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Do You Need a Graph Database? (Online Seminar)

‍We are in an era of unprecedented innovation in databases. Data-intensive companies are grappling with whether the many new options — NoSQL, Key-Value, Document, Column Family, Column-Oriented — are appropriate for them. The commercial success of Facebook and LinkedIn makes graph databases a hot area of investigation. Unlike many new databases, they are not a variation on or a simplification of relational databases. Instead they require new ways of thinking and modeling data. In return they can answer truly novel questions.

A Fraud Series - Part Three: Types of Fraud Identified by a Detection System

It is important to note that as time goes on, fraudsters will continue to adapt to rules and regulations that attempt to prevent them from committing fraud. While supervised detection systems can detect certain types of fraud well, oftentimes analysts don’t immediately know whether new patterns are indicative of fraud or not. This is why it is important to use an unsupervised system that can learn not only from existing patterns, but from new patterns as well. 

Alternative Investments: Part 2

This post explores Alternative Investments: Part 2