RESEARCH & RESOURCES

Research & Resources

Research Reports

  • Best Practices Report | Data Lakes: Purposes, Practices, Patterns, and Platforms BPR Data Lakes cover

    One of the more popular subjects in data modernization today is the addition of data lakes to many different ecosystems. This report defines data lake types and discusses emerging best practices, enabling technologies, and real-world use cases. March 29, 2017 Read Now

  • Best Practices Report | Data Science and Big Data: Enterprise Paths to Success

    Big data and data science can provide a significant path to value for organizations. Download this report for organizations’ experiences with and plans for big data and data science including both technology plans and organizational strategies. December 21, 2016 Read Now

  • TDWI Checklist Report | Data Modernization for the Telecommunications Industry

    Now is the time for the telecommunications industry to devise a strategy for modernization of the data management environment in ways that streamline the end-to-end processes for ingesting, transforming, loading, reporting, delivering, and analyzing data. This Checklist Report describes a vision for the future that includes using an architecture that leverages a hybrid environment combining traditional enterprise data warehouse (EDW) techniques with the ability to deploy augmentation tactics on big data environments, such as those built using the Hadoop ecosystem. December 2, 2016 Read Now

  • TDWI Checklist Report | Emerging Best Practices for Data Lakes

    Forward-looking businesses need discovery-oriented analytics, but discovery analytics tends to work best with large volumes of raw source data. The data lake enables analytics with big data and other diverse sources. This TDWI Checklist Report discusses many of the emerging best practices for data lakes. December 1, 2016 Read Now

Assessments

  • 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

Publications

  • TDWI Checklist Report | New Strategies for Visual Big Data Analytics Checklist Visual Big Data Analytics Cover

    Organizations need a strategy for a modern data platform that can support users who need more than traditional BI and OLAP provide but don’t have the specialized skills of advanced data scientists. This Checklist focuses on six key considerations for modern data platforms that enable more users to benefit from big data through easier to use, visual big data analytics. April 17, 2017 Read Now

  • TDWI Checklist Report | Machine Learning for Business: Eight Best Practices to Get Started

    In a recent TDWI survey, 51 percent of respondents said that enhancing business analysts’ skills was one of their top two strategies for growing their data science competencies. How do businesses get started with machine learning? This Checklist defines machine learning and discusses best practices for the business as it takes the next step on its analytics journey toward using machine learning. March 29, 2017 Read Now

  • TDWI Checklist Report | Rethinking Enterprise BI to Fit a Self-Service World

    Business intelligence (BI) is becoming increasingly democratized, and realizing value from BI tools is no longer limited to an exclusive group with technical expertise. This Checklist Report focuses on how organizations can revise and revitalize enterprise BI in the age of self-service technology. March 15, 2017 Read Now

  • TDWI Checklist Report | Six Strategies for Accelerating ROI from Self-Service BI and Visual Analytics

    Organizations can unleash the potential of business intelligence (BI) and analytics by empowering users with greater freedom and flexibility in how they work with data. However, it is critical for organizations to improve ROI. This TDWI Checklist covers six strategic issues to address to realize higher ROI with BI and analytics. In some cases, our recommendations focus on traditionally enterprise-level concerns, such as governance. In others, we look at overcoming challenges to enable more users to meet dynamic business demands. March 1, 2017 Read Now

Webinars

  • End Your Data Struggle: How to Seamlessly Analyze Disparate Data

    Many organizations today are struggling to get value from their data and advanced analytics initiatives. The struggle begins with data diversity, as organizations are trying to support new apps, customer channels, sensors, and social media outlets. Each source may have its own data structure, quality, and container (in the form of files, documents, messages). The struggle is exacerbated by the exploding volume of data that must be captured, processed, stored, and delivered to the right users in a state that is fit for their own individual needs. April 25, 2017 View Now

  • Database Strategies for Modern BI and Analytics

    The data universe has changed. Big data, cloud computing, and open source have dramatically expanded the number of data warehousing offerings available to today’s businesses. An increasing number of companies are implementing self-service business intelligence (BI) and visual analytics tools to access and make sense of all of the new and diverse sources of data their teams are consuming. Data literacy is changing equally fast as an increasing number of “data consumers” want to interact with data on their own rather than through IT. April 26, 2017 View Now

  • Between a Rock and a Hard Place: How to Modernize Legacy Middleware for an Evolving, Data-driven World

    In support of daily operations, many organizations depend heavily on systems for enterprise application integration (EAI), enterprise service bus (ESB), and other approaches to middleware. Yet, these infrastructures are today legacy technologies that predate the rise of big data and unstructured data, as well as modern sources and targets for integration, such machines, devices, clouds, social media, and the Internet of Things (IoT). Furthermore, many middleware vendor tools are still optimized for the on-premises ERP-dominated applications world of twenty years ago; others are in legacy mode, with no future upgrades coming. May 3, 2017 View Now

  • Data Management for Big Data, Hadoop, and Data Lakes

    A perfect storm of data management trends is converging. First, organizations across many industries are experiencing the big data phenomenon, which forces them to capture and leverage data from new sources, in structures and velocities that are new to them, in unprecedented volumes. Second, technical users are scrambling to learn new data platforms like Hadoop and their evolving best practices. Third, the data lake arose suddenly in 2016 as the preferred approach to managing very large repositories of raw source data. Fourth, business managers have attained a new level of sophistication in their use big data for business value and organizational advantage. May 10, 2017 View Now

White Papers

Best Practices Awards

TDWI’s Best Practices Awards program is designed to identify and honor companies and other organizations that have demonstrated best practices in developing, deploying, and maintaining solutions.

Solution Gateways

  • SAP

    SAP

    5 Reports to Help you Prepare for the Future of Analytics

  • informatica

    Informatica

    Data Management for Next-Generation Analytics

Product Directory

Take advantage of the wealth of insight and information available from industry experts in TDWI's Online Directory. Access a network of highly qualified industry-specific suppliers.