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Teradata Physical Implementation

Price
1,530 USD
2 Days
CFLQ-185
Classroom Training, Online Training
Teradata

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Course Description

Overview

This Teradata Physical Implementation course is designed to provide students with in-depth knowledge of Teradata Implementation. This course can be taught using Version 12, 13, or 14. Please inform your sales representative of which version you are currently using.
 

Objectives


 

Audience

  • A mix of beginning,intermediate and advanced Teradata users

Prerequisites

    • None

Topics

  • The Teradata Architecture
    • Teradata Spreads the Rows across AMPs
    • The Teradata Architecture
    • The Parsing Engine
    • The PE comes up with a PLAN the AMPs follow
    • The AMPs
    • Born to be parallel
    • The BYNET
    • A Scalable Architecture
    • Single-AMP Retrieve
    • Primary Index
  • The Primary Index
    • Two Types of Primary Indexes (UPI or NUPI)
    • Unique Primary Index (UPI)
    • Non-Unique Primary Index (NUPI)
    • Multi-Column Primary Indexes
    • When do you define the Primary Index?
    • Defining a Non-Unique Primary Index (NUPI)
    • Defining a Multi-Column Primary Index
  • Laying out and Retrieving Data
    • Hashing the Primary Index Value
    • The Hash Map
    • An 8-AMP Hash Map Example
    • Laying a Row onto the Proper AMP
    • Retrieving a Row by way of the Primary Index
    • Hashing Non-Unique Primary Indexes (NUPI)
    • Placing Non-Unique Primary Indexes (NUPI) Rows
    • Non-Unique Primary Indexes Continued
    • Placing (NUPI) Rows Continued
    • Retrieving (NUPI) Rows
    • Placing Multi-Column Primary Index Rows
    • Retrieving Multi-Column Primary Index Rows
    • Even Distribution with an UPI
    • Uneven Distribution with a NUPI
    • Unacceptable Distribution with a NUPI
    • Review – Parsing Engines Plan with an UPI
    • Review – Parsing Engines Plan with a NUPI
    • Review – Big Trouble – The Full Table Scan
    • Big Trouble – A Picture of a Full Table Scan
    • Test your Teradata Primary Index Knowledge
  • The Row-ID
    • The Uniqueness Value
    • The Row ID
    • Duplicates and the Uniqueness Value
    • AMPs Sort Their Rows by the Row ID
    • Search the Data like a Phone Book
    • A Visual for Data Layout
    • Test Your Teradata Access Query Knowledge
    • UPI Row-ID Test
    • NUPI Row-ID Test
  • Secondary Indexes
    • The Base Table
    • Creating a Unique Secondary Index (USI)
    • The Secondary Index Subtable
    • Inside the Secondary Index Subtable
    • How Teradata builds the Secondary Index Subtable
    • Lab: Place the USI Rows on the Proper AMP
    • Lab: Place the USI Rows on the Proper AMP
    • Building the Secondary Index Subtable Results
    • USI – Always a Two-AMP Operation
    • USI Summary
    • USI Pictorial using the Hash Maps
    • USI Secondary Index Quiz
    • A Full Table Scan Example
    • The Base Table
    • Creating a Non-Unique Secondary Index (NUSI)
    • Columns inside a NUSI Secondary Index Subtable
    • NUSI Subtable is AMP-Local
    • A Query using the NUSI Column
    • A Query using the NUSI Column
    • NUSI Recap
    • Value Ordered NUSI
    • Secondary Index Summary
    • Test Your Teradata Access Query Knowledge
    • An Incredible Quiz Opportunity
  • Partitioned Tables
    • Range Queries
    • Why we had to perform a Full Table Scan
    • A Partitioned Table
    • A Partitioned Table
    • One Year of Orders Partitioned
    • Fundamentals of Partitioning
    • Add the Partition to the Row-ID for the Row Key
    • You Partition a Table when you CREATE the Table
    • RANGE_N Partitioning by Week
    • RANGE_N Partitioning Older and Newer Data
    • Case_N Partitioning
    • Multi-Level Partitioning
    • New Feature V13.10 – Character Based PPI
    • NEW! Character Based PPI Multi-Level Example
    • NEW! CASE Based Character PPI
    • TIMESTAMP partitioning that is Deterministic
    • Disadvantages of PPI Tables
    • PPI Tricks for the Primary Index
    • Using the Keyword Partition
    • Partitions for No Case, No Range and Unknown
    • SQL for RANGE_N
    • SQL for CASE_N
    • Adding and Deleting Partitions
    • Adding and Deleting Partitions with INSERT
    • Partitioning Rules
    • See the data
    • Test Your Teradata Access Knowledge
  • Columnar
    • Columnar Tables are NOPI tables
    • A No Primary Index (NOPI) table
    • How to CREATE a NOPI table
    • NOPI tables spread data evenly
    • NOPI tables are often used for ETL Staging Tables
    • NOPI Options
    • NOPI Restrictions
    • NOPI Row-ID Architecture
    • Columnar Tables still have AMPs process entire row
    • How does a Columnar Table differ from a traditional Teradata Table
    • The fundamentals of Columnar
    • Columnar splits rows into column Containers
    • All Column Containers contain rows in perfect order
    • Columnar Relative Row Numbers among Containers
    • File System Generating (FSG) Cache
    • How Teradata processes using FSG Cache
    • How Columnar provides performance benefits
    • How to create a Columnar Table
    • Comparing Normal Tables to Columnar Tables
    • How normal tables are processed
    • How columnar tables are processed
    • Indexes can be used with Columnar
    • Visualize a Columnar Table
    • Questions to answer about Columnar
    • Single-Column and Multi-Column Containers
    • Columnar Row Hybrid Creation
    • Advanced Rules of Columnar Tables
    • Row Based Partitioned (PPI) Tables
    • CREATE Statement for both row and column partitioning
    • Column and Row partitioning combined
    • How to load a Columnar Table
    • Columnar Table Access through Secondary Indexes
    • Columnar Compression Capabilities
    • Auto Compress in Columnar
    • When and When NOT to use Columnar Tables
    • Restrictions of Columnar Tables
  • Joins
    • A Join Example
    • Joins and the Primary Index
    • Redistributing Rows in Spool
    • Redistributing Rows of Both Tables
    • Duplicating the Smaller Table
    • Quiz – How Many Rows are in Spool?
    • Quiz Answer – How Many Rows in Spool?
    • How Duplication Appears on Every AMP
    • How Many Rows in Spool with Redistribution?
    • Answer to How Many Rows in Spool
    • An Example of an AMP with Redistribution
    • New V13 – Up to 128 Tables Joined Together!
  • The Logical and Extended Logical Model (ELDM)
    • Primary and Foreign Keys
    • A Normalized Data Warehouse
    • Normalization
    • Dimensional Modeling also called Star Schema
    • Dimensional Modeling also called Star Schema
    • Fact Table Vs Dimensional Table
    • The Extended Logical Data Model (ELDM)
    • The End Goal of the ELDM
    • Column ACCESS in the WHERE Clause
    • The Purpose of Examining Access
    • The Purpose of Examining Access for Joins
    • Data Demographics
    • Distinct Values
    • Distinct Values Danger
    • Maximum Rows per Value
    • Typical Rows per Value
    • Maximum Rows NULL
    • Change Rating
    • Extended Logical Data Model Template
    • The Application Development Life Cycle
  • The Physical Data Model
    • An Overview of picking the right Primary Index
    • Step 1 – Look at Distribution
    • Step 1 – Test - Find the Potential Index Candidates through good Distribution
    • Step 1 – Answers- Find the Potential Index Candidates through good Distribution
    • Step 2 – Eliminate based on Change Rating
    • Step 3 – NUSI Elimination via Value Access Frequency
    • Step 4 – Pick the Primary Index
    • Why Join Access Frequency is Top Priority?
    • Why Value Access Frequency is Second Priority?
    • What have we learned about picking the Primary Index?
    • You pick the final Primary and Secondary Index
    • What have we learned about picking the Primary Index?
    • Check your answer to the Primary Index pick
    • Step 5 — Pick Secondary Indexes
    • USI Considerations
    • USI to eliminate Duplicate Row Checking
    • NUSI considerations
    • Four Techniques for using a NUSI
    • Tactical Queries
  • Denormalization
    • Derived Data
    • Storing Aggregates
    • Derived Data and Temporary Tables
    • Derived Tables
    • Volatile Temporary Tables
    • Global Temporary Tables
    • Pre–Joining Tables
    • Repeating Groups
    • Horizontal Partitioning 1 - Splitting Rows into Separate Tables
    • Horizontal Partitioning 2 – Separating Rows through a Partitioned Primary Index (PPI) Table
    • Vertical Partitioning
    • Covered Query
    • Value Ordered NUSI
    • Identity Columns
  • Join Indexes
    • Join Index Fundamentals
    • Many types of Join Indexes
    • A Multi-Table Join Index Example
    • Multi-Table Join Index Picture
    • Compressed Multi-Table Join Index Example
    • Compressed Multi-Table Join Index Picture
    • Single-Table Join Index
    • Explain showing use of the Join Index
    • Compressed Single-Table Join Index Example
    • Aggregate Join Index
    • Sparse Join Index
    • Global Multi-Table Join Index
    • Hash Index
    • Join Index Details to Remember
    • New in V13 – Compression in your Join Index from the Base Tables
  • Compression
    • How Compression Works
    • Using the Nexus Query Chameleon to Compress
    • An Example of SmartCompress of Nexus
    • Compression Reports with Nexus
    • Compression in V13
  • COLLECT STATISTICS
    • Parsing Engine uses Statistics for the Plan
    • Columns and Indexes to Collect Statistics On
    • Syntax to Collect Statistics
    • Recollecting Statistics
    • Random Sample instead of Collected Statistics
    • V12 Statistics Enhancement – Stale Statistics
    • Where Statistics are Stored in DBC
    • A Collect Statistics Example
    • What Statistics Really Collects?
    • Loner Values and High Bias Intervals
    • Teradata Limits
  • Chapter 15 – The Load Utility BTEQ
    • Teradata Load Utilities Continued
    • BTEQ
    • The Four Types of BTEQ Exports
    • FastLoad
    • FastLoad has Two Phases
    • Acquisition Phase 1
    • FastLoad Application Phase 2
    • A Sample FastLoad Script
    • MultiLoad
    • The Five Phases of MultiLoad
    • A Sample MultiLoad Script
    • TPump
    • Limitations of TPump
    • A Sample TPump Script
    • FastExport
    • FastExport Enhancement – No Spool
    • Teradata Parallel Transport
    • The TPT Data Stream Flow
    • TPT Operators
    • Read from Multiple Source Files Simultaneously
    • TPT Operators and their Functions
    • TPT Operator Types
    • TPT Operators and their Equivalent Load Utility
    • How to Run a TPT Script
  • 2023 Top 20 Training Industry Company - IT Training

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