Research & Resources

Research Reports


  • TDWI IoT Readiness Assessment TDWI IoT Readiness Guide Cover image

    The Internet of Things (IoT)—a network of connected devices that collect and interpret data over the Internet—is a hot and growing trend. These devices—which include sensors, RFID tags, and more—are in your home in smart appliances; you’re wearing them for health and wellness. They are on factory floors, in office buildings, on farms, and much more. IoT is being used by organizations to change their business model, improve operations, and improve the customer experience. Some view it as a competitive necessity. Read Now

  • TDWI Analytics Maturity Model

    TDWI has developed an analytics maturity model to help you determine the maturity of your organization's analytics initiatives when compared with other companies. The model provides the big picture of an analytics program, where it needs to go, and where you should concentrate your attention to create more value for your data. Read Now

  • TDWI Big Data Maturity Model

    TDWI developed the Big Data Maturity Model to describe the stages that most organizations follow when they embark on big data initiatives. The model provides the big picture of a big data program, where it needs to go, and how to get there. As organizations move through these stages, they gain more and more value from their investments. Read Now

  • TDWI Hadoop Readiness Assessment

    TDWI's Hadoop Readiness Assessment is an online questionnaire that asks how prepared you and your organization are to get full value from Hadoop. When you complete the questionnaire, the assessment tool immediately shows you scores that quantify your readiness for Hadoop. It is designed to help answer your questions about where to focus your best efforts with Hadoop. Read Now



  • Navigating the Predictive Analytics Market

    Predictive analytics is on the verge of widespread adoption. Enterprises are extremely interested in deploying predictive capabilities. In a recent TDWI survey about data science, about 35 percent of respondents said they had already implemented predictive analytics in some way. In a 2017 TDWI education survey, predictive analytics was the top analytics-related topic respondents wanted to learn more about. August 1, 2017 View Now

  • Use Big Data Analytics and Geoenrichment to Drive Better Business Outcomes

    The volumes of data and speed at which data is produced continually increases on an exponential scale. Consumer transaction data, client records and data in motion from mobile devices, IoT sensors and other sources usually contains associated geographic coordinates that require geospatial processing to extract value. With the volume and variety of this data, organizations need to have a location strategy that includes big data technology that can join disparate data sets (geoenrichment) and perform location analytics to reveal actionable business and operational insights. August 15, 2017 View Now

  • Get More Business Value from a Data Lake via Data-as-a-Service (DaaS)

    Data lakes are coming on strong as a modern and practical way of managing the large volumes and broad range of data types and sources that enterprises are facing today. TDWI sees data lakes managing diverse data successfully for business-driven use cases, such as omni-channel marketing, multi-module ERP, the digital supply chain, and data warehouses extended for business analytics. Yet, even in business-driven examples like these, user organizations still haven’t achieved full business value and return on investment from their data lakes. August 16, 2017 View Now

  • Making Multiplatform Data Architectures Work for You: Common Use Cases and Reference Architectures

    To leverage the new wave of advanced data sources available, users and architects are turning to a multiplatform data architecture (MDA), where numerous diverse data platforms and tools are integrated in a multiplatform, distributed architecture. An MDA is typified by an extreme diversity of platform types that may include multiple brands of relational databases, NoSQL platforms, in-memory functions, and tools for data integration, analytics, and stream processing. Any of these may be on premises, in the cloud, or in hybrid combinations of the two. August 17, 2017 View Now

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Solution Gateways

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