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TDWI Upside - Where Data Means Business

Graph Databases for Analytics (Part 4 of 4): Addressing Performance Challenges

Once you put graph databases into practice, you may find performance does not scale at large volumes. We explain how you can improve the performance of your graph applications.

Graph Databases for Analytics (Part 3 of 4): The Basics of Graph Structure and Analytics

If you have an application for graph databases, what does the graph structure actually look like? We go further in-depth into the parts of a graph database and the purposes of common graph analytics.

Graph Databases for Analytics (Part 2 of 4): Practical Applications

Is a graph database the solution to your business problem? In this article we'll explore the common characteristics of practical applications for graph databases.

Graph Databases for Analytics (Part 1 of 4): What’s So Great about Graphs?

What makes now the right time to learn about graph databases? When the connections between data elements are as important as the elements themselves, you need a new way to handle your data.

Analysis: Aurora Is Amazon's Answer for Forgotten DBMS Users

Amazon's Aurora may close the gap between spreadsheets and full-blown RDBMSs for large enterprises.

Tunable Consistency in Cassandra NoSQL

Tunable consistency is one of the many points of differentiation between SQL and NoSQL databases. This article explains this important parameter and the tunable consistency options Cassandra provides.

Considering a Cloud-based EDW: Questions You Must Ask

Enterprise data warehousing in the cloud represents a major change in thinking as well as in architecture. Addressing these critical questions can help you judge the practical value of cloud EDW for your enterprise.

High-Frequency Decision Making: Embracing a Competitive Advantage

Converged data platforms allow enterprises to make decisions faster, even in real time, transforming organizations across a wide variety of industries.

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