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Datawarehousing White Papers (View All Report Types)
 
The Data Lake Data Integration Challenge
sponsored by SnapLogic
WHITE PAPER: This white paper explores how to update data integration to meet the unique challenges of big data and data lakes. With insights backed by Linthicum Research, learn how to meet the core data integration, governance, and security needs of data lakes.
Posted: 06 Apr 2018 | Published: 06 Apr 2018

SnapLogic

Top Reasons to Choose EMC for SAP HANA
sponsored by EMC Corporation
WHITE PAPER: EMC is the leading enterprise storage platform for SAP, making it ideal for your SAP HANA solution. Click here for more reasons why EMC is the natural choice when it comes to your SAP HANA deployment.
Posted: 27 May 2014 | Published: 31 Oct 2013

EMC Corporation

7 must-have capabilities of big data DBMS
sponsored by IBM
WHITE PAPER: Companies are rushing to invest in big data analytics tools, but many forget about the underlying infrastructure that supports their big data efforts. In this informative white paper, learn why the right database management system (DBMS) could be the key to a successful big data analytics project.
Posted: 07 Apr 2014 | Published: 28 Feb 2014

IBM

SQL Server 2012 Fast Track Data Warehouse on PowerEdge R720xd
sponsored by Dell and Microsoft SQL
WHITE PAPER: Read this white paper to learn how to configure your SQL Server data warehousing system to support growing online analytical processing (OLAP) loads while lowering costs, easing management, and improving performance.
Posted: 21 Jun 2012 | Published: 31 May 2012

Dell and Microsoft SQL

Unified Data Architecture
sponsored by Teradata
WHITE PAPER: Access the following e-book to uncover the tools and strategies you need to get the most out of big data. Learn from leading authors in the field of data management as they explain some of the common mistakes made by analytics professionals while mining for new insights and what you can do to avoid them.
Posted: 31 Jan 2014 | Published: 31 Jan 2014

Teradata

Best Practices for Implementing a High-Performance Data Warehouse
sponsored by SAS
WHITE PAPER: There are more new forms of data today than ever before, and traditional business intelligence systems cannot always handle the amount of stress from this influx of information.  Check out this white paper to discover a system known as 'high performance data warehousing' that can help you successfully analyze and glean insights from your big data.
Posted: 11 Apr 2013 | Published: 31 Dec 2012

SAS

Deliver Better Results Across the Data Management Lifecycle: HP AppSystem for Microsoft SQL Server 2012 Parallel Data Warehouse
sponsored by HP
WHITE PAPER: The following whitepaper outlines the important steps to consider when implementing a diversified data management strategy.
Posted: 18 Oct 2013 | Published: 18 Oct 2013

HP

The Human Side of Big Data and High-Performance Analytics
sponsored by SAS
WHITE PAPER: The following white paper explores the through the eyes of pioneering analyst, Tom Davenport, on the importance of the data scientist when it comes to success with big data and advanced analytics. Learn how they how they help, how to onboard or create them, and much more.
Posted: 29 Apr 2014 | Published: 29 Apr 2014

SAS

The Next Wave of Data Management : Is Big Data The New Normal?
sponsored by Talend
WHITE PAPER: The following white paper reviews the business drivers that are impacting the new wave of data management, highlights the new tools companies have for consideration in their next generation data architecture, and finally outlines a total data management blueprint for consideration in your big data strategy.
Posted: 28 Jul 2014 | Published: 28 Jul 2014

Talend

IBM Cognos Data Manager
sponsored by IBM
WHITE PAPER: Access the following white paper to uncover how a data manager works seamlessly with your Cognos BI solution to help simplify the way your data is presented. Get a firsthand look at how simplification can effectively increase the performance of the end user and more.
Posted: 15 Jan 2014 | Published: 15 Jan 2014

IBM
 

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