Connection Analytics provides a new way of looking at people, products, physical phenomena, or events. It provides insights by dissecting the types of relationships between entities to determine causation and can be used for generating predictive intelligence based on the patterns of interactions. Connection Analytics can address queries such as identifying influencers, the groups that they influence, and where promotions or other forms of marketing are best directed. It can be utilized for product affinity analysis by taking a bottom up look at how the decisions to buy different items are linked. Likewise, this approach can help analyze networks by patterns of activity, and fraud and money laundering through the actions (rather than identities) of involved actors. It can help segment customers based on behavior patterns like past purchase behavior or reviews vs. traditional segmentation techniques like income & demographics. Graph analytics is one of the most promising approaches to performing Connection Analytics. Teradata is the first analytics data platform provider to make graph computing accessible to the existing base of data scientists, database developers and business analysts by introducing a SQL-friendly approach. Underneath the hood, Teradata Aster is using a compute approach that allows the data to leverage the power and performance of massively parallel analytic processing engines and pre-built algorithms. Introducing Connection Analytics