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.
As the importance of self-service solutions for BI, analytics, and data preparation continues to grow, the emphasis is no longer only on centralized, full-time data professionals and their institutional knowledge. We also must find a way to support the business’ needs with better-documented data assets. For many organizations, this is a data catalog.
For organizations struggling to modernize their DM efforts, the intelligent integration hub provides a flexible and scalable foundation. This TDWI report examines the attributes and use cases of the intelligent integration hub.
This Checklist Report examines how seven industries are using analytics to drive value. These industries include finance, insurance, retail, healthcare,manufacturing, utilities, and technology/software/Internet.
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.
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