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Data Architecture Principles

Data Architecture best practices have evolved over time as data sources and data usage have expanded exponentially. Here are a few key modern Data Architecture principles for today's data-driven marketplace

Machine Learning vs. AI

Exploring the capabilities and differences in Machine Learning vs. AI.

The Right Tools to Analyze Data Require the Right Data Warehouse

Learn why it takes more than the right tools to analyze data. You also need a scalable, flexible cloud data warehouse.

Data Management Products

Data management products enable security and efficiency for data-forward organizations.

Cloud Data Architectures

Cloud data architectures contain the rule and models that define how data is collected, stored, used and managed in the cloud.

Big Data Architectures

Big data architectures act as the design blueprint for big data infrastructure and solutions. and created by data architects before a big data solution is deployed.

Analyze Big Data More Efficiently

The need to analyze Big Data more efficiently becomes increasingly more significant as the volume of data grows. Additionally, multiple data sources and users create data storage challenges.

Analytics for Games

Analytics for games has changed dramatically over the past 15 years. The advent of mobile gaming platforms has produced a flood of new data points and the need to update, personalize, and upsell the gaming experience.

Analytics on Big Data: Why It Matters

Analytics on Big Data is important to every organization. Find out how companies unlock the power of their big data with a data warehouse built for the cloud.