ComputerWeekly.com Research Library

Powered by Bitpipe.com

Data Warehouse Architectures White Papers

  • 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 the versatility of data lake models, increasing the value of visualizations, and accelerating self-service BI. Find out to make it easier to handle 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.

  • Realizing the Promise of a Data Lake

    Sponsored by: Zaloni

    From 2010 to 2020, the amount of data is expected to increase by 20 times, with 77% of relevant data being unstructured. Learn why enterprise data warehouses (EDWs) can't always deliver the necessary insights and discover how Hadoop data lakes can pick up where EDWs leave off.

  • 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.

  • 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.

  • Product Tour: IBM PureData System for Analytics

    Sponsored by: IBM

    Explore this interactive resource to learn more about how data analytics technology can enable you to master risk and compliance, accelerate time-to-insights, and more.

  • An Integrated Platform Approach Brings IT Goals within Reach

    Sponsored by: Red Hat

    IT is taking advantage of new aggregations of servers, open source operating systems, and in-memory technology to accelerate business transformation. Discover how these tools can help leverage big data and analytics, modernize the data warehouse, and more.

  • A Data Warehouse for Big Data and Beyond

    Sponsored by: IBM

    Considering how much business decisions now rely on data, your data warehouse needs to be optimized and modernized. Learn how to update your warehouse and see what services it will need to provide in the era of big data.

  • Research Report: Data Warehouse Modernization in the Age of Big Data Analytics

    Sponsored by: IBM

    An overwhelming 89% of businesses consider data warehouse modernization an opportunity. This comprehensive TDWI research report highlights insights from a recent survey on data warehouse modernization to help you identify the trends that matter most to your organization. Also explore the top 12 priorities for data warehouse modernization today.

  • Architecting A Platform For Big Data Analytics

    Sponsored by: IBM

    This Intelligent Business Strategies paper explains the new technical and data requirements for identifying, processing, and analyzing data. Discover how to become a disruptor by gaining an understanding of shifting customer behavior.

  • Maximizing Your Data Lake with a Cloud or Hybrid Approach

    Sponsored by: IBM

    Access this Aberdeen Research report to discover how a Hadoop-based data lake maintained in a cloud or hybrid environment can provide benefits such as greater access to data across the organization, enhanced accuracy in the analysis process, and more.

  • 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.

  • A Data Warehouse for Big Data and Beyond

    Sponsored by: IBM

    Considering how much business decisions now rely on data, your data warehouse needs to be optimized and modernized. Learn how to update your warehouse and see what services it will need to provide in the era of big data.

  • Getting More Out of Hadoop Data Lakes and Big Data

    Sponsored by: IBM

    This in-depth guide provides expert insights into the challenges posed by big data today and how technology is advancing to help overcome them. Learn what to consider before adopting a data lake, how Hadoop is coming closer to bridging the enterprise data warehouse gap, and more.

  • 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.

  • 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.

  • 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.

  • 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.

Bitpipe Definitions: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Other

What's Popular at Bitpipe? Daily Top 50 Reports | Daily Top 100 Topics | Popular Report Topics

ComputerWeekly.com Research Library Copyright © 1998-2016 Bitpipe, Inc. All Rights Reserved.

Designated trademarks and brands are the property of their respective owners.

Use of this web site constitutes acceptance of the Bitpipe Terms and Conditions and Privacy Policy.