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Data Warehouse Architectures Research

  • 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, in the future, they will be combined with the increased analytics power of big data systems to provide improved insights.

  • Avnet, Inc: Serving up Insight to Customers Faster than Ever with Data Analytics and Warehousing in the Cloud

    Sponsored by: IBM

    Learn how to accelerate analytics and reporting with a cloud-based data warehousing platform that combines high-performance in-memory technology with in-database analytics processing. Download now to turn data into actionable insights, and fast.

  • Cloud and Local Data Warehousing: Purpose-Built for Analytics

    Sponsored by: IBM

    Discover an overview of a data warehouse appliance purpose-built for analytics on both cloud and locally, optimized to handle newer data types and applications in today's hybrid environments. Learn how to enact elastic scaling with a database that can rapidly compose new applications.

  • Data Warehousing in the Cloud: An Essential Adoption Checklist

    Sponsored by: IBM

    Discover how to glean greater business value from your data by utilizing a cloud-based data warehouse. Uncover a 7-point checklist that will facilitate easy adoption, including instructions on how to meet consistent performance requirements and proactively manage data connectivity.

  • Why Cloud is The Future of Data Warehousing

    Sponsored by: IBM

    This 2 page whitepaper explores how you can stay ahead in a world full of big data by combining the processing power of data warehousing with the agility and flexibility of the cloud. Find out how you can determine data quality with an automated efficiency query, advance processing so your entire dataset doesn't have to fit in-memory, and more.

  • Accelerate and Simplify Oracle with Rack-Scale Flash Storage

    Sponsored by: Dell EMC

    This resource explores how you can speed up workloads and deliver agility in Oracle environments. Discover how to accelerate analytics for larger data sets, enable self-service, and more.

  • Developing a Strategy for Data Lake Governance

    Sponsored by: Zaloni

    Access this webinar to learn about how to develop the best data lake governance strategy to fit your organization's goals. Discover how to start building and managing your data lake while enabling it to deliver valuable, actionable business insight.

  • 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.

  • 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.

  • 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.

  • An Integrated Approach: Analytics, Data Warehouses, Big Data and More

    Sponsored by: IBM

    Find out how you can leverage an integrated appliance to make data computing simpler. You'll discover how to bring analytics right into the database, add agility, and eliminate siloes. Additionally, you'll learn how to optimize the performance of data warehouse services for analytic apps, including those that require big data capabilities.

  • 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.

  • 30-Day dashDB: Test Drive Data Warehousing and Analytics Functionalities

    Sponsored by: IBM

    A well-designed data warehouse system can help boost the corporate bottom line, but if you aren't careful, data warehouse performance can bog down in different places. Start a free 30-day trial to dashDB, a fully-managed cloud data warehouse built specifically for analytics. Take their data warehousing and analytics capabilities for a test drive.

  • 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.

  • 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.

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