Research & Resources

Research Reports


  • TDWI Advanced Analytics Maturity Model TDWI Advanced Analytics Maturity Model Guide Cover

    The TDWI Advanced Analytics Maturity Model is designed to help assess your current use of advanced analytics and how that compares to others. It provides a framework for companies to understand where they are in the journey, where they’ve been, and what they still need to do to succeed with technologies including predictive analytics and machine learning. Read Now

  • TDWI Self-Service Analytics Maturity Model

    The TDWI Self-Service Analytics Maturity Model Guide is designed to help you understand the phases of maturity in self-service analytics, interpret your assessment scores, and provide best practices to move you forward. Its insight and advice can help you quickly advance your self-service analytics initiatives to gain more value. 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



  • Supercharging Operational Analytics with Spark and Change Data Capture

    Organizations can gain competitive advantages if they can eliminate the latency that prevents them from getting a real-time view of operations. In many cases, operational reporting and analytics are still tied to traditional business intelligence, ETL, and data warehousing that can only deliver historical views of the data. Executives and managers have to wait – and the wait is getting longer and data volumes rise and analytics grow more complex. August 28, 2018 View Now

  • The Three Pillars of Data Governance: Compliance, Trust, and Transformation

    Many organizations initiate data governance programs because of pressing compliance issues that impact data usage. At the other end of the spectrum, some organizations begin by governing data that’s shared broadly through a community of consumers across the enterprise, each with their own perspective on what constitutes quality and usability. August 30, 2018 View Now

  • Improving Data Sharing Through Modernized Data Accessibility

    Organizations have struggled to easily provide access to sharable data assets ever since the early days of decision support systems. Traditional methods of data sharing are slow and cumbersome. Simple data sharing methods—such as emailing extracted files, opening up unsecured access to critical databases, or file exchanges via FTP or EDI—not only pose risks of inadvertent data exposure, they also fundamentally require manual steps for both the individual sending the data and the individual receiving the data. September 12, 2018 View Now

  • Modernizing Data Architecture With Streaming CDC

    Expanding analytics requirements have increased the appetite for massive data volumes. However, these data flows can create bottlenecks, preventing timely and modern analytics innovations such as machine learning. September 13, 2018 View Now

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