In today's data-driven world, the concepts of data modeling and data analysis are playing increasingly vital roles in helping companies manage their vast assets of data efficiently and effectively.

Learn about the key principles and techniques for using data modeling to understand, analyze, and communicate your data, and to support data-driven decision-making.

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis ...

Data modeling, data science, and data analytics all go hand-in-hand—you need a quality data model to get the most impactful data analytics for effectual business intelligence that'll inform your ...

While data modeling focuses on the structure and design of data, data analysis dives into the content to extract meaningful insights. Their collaborative relationship is pivotal for organizations ...

Learn how data modeling methods, tools, and best practices are changing in the age of Big Data and Analytics, and what it means for BI professionals and data consumers.

Data analytics is a discipline focused on extracting insights from data, including the analysis, collection, organization, and storage of data, as well as the tools and techniques to do so.

Predictive modeling is a statistical analysis of data used to generate future scenarios for organizations and companies. It can be used in any industry, enterprise, or endeavor in which data is ...

Data modeling, data science, and data analytics all go hand-in-hand—you need a quality data model to get the most impactful data analytics for effectual business intelligence that'll inform your ...