Download TDWI Infographics for illustrated snapshots of the latest pertinent findings and vital statistics from TDWI Research. Then access the associated Best Practices Reports for more in-depth information on how to take advantage of these trends in your organization.
October 11, 2019
Organizations are using IoT for a range of use cases, from sensing air quality to autonomous vehicles, designing factories of the future to disaster response. A recent TDWI survey sheds light on how enterprises are planning to use or currently using IoT, what challenges they face, and how often they need to visualize their ever-changing data from IoT sources.
November 1, 2019
This TDWI Best Practices Report examines how organizations using AI are making it work. It looks at how those exploring the technology are planning to implement it. Finally, it offers recommendations and best practices for successfully implementing AI in organizations.
September 20, 2019
No matter the vintage or sophistication of your organization’s data warehouse (DW), it probably needs to be modernized. This report provides a presentation of the many issues and categories of DW modernization, plus the strategies, methods, and enabling technologies that lead to success.
June 20, 2019
This TDWI Best Practices Report explains in detail what cloud data management (CDM) is and does so data professionals and their business counterparts can understand what CDM can do for them and how they might organize a successful program.
February 13, 2018
This TDWI Best Practices Report examines how organizations become data-driven, including patterns for building out infrastructure for managing data and driving analytics. It also examines the best practices of those organizations that are data-driven across three areas we believe are important: technology, analytics, and organization.
November 16, 2017
This TDWI Best Practices Report examines organizations’ experiences with and plans for machine learning, NLP, and AI, including technology plans as well as organizational strategies. It also looks at various advanced analytics challenges and how organizations are overcoming them. It examines the importance of new open source models and automated intelligence. Finally, it offers recommendations and best practices for successfully implementing more advanced analytics such as machine learning and AI in the organization.
September 7, 2017
Organizations need to accelerate the pace at which they can realize business value from data. Their focus is on improving “time to value,” which is the length of time it takes from the beginning of a project to the delivery of anticipated business value. In TDWI Best Practices Report: Accelerating the Path to Value with Business Intelligence and Analytics, we look at multiple factors impacting the ability of organizations to quickly derive greater value from data and analytics, including the organizational issues, practices, and development methods that are often just as important as keeping pace with technological innovation. Here are several of the key survey results.
June 14, 2017
The TDWI 2017 Salary, Roles, and Responsibilities Report captures key information from the people and teams who built and maintained business intelligence, analytics, and data management solutions during the 2016 calendar year.
May 8, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. In the recent TDWI Best Practices Report: Data Lakes – Purposes, Practices, Patterns, and Platforms, we define data lake types, discuss emerging best practices, and take a look at user trends and readiness for data lakes. Here are several of the key survey results.
February 17, 2017
Organizations increasingly value big data and data science and embrace more diverse data sources to gain insight about customers, increase efficiency, and generate new revenue streams. Developing an effective analytics and data science strategy, however, is often a struggle. In the recent TDWI Best Practices Report: Data Science and Big Data – Enterprise Paths to Success, we take a look at organizations’ experiences with and plans for big data and data science and offer best practices for successfully implementing big data programs. Here are several of the key survey results.