based Tool Simple SQL Queries Advanced Cube Content

Application Express on Oracle OLAP

SELECT cu.long_description customer, f.profit_rank_cust_sh_parent, f.profit_share_cust_sh_parent, f.profit_rank_cust_sh_level,f.profit,f.gross_margin

FROM time_calendar_view t, product_primary_view p, customer_shipments_view cu, channel_primary_view ch, units_cube_view f

WHERE t.level_name = \'CALENDAR_YEAR\' AND t.calendar_year = \'CY2006\' AND p.dim_key = \'TOTAL\' AND cu.parent = \'TOTAL\' AND ch.dim_key = \'TOTAL\' AND t.dim_key = f.TIME AND p.dim_key = f.product AND cu.dim_key = f.customer AND ch.dim_key = f.channel;

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Oracle Business Intelligence Enterprise Edition querying time series calculations directly from an Oracle cube using SQL.

Oracle cubes can make any BI tool smarter and faster.

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SQL issued by Oracle BI EE against views of Oracle cube and dimensions.

New Joined Cube Scan row source pushes joins into the cube and accesses summary data and calculations.

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oracle olap option summary
Oracle OLAP OptionSummary
  • Enhances the performance and analytic content of SQL-based business intelligence applications.
  • May be used as:
    • A summary management solution with cube-organized materialized views.
    • A full-featured multidimensional cube and calculation engine queried directly with SQL
  • Embedded in the Oracle database instance and storage.
    • Safe, secure and manageable.
    • Fully compatible with Grid Computing/Real Application Clusters.

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for more information
For More Information
  • Oracle.com
    • http://www.oracle.com/solutions/business_intelligence/olap.html
  • Oracle Technology Network:
    • http://www.oracle.com/technology/products/bi/olap/index.html
  • Product Discussion Forum:
    • http://forums.oracle.com/forums/forum.jspa?forumID=16

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Q

&

A

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