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.
June 29, 2018
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
Businesses can only seize new data-driven opportunities if they recognize sensitive data and handle it responsibly. This report focuses on how targeted improvements to specific data management best practices and technology can contribute significantly to your success with GDPR compliance, as well as data governance and data-driven programs in general.
March 6, 2018
The gender gap in wages saw a dramatic narrowing in 2015, as women’s average salary rose by 1 percent and men’s dropped by 4 percent. Read more in the 2016 TDWI Salary, Roles, and Responsibilities Report.
Download this report for recommendations and best practices for successfully operationalizing analytics in your organization to derive business value.
This Checklist discusses seven best practices for implementing data warehouse automation within an agile development framework.
This Checklist discusses seven key considerations to help organizations focus their evaluation and develop a strategy for gaining value from open source technologies to support faster, more powerful, and more flexible analytics.
This TDWI Checklist Report drills into seven recommendations and discusses many of the new vendor product types, their functionality, and user best practices that can contribute to data integration modernization. It also presents the business case and technology strengths of each recommendation.
To help the reader understand the ongoing evolution of data management—in response to new requirements around big data and analytics—this report provides a checklist of data management practice areas that are most affected. In addition, the report relates new practices to existing ones, indicating when to use which one.
This Checklist Report discusses what your enterprise should consider before diving into a data lake project, no matter if it’s your first or second or even third major data lake project. Presumably, adherence to these principles will become second nature to the data lake team and they will even improve upon them at some point.
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