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Data Warehouse Architectures Research

  • BI and Analytics on a Data Lake

    Sponsored by: MapR

    BI and analytics plus big data equals an explosive business differentiator across all industries and regions. Discover how you can create actionable insights by building big data BI and analytics on data lakes and converged data platforms.

  • Planning for Digital Transformation with a Converged Data Platform

    Sponsored by: MapR

    Discover how to keep up with the progression of big data use cases by implementing a converged data platform that leverages the power of Hadoop, Spark, and Apache Drill.

  • Cloud-Based BI and Analytics Systems Start Taking a Firmer Shape

    Sponsored by: SearchBusinessAnalytics

    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.

  • The Modern Approach to Business Intelligence

    Sponsored by: Tableau Software

    Whether you're working with data in spreadsheets, warehouses, or across disparate data sets, this white paper explores how to improve analytics and access to real-time insights. Uncover the 7 key attributes that are shaping the modern approach to business intelligence.

  • Vitria VIA IoT Analytics Platform Overview

    Sponsored by: Vitria Technology, Inc.

    This brief webcast examines Vitria and their real-time IoT analytics platform. Learn how to generate faster insights to drive smarter decision-making and bolster IoT business strategies, predictive analytics, data visualizations, and more.

  • Understanding the 4 Zones of Data Lake Architecture

    Sponsored by: Zaloni

    In this presentation, Zaloni CEO and co-founder Ben Sharma discusses the 4 zones of data architecture, the challenges and tools to building data lakes, and how you can leverage your data lake to serve your needs.

  • Analytics in Action: Tackling the Big Data Headache

    Sponsored by: SAS

    Find out how to take the big data challenge and turn it into a golden opportunity for your company with new approaches to data management and analytics. Learn about 5 steps to maximize the value of Hadoop and your data warehouse, 3 use cases for predictive analytics, and more.

  • Better Together? Hadoop and Your Enterprise Data Warehouse

    Sponsored by: SAS

    Explore ways to overcome the challenges of moving your entire data warehouse to Hadoop. Plus, hear from big data expert Tom Davenport on augmenting small data projects with Hadoop big data initiatives.

  • Why Your Data Warehouse Needs a Data Lake and How to Make Them Work Together

    Sponsored by: Zaloni

    Complementing your DW with a data lake can be a smart first step. But before tackling a DW augmentation project, it's a good idea to review your current resources and understand what you'll need. Explore 2 reasons why companies augment their DW, tips for seamlessly integrating a data lake into a DW, and more.

  • A Governed Data Lake: The 360┬░ 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.

  • An Analytics Use Case for Unified Data

    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.

  • 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.

  • Big Data Poses Weighty Challenges for Data Integration Best Practices

    Sponsored by: SearchDataManagement

    Organizations that deploy big data platforms are finding that they also need an upgraded data integration framework to meet rising demands. In this expert handbook, uncover advice on how to navigate the demands of big data architectures, high volume data warehousing, and data lakes by updating your data integration strategy.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

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