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June 11, 2009

Oracle 11g Data Warehousing Masterclass with Mark Rittman

Filed under: Oracle Seminars — H.Tonguç Yılmaz @ 11:55 am

Mark Rittman will be in Istanbul for a two days seminar this month(30 June-1 July), most probably I will be there and here is the details of this seminar.

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  1. Oracle 11g Data Warehousing Masterclass Seminar Description :

    The Oracle Database is the foundation for any Oracle Business Intelligence and analytical application, and Oracle Database 11g delivers a number of new and incremental features that relates to data warehousing, analytics and aggregate management. This two-day seminar, delivered by Mark Rittman, takes delegates through the 11g release of Oracle’s data warehousing platform, examines several new features and provides an end-to-end guide to delivering fast, efficient data warehouses using the latest Oracle tools and database features.

    Topics:
    Oracle 11g Data Warehouse Design ETL and Data Loading Indexing – Bitmap Indexes, Bitmap Join Indexes, Indexing for Star Transformations, Index Tuning using the SQL Access Advisor Partitioning, Compression & Parallel Execution SQL for Analysis Summarization & Oracle OLAP Data Mining Data Warehouse Optimization & Tuning

    Day 1 :
    Creating the Data Warehouse Foundation
    – Oracle 11g Data Warehouse Design – The three-layer model – Constraints – Real Application Clusters – Storage – Backup & Recovery – Optimized Warehouse Initiative – ETL and Data Loading – SQL ETL functions – Merge – Table Functions – Multi-table Inserts – Parallel DML – Data Pump – Transportable Tablespaces – Oracle Warehouse Builder 11g – Indexing – Bitmap Indexes – Bitmap Join Indexes – Indexing for Star Transformations – Index Tuning using the SQL Access Advisor – Partitioning, Compression & Parallel Execution – New Partitioning features in 11g – Partitiion Pruning – Partition-wise Joins – Index Partitioning – Partitioning and Table Compression – Basic Segment Compression – Loading data into a standard compressed segment – Advanced Compression – ILM & ILM Assistant

    Day 2 :

    Effective Data Warehouse Querying, Mining and Tuning
    – SQL for Analysis – Analytic Functions – Pivoting Operations – User-defined Aggregates – Data Densification (Partition Outer Join) and Time-Series Calculations – Model Clause – SQL For Aggregation – Rollup, Cube – Grouping Sets – With clause (subquery factoring) – Grouping into Itemsets – Hierarchical Cubes – Summarization & Oracle OLAP – Basic Materialized Views – Advanced Materialized Views – Refresh Mechanisms & MV Maintenance – Creating Analytic Workspaces – Querying AWs using SQL Views – Cube Organized Materialized Views – Data Mining – Introduction to Oracle Data Mining – Key algorithms – Preparing data for data mining – Supervised and Unsupervised mining – Incorporating DM functionality into the DW – Oracle Data Miner – Data Warehouse Optimization & Tuning – Star Transformations – Basic Query Rewrite – Advanced Query Rewrite (Query Equivalence) – Reading Explain Plans – Reading Trace Files – Data Warehouse Tuning using Oracle Enterprise Manager

    Comment by H.Tonguç Yılmaz — June 24, 2009 @ 10:58 am | Reply


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