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Data Warehouse Architectures White Papers

  • Data Warehousing Is Improved By Integrating Big Data Capabilities

    Sponsored by: IBM

    Both big data and data warehousing systems experience increased performance when they work together. In this expert e-guide, uncover the importance of data warehouses' storage and organization abilities, and learn how they can be combined with the increased analytics power of big data systems to provide improved insights.

  • Data Lakes: The 360-Degree Approach

    Sponsored by: Zaloni

    With so much data available, managed data lakes are becoming crucial to the modern data architecture. Learn how they can give your enterprise the agility and scalability needed for timely discovery and valuable business insights from big data.

  • Defining the Data Lake and Common Use Cases

    Sponsored by: Zaloni

    In a time when the variety and volume of data is continuously growing, data lakes are an emerging and powerful architectural approach, providing much needed flexibility. Learn more about the differences between data lakes and EDWs, keys to data lake management, and common use cases.

  • Architecting Data Lakes: Data Management Architectures for Advanced Business Use Cases

    Sponsored by: Zaloni

    Data lakes allow for all data to be stored regardless of source or format, including new types of social media and IoT data. Access this e-book for a comprehensive guide to data lakes and determine whether a data lake or EDW is right for your business.

  • Orlin & Cohen Orthopedic Group Benefits from a 24x7 Managed Electronic Medical Records Database Architecture

    Sponsored by: Cintra/Oracle

    In this white paper, learn how Orlin & Cohen overcame the challenges its legacy Windows-based Oracle standard Edition architecture and upgraded to an enterprise-class platform. Learn how they accomplished this without the typical cost and complexity associated with enterprise architecture but still gained high performance and reduced risk.

  • A Review of SQL Server

    Sponsored by: Microsoft

    Determine if SQL Server 2016 is a sensible upgrade for you. Learn about improvements to availability, scalability, security, and analytics—including support for in-memory OLTP and the R programming language.

  • How A Data Governance Framework Is The Blueprint for Success

    Sponsored by: SAS

    In this white paper, learn how a holistic approach to data governance combined with a data governance framework can provide timely, trusted, and high-quality data to everyone in your organization. Plus, discover the features of one data governance framework.

  • An Introduction to Amazon Redshift

    Sponsored by: Global Knowledge

    In this article, explore what Amazon Redshift is as well as what it is not. Find out how it compares with the costs, performance, support for third-party virtualization tools, scale and reliability. Also, examine a comparison of Amazon Redshift versus other solutions.

  • Improving Manufacturing with Advanced Data Analytics

    Sponsored by: Intel Corporation

    Increasing complexity in products, manufacturing processes, and the Internet of Things (IoT) means that massive amounts of data are being generated every day. Find out how to address 3 of the biggest challenges of data management with integrated analytics so you can reduce costs, improve process cycle time, and speed up time to market.

  • Integrated Analytics: Manage the Growing Diversity of Sales and Marketing Data Sources

    Sponsored by: Intel Corporation

    This white paper explores how to enable an integrated analytics approach by leveraging data lake models, visualizations, and self-service BI. Find out to simplify big data, overcome traditional data warehouse limitations, and increase efficiency with automation.

  • Database Explorations: Learn About Redis NoSQL Server Clusters

    Sponsored by: IBM

    This geek guide by web development expert Reuven Lerner highlights the factors that make Redis NoSQL server clusters worth considering. Explore the technical underpinnings that make Redis currently the most popular NoSQL technology.

  • Hadoop Deployments: Maximizing Efficiency for Big Data Analytics

    Sponsored by: IBM

    Many businesses recognize Hadoop as a premier cloud app framework, but they still don't know how to deploy Hadoop properly or prepare for its pitfalls. In this e-guide, we identify and explore some of the biggest Hadoop challenges. Find out how to resolve these issues and unlock the benefits of big data analytics.

  • The Future of Data Warehousing Infrastructure and Architectures

    Sponsored by: IBM

    This e-guide examines how a shift from traditional data warehousing (DW) appliances to an infrastructure that combines traditional DWs with big data technologies offers new opportunities for businesses to address needs such as costs, flexibility and agility while eliminating key technology silos.

  • Augment and Extend the Life of Your Data Warehouse

    Sponsored by: IBM

    Learn how organizations currently using a high powered data warehouse appliance can augment and extend the life of their data warehouses with industry-leading cloud data services. Discover tips for "future-proofing" your data warehouse and more.

  • Cloud-based data warehousing as-a-service, built for analytics

    Sponsored by: IBM

    Discover how a cloud-based data warehouse service offers integrated analytics to rapidly deliver answers. IBM's dashDB offers unique in-database analytics, R predictive modeling, and business intelligence tools could free you to analyze your data and get precise insights, quicker.

  • Cloud-based data warehousing as-a-service, built for analytics

    Sponsored by: IBM

    Traditional data warehousing has long been a painstaking endeavor, but today you have other options. Read on to learn about a fully managed, cloud data warehouse solution and the benefits it could help you realize.

  • Preparing Your Data Architecture for Big Data Analytics

    Sponsored by: Hewlett-Packard Enterprise

    While big data can provide actionable insights to drive business value, your enterprise can't experience those benefits without the right data architecture in place first. In this e-guide, analytics expert Lyndsay Wise reveals the 4 crucial factors to keep in mind before embarking on a big data project.

  • TDWI Checklist Report: Data Warehousing in the Cloud

    Sponsored by: IBM

    Using a cloud-based data warehouse provides value. Uncover ways this approach to data warehousing can reduce startup costs, potentially eliminate ongoing maintenance costs, accelerate analysis, and more.

  • Making an Operational Data Store (ODS) the Center of Your Data Strategy

    Sponsored by: Attunity

    This white paper provides an overview of why organizations today need operational data stores, how to sell an ODS to 5 different stakeholder groups, and best practices for implementing an ODS.

  • Big Data Era: Embrace Speed & Simplicity in your Data Warehouse for a Competitive Edge

    Sponsored by: IBM

    This white paper provides insight into what modern data warehouses need to accomplish to be relevant. Learn how adapting old technologies to manage new challenges is inadequate, and how you can manage big data simply and at low cost, while simultaneously processing advanced analytics at the speed of business.

  • How to Unlock Big Data's True Potential

    Sponsored by: IBM

    When it comes to big data, it can be difficult to combine data from disparate sources into a meaningful and valuable picture. Discover a business intelligence platform that can allow you to integrate data from heterogeneous sources, augment the data warehouse with Hadoop data services, leverage real-time analytics, and more.

  • Date Lake: Adoption and Maturity Survey Findings Report

    Sponsored by: Attunity

    Back by insights from 385 IT practitioners, this report, produced by Radiant Advisors and Unisphere Research, reveals the findings of data lake adoption and use cases.

  • Hadoop and the Modern Data Supply Chain

    Sponsored by: Attunity

    In this white paper, learn how organizations are coordinating multiple data sources in a data supply chain, enabling insights to travel nimbly throughout the enterprise. Additionally, learn the pros and cons of using Hadoop to process data, and how you can modernize the way you use data.

  • 8 Proven Strategies for Data Integration

    Sponsored by: Information Builders

    This white paper highlights 8 proven data integration strategies and uses real-world examples to demonstrate the high-value, high-return data access options that are available to you.

  • Cognos: BI: IBM Cognos Data Manager - Data integration for the last mile to BI

    Sponsored by: IBM

    This white paper explores the major challenges associated with integrating data and the key processes and factors associated with developing a conformed, dimensional data warehouse solution.

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