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Data Warehouse Fundamentals for Storage Professionals – What You Need to Know EMC Proven Professional Knowledge Sharing 2011
Data Warehouse Fundamentals for Storage Professionals – What You Need To Know EMC Proven Professional Knowledge Sharing 2011 Bruce Yellin Advisory Technology Consultant EMC Corporation [email protected] Table of Contents Introduction ................................................................................................................................ 3 Data Warehouse Background .................................................................................................... 4 What Is a Data Warehouse? ................................................................................................... 4 Data Mart Defined .................................................................................................................. 8 Schemas and Data Models ..................................................................................................... 9 Data Warehouse Design – Top Down or Bottom Up? ............................................................10 Extract, Transformation and Loading (ETL) ...........................................................................11 Why You Build a Data Warehouse: Business Intelligence .....................................................13 Technology to the Rescue?.......................................................................................................19 RASP - Reliability, Availability, Scalability and Performance ..................................................20 Data Warehouse Backups .....................................................................................................26 -
Netezza EOL: IBM IAS Is a Flawed Upgrade Path Netezza EOL: IBM IAS Is a Flawed Upgrade Path
Author: Marc Staimer WHITE PAPER Netezza EOL: What You’re Not Being Told About IBM IAS Is a Flawed Upgrade Path Database as a Service (DBaaS) WHITE PAPER • Netezza EOL: IBM IAS Is a Flawed Upgrade Path Netezza EOL: IBM IAS Is a Flawed Upgrade Path Executive Summary It is a common technology vendor fallacy to compare their systems with their competitors by focusing on the features, functions, and specifications they have, but the other guy doesn’t. Vendors ignore the opposite while touting hardware specs that mean little. It doesn’t matter if those features, functions, and specifications provide anything meaningfully empirical to the business applications that rely on the system. It only matters if it demonstrates an advantage on paper. This is called specsmanship. It’s similar to starting an argument with proof points. The specs, features, and functions are proof points that the system can solve specific operational problems. They are the “what” that solves the problem or problems. They mean nothing by themselves. Specsmanship is defined by Wikipedia as: “inappropriate use of specifications or measurement results to establish supposed superiority of one entity over another, generally when no such superiority exists.” It’s the frequent ineffective sales process utilized by IBM. A textbook example of this is IBM’s attempt to move their Netezza users to the IBM Integrated Analytics System (IIAS). IBM is compelling their users to move away from Netezza. In the fall of 2017, IBM announced to the Enzee community (Netezza users) that they can no longer purchase or upgrade PureData System for Analytics (the most recent IBM name for its Netezza appliances), and it will end-of-life all support next year. -
EMC Greenplum Data Computing Appliance: High Performance for Data Warehousing and Business Intelligence an Architectural Overview
EMC Greenplum Data Computing Appliance: High Performance for Data Warehousing and Business Intelligence An Architectural Overview EMC Information Infrastructure Solutions Abstract This white paper provides readers with an overall understanding of the EMC® Greenplum® Data Computing Appliance (DCA) architecture and its performance levels. It also describes how the DCA provides a scalable end-to- end data warehouse solution packaged within a manageable, self-contained data warehouse appliance that can be easily integrated into an existing data center. October 2010 Copyright © 2010 EMC Corporation. All rights reserved. EMC believes the information in this publication is accurate as of its publication date. The information is subject to change without notice. THE INFORMATION IN THIS PUBLICATION IS PROVIDED “AS IS.” EMC CORPORATION MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND WITH RESPECT TO THE INFORMATION IN THIS PUBLICATION, AND SPECIFICALLY DISCLAIMS IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Use, copying, and distribution of any EMC software described in this publication requires an applicable software license. For the most up-to-date listing of EMC product names, see EMC Corporation Trademarks on EMC.com All other trademarks used herein are the property of their respective owners. Part number: H8039 EMC Greenplum Data Computing Appliance: High Performance for Data Warehousing and Business Intelligence—An Architectural Overview 2 Table of Contents Executive summary ................................................................................................. -
Microsoft's SQL Server Parallel Data Warehouse Provides
Microsoft’s SQL Server Parallel Data Warehouse Provides High Performance and Great Value Published by: Value Prism Consulting Sponsored by: Microsoft Corporation Publish date: March 2013 Abstract: Data Warehouse appliances may be difficult to compare and contrast, given that the different preconfigured solutions come with a variety of available storage and other specifications. Value Prism Consulting, a management consulting firm, was engaged by Microsoft® Corporation to review several data warehouse solutions, to compare and contrast several offerings from a variety of vendors. The firm compared each appliance based on publicly-available price and specification data, and on a price-to-performance scale, Microsoft’s SQL Server 2012 Parallel Data Warehouse is the most cost-effective appliance. Disclaimer Every organization has unique considerations for economic analysis, and significant business investments should undergo a rigorous economic justification to comprehensively identify the full business impact of those investments. This analysis report is for informational purposes only. VALUE PRISM CONSULTING MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS DOCUMENT. ©2013 Value Prism Consulting, LLC. All rights reserved. Product names, logos, brands, and other trademarks featured or referred to within this report are the property of their respective trademark holders in the United States and/or other countries. Complying with all applicable copyright laws is the responsibility of the user. Without limiting the rights under copyright, no part of this report may be reproduced, stored in or introduced into a retrieval system, or transmitted in any form or by any means (electronic, mechanical, photocopying, recording, or otherwise), or for any purpose, without the express written permission of Microsoft Corporation. -
Dell Quickstart Data Warehouse Appliance 2000
Dell Quickstart Data Warehouse Appliance 2000 Reference Architecture Dell Quickstart Data Warehouse Appliance 2000 THIS DESIGN GUIDE IS FOR INFORMATIONAL PURPOSES ONLY, AND MAY CONTAIN TYPOGRAPHICAL ERRORS AND TECHNICAL INACCURACIES. THE CONTENT IS PROVIDED AS IS, WITHOUT EXPRESS OR IMPLIED WARRANTIES OF ANY KIND. © 2012 Dell Inc. All rights reserved. Reproduction of this material in any manner whatsoever without the express written permission of Dell Inc. is strictly forbidden. For more information, contact Dell. Dell , the DELL logo, the DELL badge, and PowerEdge are trademarks of Dell Inc . Microsoft , Windows Server , and SQL Server are either trademarks or registered trademarks of Microsoft Corporation in the United States and/or other countries. Intel and Xeon are either trademarks or registered trademarks of Intel Corporation in the United States and/or other countries. Other trademarks and trade names may be used in this document to refer to either the entities claiming the marks and names or their products. Dell Inc. disclaims any proprietary interest in trademarks and trade names other than its own. December 2012 Page ii Dell Quickstart Data Warehouse Appliance 2000 Contents Introduction ............................................................................................................ 2 Audience ............................................................................................................. 2 Reference Architecture .............................................................................................. -
Magic Quadrant for Data Warehouse Database Management Systems
Magic Quadrant for Data Warehouse Database Management Systems Gartner RAS Core Research Note G00209623, Donald Feinberg, Mark A. Beyer, 28 January 2011, RV5A102012012 The data warehouse DBMS market is undergoing a transformation, including many acquisitions, as vendors adapt data warehouses to support the modern business intelligence and analytic workload requirements of users. This document compares 16 vendors to help you find the right one for your needs. WHAT YOU NEED TO KNOW Despite a troubled economic environment, the data warehouse database management system (DBMS) market returned to growth in 2010, with smaller vendors gaining in acceptance. As predicted in the previous iteration of this Magic Quadrant, 2010 brought major acquisitions, and several of the smaller vendors, such as Aster Data, Ingres and Vertica, took major strides by addressing specific market needs. The year also brought major market growth from data warehouse appliance offerings (see Note 1), with both EMC/Greenplum and Microsoft formally introducing appliances, and IBM, Oracle and Teradata broadening their appliance lines with new offerings. Although we believe that much of the growth was due to replacements of aging or performance-constrained data warehouse environments, we also think that the business value of using data warehouses for new applications such as performance management and advanced analytics has driven — and is driving — growth. All the vendors have stepped up their marketing efforts as the competition has grown. End-user organizations should ignore marketing claims about the applicability and performance capabilities of solutions. Instead, they should base their decisions on customer references and proofs of concept (POCs) to ensure that vendors’ claims will hold up in their environments. -
The Teradata Data Warehouse Appliance Technical Note on Teradata Data Warehouse Appliance Vs
The Teradata Data Warehouse Appliance Technical Note on Teradata Data Warehouse Appliance vs. Oracle Exadata By Krish Krishnan Sixth Sense Advisors Inc. November 2013 Sponsored by: Table of Contents Background ..................................................................3 Loading Data ............................................................3 Data Availability .........................................................3 Data Volumes ............................................................3 Storage Performance .....................................................4 Operational Costs ........................................................4 The Data Warehouse Appliance Selection .....................................5 Under the Hood ..........................................................5 Oracle Exadata. .5 Oracle Exadata Intelligent Storage ........................................6 Hybrid Columnar Compression ...........................................7 Mixed Workload Capability ...............................................8 Management ............................................................9 Scalability ................................................................9 Consolidation ............................................................9 Supportability ...........................................................9 Teradata Data Warehouse Appliance .........................................10 Hardware Improvements ................................................10 Teradata’s Intelligent Memory (TIM) vs. Exdata Flach Cache. -
State of the Data Warehouse Appliance Krish Krishnan
Thema Datawarehouse Appliances The future looks bright considering all the innovation State of the Data Warehouse Appliance Krish Krishnan Krish Krishnan is a recognized expert worldwide in the strategy, architec- ture and implementation of high performance data warehousing solutions. He is a visionary data warehouse thought leader and an independent analyst, writing and speaking at industry leading conferences, user groups and trade publications. His conclusion: The future looks bright for the data warehouse appliance. We have been seeing in the past 18 months a steady influx of runs for 10 hours in a 1,000,000 records database”; data warehouse appliances, and the offerings include the esta- - “My users keep reporting that the ETL processes failed due to blished players like Oracle and Teradata. There are a few facts large data volumes in the DW”; that are clear from this rush of options and offerings: - “My CFO wants to know why we need another $500,000 for - The data warehouse appliance is now an accepted solution and infrastructure when we invested a similar amount just six is being sponsored by the CxO within organizations; months ago”; - The need to be nimble and competitive has driven the quick - “My DBA team is exhausted trying to keep the tuning process maturation of data warehouse appliances, and the market is online for the databases to achieve speed.” embracing the offerings where applicable; - Some of the world’s largest data warehouses have augmented The consistent theme throughout the marketplace focuses on the the data warehouse appliance, including: New York Stock need to keep performance and response time up without incur- Exchange has multiple enterprise data warehouses (EDWs) on ring extra spending due to higher costs. -
Government Contracting M&A Update
Government Contracting M&A Update “Market Intelligence for Business Owners” Q3 2013 Capstone Partners Investment Banking Advisors BOSTON | CHICAGO | LONDON | LOS ANGELES | PHILADELPHIA | SAN DIEGO | SILICON VALLEY Government Contracting Coverage Report MERGERS & ACQUISITIONS UPDATE With the nation’s attention focused on reducing government spending and sequestration, one would expect mergers & acquisitions in the government contracting space to come CAPSTONE PARTNERS LLC to a standstill. But such is not the case, with the number of acquisitions announced 200 South Wacker Drive through June totaling more than 250. 31st Floor Chicago, IL 60606 M&A Activity: Government Contractors www.capstonellc.com 1000 964 900 852 800 786 772 786 732 751 700 568 Ted Polk 600 521 Transactions Managing Director 500 of 398 (312) 674‐4531 400 [email protected] 300 256 Number 200 100 Lisa Tolliver 0 Director 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 YTD (312) 674‐4532 2013 [email protected] YTD 2013 through June 30, 2013 Source: Capital IQ, Capstone Partners LLC research While the year’s activity is currently on‐track to come in under the 2012 figure, that trend is reflective of what we are seeing in mergers and acquisitions in general. M&A activity across the board has been down in early 2013 compared to 2012, primarily the result of the market continuing to absorb the rash of transactions that were closed at the end of 2012 in anticipation of rising capital gains tax rates. But, while the number of closed transactions has slowed this year, M&A activity continues to be supported by strong market fundamentals, namely reasonably high transaction valuations; strategic acquirers with strong balance sheets; abundant private equity capital; an accessible and affordable debt market; and a modestly expanding U.S. -
Gartner Magic Quadrant for Data Management Solutions for Analytics
16/09/2019 Gartner Reprint Licensed for Distribution Magic Quadrant for Data Management Solutions for Analytics Published 21 January 2019 - ID G00353775 - 74 min read By Analysts Adam Ronthal, Roxane Edjlali, Rick Greenwald Disruption slows as cloud and nonrelational technology take their place beside traditional approaches, the leaders extend their lead, and distributed data approaches solidify their place as a best practice for DMSA. We help data and analytics leaders evaluate DMSAs in an increasingly split market. Market Definition/Description Gartner defines a data management solution for analytics (DMSA) as a complete software system that supports and manages data in one or many file management systems, most commonly a database or multiple databases. These management systems include specific optimization strategies designed for supporting analytical processing — including, but not limited to, relational processing, nonrelational processing (such as graph processing), and machine learning or programming languages such as Python or R. Data is not necessarily stored in a relational structure, and can use multiple data models — relational, XML, JavaScript Object Notation (JSON), key-value, graph, geospatial and others. Our definition also states that: ■ A DMSA is a system for storing, accessing, processing and delivering data intended for one or more of the four primary use cases Gartner identifies that support analytics (see Note 1). ■ A DMSA is not a specific class or type of technology; it is a use case. ■ A DMSA may consist of many different technologies in combination. However, any offering or combination of offerings must, at its core, exhibit the capability of providing access to the data under management by open-access tools. -
Presto: the Definitive Guide
Presto The Definitive Guide SQL at Any Scale, on Any Storage, in Any Environment Compliments of Matt Fuller, Manfred Moser & Martin Traverso Virtual Book Tour Starburst presents Presto: The Definitive Guide Register Now! Starburst is hosting a virtual book tour series where attendees will: Meet the authors: • Meet the authors from the comfort of your own home Matt Fuller • Meet the Presto creators and participate in an Ask Me Anything (AMA) session with the book Manfred Moser authors + Presto creators • Meet special guest speakers from Martin your favorite podcasts who will Traverso moderate the AMA Register here to save your spot. Praise for Presto: The Definitive Guide This book provides a great introduction to Presto and teaches you everything you need to know to start your successful usage of Presto. —Dain Sundstrom and David Phillips, Creators of the Presto Projects and Founders of the Presto Software Foundation Presto plays a key role in enabling analysis at Pinterest. This book covers the Presto essentials, from use cases through how to run Presto at massive scale. —Ashish Kumar Singh, Tech Lead, Bigdata Query Processing Platform, Pinterest Presto has set the bar in both community-building and technical excellence for lightning- fast analytical processing on stored data in modern cloud architectures. This book is a must-read for companies looking to modernize their analytics stack. —Jay Kreps, Cocreator of Apache Kafka, Cofounder and CEO of Confluent Presto has saved us all—both in academia and industry—countless hours of work, allowing us all to avoid having to write code to manage distributed query processing. -
Nexus User Guide (Pdf)
The Best Query Tool Works on all Systems When you possess a tool like Nexus, you have access to every system in your enterprise! The Nexus Query Chameleon is the only tool that works on all systems. Its Super Join Builder allows for the ERwin Logical Model to be loaded, and then Nexus shows tables and views visually. It then guides users to show what joins to what. As users choose the tables and columns they want in their report, Nexus builds the SQL for them with each click of the mouse. Nexus was designed for Teradata and Hadoop, but works on all platforms. Nexus even converts table structures between vendors, so querying and managing multi-vendor platforms is transparent. Even if you only work with one system, you will find that the Nexus is the best query tool you have ever used. If you work with multiple systems, you will be even more amazed. Download a free trial at www.CoffingDW.com. The Tera-Tom Video Series Lessons with Tera-Tom Teradata Architecture and SQL Video Series These exciting videos make learning and certification much easier Four ways to view them: 1. Safari (look up Coffing Studios) 2. CoffingDW.com (sign-up on our website) 3. Your company can buy them all for everyone to see (contact [email protected]) 4. YouTube – Search for CoffingDW or Tera-Tom. The Tera-Tom Genius Series The Tera-Tom Genius Series consists of ten books. Each book is designed for a specific audience, and Teradata is explained to the level best suited for that audience.