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Data Warehouse Software Research

  • Why Data Modeling Is Still Relevant

    Sponsored by: Quest

    There are those who think data modeling is passé or irrelevant. But data modeling offers a unique value not found in other techniques. Inside, learn what data modeling offers, how you can use it, and why it's still very much a relevant technique today.

  • 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.

  • Understanding The Relationship Between Master Data Management (MDM) & Application Data Management (ADM)

    Sponsored by: Triniti

    Failure to recognize potential pitfalls in a master data management (MDM) program can leave you disappointed. In this paper, understand the relationship between MDM and application data management (ADM) to better trust your data and devote more time to operations – not fixing data.

  • 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.

  • 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.

  • 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.

  • 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.

  • Understanding Insurance Industry Data Warehousing Challenges

    Sponsored by: IBM

    Learn how enhancements in the areas of life insurance and workers' compensation help companies address economic and technological challenges. Plus, discover how to build an effective data warehouse that provides a flexible, scalable solution which enables the consolidation and integration of data.

  • Reach New Performance Heights with Cloud Data Warehousing

    Sponsored by: IBM

    Discover a high performance cloud data warehouse service that can enable simple and fast information management, analytics, and business intelligence operations in the cloud. Explore how your enterprise can manipulate and analyze data without the added complexity of network cluster maintenance and database management.

  • 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.

  • 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.

  • Enabling an Agile Data Warehouse with Automation

    Sponsored by: Attunity

    Watch this webinar to learn how to overcome the limitations of traditional data warehouses with modern technology, which can enable you to automate and accelerate routine IT tasks associated with designing, creating, populating, and managing data warehouses and data marts.

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