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DATA WAREHOUSING FOR LIFE SCIENCES: HOW TO ELIMINATE DATA SILOS AND PROVIDE BUSINESS VALUE
sponsored by Maven Wave
WHITE PAPER: For some scientists, it can be more challenging to store, integrate, and prepare data than it can be to find the critical insights hidden in it. Access this white paper to learn how Maven Wave, a Google Cloud Partner, can help you leverage the capabilities of cloud data warehouses to accelerate and ease your journey to discovering crucial insight.
Posted: 09 Oct 2020 | Published: 09 Oct 2020

Maven Wave

Delivering Trusted Information with IBM InfoSphere Foundation Tools
sponsored by IBM
WHITE PAPER: This paper discusses challenges with trusted data in enterprises and recommends solutions through a data warehousing implementation scenario. The paper also discusses the capabilities of InfoSphere Foundation Tools and provides proof points through customer scenarios on the productivity, acceleration and risk reduction benefits.
Posted: 29 Nov 2010 | Published: 29 Nov 2010

IBM

Data Quality Considerations in Master Data Management Structure
sponsored by Pitney Bowes Group 1 Software
WHITE PAPER: This white paper discusses the challenges, solutions and importance of data management consolidation within an organization.
Posted: 13 Sep 2011 | Published: 13 Sep 2011

Pitney Bowes Group 1 Software

Best Practices for Decision Support Systems with Microsoft SQL Server 2012 using Dell EqualLogic PS Series Storage Arrays
sponsored by Dell and VMware
WHITE PAPER: This white paper describes sizing and best practices for deploying a data warehouse in order to prevent bottlenecks and deliver a cost-effective solution.
Posted: 29 Aug 2013 | Published: 31 Jul 2013

Dell and VMware

BI is in the Details: How Columnar Technology Leverages the Latent Value in SQL Databases
sponsored by Vertica Systems
WHITE PAPER: This paper will discuss how Vertica enhances the capabilities of analytical work through the implementation of different architecture for relational database-based analytical work. By simply rotating the orientation of the database from rows to columns, dramatic improvements in load and query speed, scalability and cost effectiveness are achieved.
Posted: 29 Aug 2011 | Published: 01 Sep 2009

Vertica Systems

Cisco Business Intelligence Appliance for SAP
sponsored by Cisco Systems, Inc.
WHITE PAPER: Read this paper to discover powerful, self-service business intelligence (BI) that helps you locate, evaluate, and use your crucial business information while minimizing the operational cost.
Posted: 22 Nov 2011 | Published: 22 Nov 2011

Cisco Systems, Inc.

E-Book: Getting the Most Out of Your BI Investment in SAP Environments
sponsored by IBM
EBOOK: In this e-book, readers will get an overview of SAP’s BI strategy, and get advice on what to do about BEx, BW, and more to develop long-term BI strategies of their own. Read on to learn how to get the most out of your BI investment in SAP environment.
Posted: 27 Dec 2010 | Published: 27 Dec 2010

IBM

Extreme Warehouse Speed for Fast Business Decisions
sponsored by IBM
WHITE PAPER: This e-book explores how forward-looking organizations like yours are using extremely rapid, highly effective analysis of data to change the way they make decisions – enabling them to predict shifts in business and proactively adjust for better business outcomes.
Posted: 03 Sep 2013 | Published: 31 Dec 2012

IBM

Cloud-Based BI and Analytics Systems Start Taking a Firmer Shape
sponsored by SearchBusinessAnalytics
EBOOK: In this expert handbook, explore the current state of cloud BI and analytics adoption and examine how companies like Lenovo are migrating big data and predictive analytics to the AWS cloud.
Posted: 24 Aug 2017 | Published: 29 Jun 2017

SearchBusinessAnalytics

Presentation Transcript: Five Reasons to Offload Analytics from Your Data Warehouse
sponsored by ParAccel
PRESENTATION TRANSCRIPT: Traditional data warehouse infrastructure struggles to keep up with the expanding demand for a wide and changing variety of analytic workloads.  The result is growing frustration as end-users are forced to use sample data, aggregate data and even restricted in their access to information in standalone or enterprise data warehouses.
Posted: 06 Dec 2011 | Published: 06 Dec 2011

ParAccel
 

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