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Large-Scale Data Warehouse Platforms & Architectures:

How They Work, How They Differ, and Why It Matters

Course Overview

Throughout the entire lifecycle of a large-scale data warehouse program, you face crucial decisions which can dictate its success or failure – from choosing the best platform to host a major new application … to deciding whether the deployed platform can meet expanding requirements … to assessing whether your data warehouse is outgrowing its architecture and whether new technology can improve its price/performance.

To ensure sound decisions that continually enhance performance, scalability and availability, your data warehouse team must stay informed of today’s rapidly changing landscape of related products, architectures, technologies and practices.

This WinterCorp seminar provides a unique opportunity for your data warehouse professionals – learning together as a team – to gain an up-to-date, working knowledge of today’s commercial data warehouse products. Led by a renowned expert in terabyte-scale data management, Richard Winter, the course also provides a common understanding of the critical issues, concepts and principles that underlie the most important decisions in your data warehouse program.

The course covers:

• Technology, principles and architecture in the data warehouse platform

• Established data warehouse engines from IBM, Microsoft, Oracle, Sybase IQ and Teradata
• New data warehouse appliances from companies such as Greenplum, Netezza, Paraccel, Vertica and Aster Data Systems
• The growing role of Linux and Windows in data warehousing

Using examples from WinterCorp’s end-user consulting practice, the course will help you gain insight you can use to manage the performance, scalability and availability of your data warehouse throughout its lifecycle. The course will answer questions such as:

• How do today’s large-scale data warehousing products actually accomplish their fundamental operations, such as load and query?

• How do their architectures differ – and why does it matter?
• How do parallel processing, query optimization, indexing and partitioning contribute to high performance, scalability and availability? How does each data warehouse product handle these functions – and which products handle them best?
• What are the trade-offs between scale up and scale out solutions? Which products are best-suited for each approach?
• Which products are shared disk? Which are shared nothing? How does this matter?
• How important is the interconnect to your data warehouse architecture? How can you tell if your interconnect is scalable? What are the differences between BYNET, Gigabit/10-Gigabit Ethernet and InfiniBand?

Course Length & Format

Available on-site, the standard course curriculum is available in a one-day format that includes an interactive question-and-answer session with the instructors. The course can also be expanded to a two-day format with optional modules on advanced technical topics, platform selection, design, implementation and engineering management.

Who Should Attend

The course is designed for all database architects, project managers and senior technical staff involved in your large-scale data warehouse program.

Course Instructor

Richard Winter is an internationally known industry expert in large database technology, architecture and implementation with over twenty-five years of experience. As President of WinterCorp, a consulting firm in Waltham MA, he advises executives on their strategies and critical projects, focusing on data warehousing. Mr. Winter also oversees all WinterCorp consulting and research activities. He directs the Winter TopTen Research Program, which investigates the practices, technologies, products and techniques used in the world’s largest databases.  He has been a regular presenter at data warehouse conferences and is widely published.   He has served on the faculty of TDWI; as a contributor editor to Intelligent Enterprise; and, as expert on the B-Eye-Network. 

Course Outline

Large-Scale Data Warehouse Platforms & Architectures:

How They Work, How They Differ, and Why It Matters

1. Introduction

   1. Objectives

   2. Scope

2. Principles of Systems Architecture

1. Server Architectures

2. Interconnect Architectures

3. Storage Architectures

3. Review of Major Hardware Products

4. Principles of Data Warehouse Engine Architecture

   1. Partitioning

   2. Parallelism

   3. Optimization

   4. Indexing

   5. Availability

   6. Manageability

5. Review of Data Warehouse Software Products

   1. DB2 for Linux, Unix & Windows

   2. Microsoft SQL Server

   3. Oracle

   4. Sybase IQ

   5. Teradata

6. Appliances

   1. Aster Data Systems

   2. Greenplum

   3. Netezza

   4. Paraccel

   5. Vertica

7. Q&A

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