Research & Resources

• TDWI Checklist Report | Six Keys to Maximizing Big Data Benefits and Project Success

  This TDWI checklist discusses six important issues that organizations should address to start big data projects off right and then manage them to achieve objectives faster and with less difficulty. more

• Best Practices Report | Multiplatform Data Architectures

  To capture distributed enterprise data, big data, and other new data assets—plus leverage them fully for business advantage—user organizations are expanding and integrating their portfolios of data platforms and tools to create what TDWI calls multiplatform data architectures (MDAs). Download this report to learn what MDAs are and do. more

• TDWI Checklist Report | AI for BI: Six Strategies for Augmenting Business Intelligence with AI and Machine Learning

  This TDWI checklist discusses six best practices for gaining greater value from AI for BI and self-service analytics. Our objective is to help organizations accomplish projects faster and provide relevant and accurate insights that users can trust. more

• TDWI Checklist Report | The Modern Data Hub

  This TDWI Checklist Report presents seven recommendations for successful data hub design and use. It should help you understand the new direction that the data hub has taken as well as what you should demand when evaluating products and deploying a modern data hub. more

• TDWI Checklist Report | Achieving High-Value Analytics with Data Virtualization

  This Checklist Report discusses six areas that are critical to achieving high-value, business-driven analytics and the role data virtualization plays in realizing success in these areas. more

• TDWI Checklist Report | The Cloud Data Integration Primer

  A number of newly mature trends are making cloud-based data integration platforms, technologies, and user best practices more relevant than ever. more

• TDWI Pulse Report | Developing Data Strategy for IoT

  This TDWI Pulse Report discusses some best practices for developing an IoT data strategy. It examines the organizational as well as the data and analytics aspects of such a strategy. This includes organizational alignment, understanding the unique nature of IoT, and other issues at play when managing and analyzing this “new” kind of data. more

• TDWI Checklist | Five Data Management and Analytics Best Practices for Becoming Data-Driven

  It can be difficult to create an organization that thrives on data and analytics. This TDWI Checklist Report discusses best practices to build a program and an infrastructure for becoming data-driven. more

• Best Practices Report | Practical Predictive Analytics

  TDWI research indicates that it is in the early mainstream stage of adoption. Yet, even as organizations continue to adopt predictive analytics, many are struggling to make it stick. The purpose of this report is to explore concrete best practices for building and deploying predictive models in organizations. more

• TDWI Checklist | Strategies for Improving Big Data Quality for BI and Analytics

  Organizations dependent on big data for a wide range of business decisions need data quality management that can improve the data so it is fit for each desired purpose. This TDWI Checklist Report offers six strategies for improving big data quality. more

• TDWI Checklist Report | The Automation and Optimization of Advanced Analytics Based on Machine Learning

  Machine learning is being used today to solve well-bounded tasks such as classification and clustering. Note that a machine learning algorithm learns from so-called training data during development; it also learns continuously from real-world data during deployment so the algorithm can improve its model with experience. This report will drill into the data, tool, and platform requirements for machine learning with a focus on automating and optimizing ML's development environment, production systems, voracious appetite for data, and actionable output. more