When we design and develop data management solutions, one of the first and most important steps is to catalog the data that will be captured, managed, analyzed, and shared. This TDWI report will examine the many components and functions of a modern enterprise data cataloging facility.
Open source has become popular, especially for big data and data science, because it is a low-cost source community for innovation, which appeals to many data scientists and analytics application developers— especially those who like to code.This TDWI Checklist Report discusses some best practices for evaluating open source analytics.
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.
Predictive analytics is on the verge of widespread adoption. In this report, Fern Halper provides an overview of the state of the predictive analytics market, as well as an overview of the key product offerings helping organizations realize value from predictive analytics.
This TDWI Best Practices Report focuses on current experiences with realizing value from BI and analytics and how organizations can accelerate the path to higher value.
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.
Average bonuses soared 19.8 percent in 2016, to $17,210. Read more in the 2017 TDWI Salary, Roles, and Responsibilities Report.
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