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Data Warehouse Software Research

  • 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.

  • Five Things to Look for When Implementing a Data Warehouse

    Sponsored by: IBM

    Discover a 5-step checklist for important criteria in selecting data warehouse technologies, backed by a recent study.

  • 3 Ways to Modernize Your Data Strategy in Minutes

    Sponsored by: Google

    Today's organizations are rushing to create actionable insights out of their big data, and this starts with modernizing data warehouses. This white paper provides 3 tips to making your warehouse stronger, smarter, and more profitable.

  • Managing Data Complexity: Does Your Warehouse Measure Up?

    Sponsored by: IBM

    Learn how to see an increase in revenue by receiving timely data. Access this quick guide to find your way to a Hybrid data warehouse report by Aberdeen Group.

  • How Hybrid Cloud Options Complement the On-Premises Data Warehouse

    Sponsored by: Teradata

    In this double case study, learn how Core Digital Media, an online marketing company, and an anonymous global mining company, adopted Teradata cloud to complement their on-premise data warehouses. Discover the benefits both realized, including lower costs and greater flexibility.

  • The Current State of The Cloud Analytics and Data Warehouse Market

    Sponsored by: Teradata

    As adoption of cloud software increases, organizations are evaluating the pros and cons of deploying software on the cloud – including data warehousing tools. In this IDC technology spotlight, uncover the current state of the cloud analytics market. Plus, learn about Teradata, a provider of big data analytics and marketing applications technology.

  • AWS and Data Warehousing: Extending Your Data Analytics With The Right Tools

    Sponsored by: Looker

    Amazon Web Services (AWS) sets a standard for delivering customers a wide range of innovative cloud services. Learn about Amazon Webshift, which extends the power of AWS by providing a high-performance data warehousing tool and data management for today's new analytics workloads.

  • How Dollar Shave Club Cuts The Competition With a Data Advantage

    Sponsored by: Looker

    How does a small e-commerce business with a good idea - and a great sense of humor - solve their data bottleneck and go up against leading retail giants to win? Ask Dollar Shave Club. In this case study, learn how this e-commerce upstart trimmed its data bottleneck considerably.

  • Big Data Integration: 3 Vendors Changing the Game

    Sponsored by: Looker

    How are you going to get more value from your data lake? 3 vendors — Looker Data Sciences, SnapLogic, and Snowflake Computing — offer new ways of making processes faster and more valuable. Inside this Forrester Research Inc. report, learn how they're pushing the boundaries of big data integration with new ideas about how to get value faster.

  • Data integration strategy: A clearer path for data

    Sponsored by: TechTarget

    A data integration strategy can help organizations get the most out of information that lies in every corner—from data warehouses to cloud applications. Gain insight and advice on building an integration strategy to support diverse pools of data and modern application needs in our expert guide, The Glue in Data-Driven Businesses.

  • The Enterprise-Wide Benefits of Real-Time Data

    Sponsored by: Tealium

    Organizations that support real-time customer data enable marketers and data analysts to work with the same source, closing enterprise-wide gaps in insights. Read on to learn more about real-time data enrichment tools.

  • 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.

  • Drive Deeper Insights across Data with SQL Server 2016

    Sponsored by: Microsoft

    Explore how SQL Server 2016 can help drive deeper insights into big data from both relational and non-relational sources, in the cloud and on-premise. Discover how SQL Server 2016 helps you store data in more formats at scale, open up data access, provide predictive analytics, and share insights on-premise, via the web, and through mobile devices.

  • 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.

  • 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.

  • 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.

  • A Data Warehouse for Big Data and Beyond

    Sponsored by: IBM

    Considering how heavily business decisions now rely on data (and now big data), your data warehouse needs to be working at its maximum potential to handle the demands. If you're just exploring what's out there, or looking to optimize/modernize your warehouse, learn which services will be needed in the era of big data.

  • An Analytical Approach to your Data Architecture

    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.

  • How Hadoop Can Make Integrating Structured And Unstructured Data Simple and Easy

    Sponsored by: IBM

    Access this white paper to learn how Hadoop can serve as an integration platform to harmonize data in a way that can be processed in relational databases and data warehouses. Inside, discover how Hadoop acts as a data lake, making mining for important information simple, simplify data access for non-technical users, and more.

  • Hadoop Makes Big Data Storage Accessible For Everyone

    Sponsored by: IBM

    Discover how Hadoop flipped the traditional big data storage paradigm by adopting a philosophy of using commodity hardware and storage to build the equivalent of a data warehouse at a much lower cost. Learn how Hadoop's extreme flexibility gives it the ability to natively scale-out and accommodate both structured and unstructured data.

  • 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.

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