This first in a new series of reports offers focused research and analysis of trending analytics, business intelligence, and
data management issues facing organizations. TDWI Pulse Reports are designed to educate technical and business professionals and aid them in developing strategies for improvement.
March 29, 2018
This TDWI Best Practices Report explores the new opportunities for AI, machine learning, and natural language processing presented by innovations in computing power and algorithmic efficiency.
September 28, 2017
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
Existing enterprise infrastructures are engineered in a way that complicates some types of data provisioning. In this checklist, we will consider the benefits of a platform-based approach to DataOps that addresses some of these complexities.
This TDWI Checklist Report discusses best practices for data engineering and management to support machine learning with a focus on collecting, cleansing, transforming, and governing new types of data for analysis.
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.
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.
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.
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.
A number of newly mature trends are making cloud-based data integration platforms, technologies, and user best practices more relevant than ever.
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