Building a Centralised Knowledge Graph to Power Your Analytics
As graph analytics is quickly becoming a core competency of many analytics departments, architecting a network graph to function in production and be reused by multiple projects is key.
Often networks graphs are batch built without much thought to node disambiguation or moving into production. Most of the focus being on generating insights from the graph but not necessarily in building the best graph.
As we’ve heard so many times before, preparing your data for analytics is key to gaining the best insights. So, how can you use analytics in building better graphs?
This talk will outline and discuss what is needed to build a truly reusable, reliable, and updatable graph of your data, knowledge, and features.
About Alex
Alex has spent most of her career as a machine learning engineer and recently founded Knights Analytics to enable the companies she works with to easily combine siloed data into a centralised knowledge graph for analytics. Alex has 10 years of experience in defining and delivering high-impact graph analytics and machine learning solutions for a wide variety of multinational financial and retail institutions, with a focus on fraud, money laundering and organised crime. During her career Alex has specialised in building and productionising network graphs which enable the extraction of features for analytics and modelling, whilst also powering front end applications.
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