Contextualizing Data: Using Graph Technologies to Enhance AI Initiatives

Data proliferation should be a source of opportunity for organizations, but for many it has become a challenge. With such large volumes of data to sort through and convert into meaningful information, companies are frequently unable to take advantage of the insights at their fingertips. Instead, data is siloed or left without context, hindering the operations of other departments that depend on this information — whether that’s in the supply chain, the financial sector or other industries. To help contextualize this data, an increasing number of organizations are turning to graph technology like the Neo4j solution on Google Cloud. Not only can graph technology create a compelling visual representation of the data, but it is able to demonstrate the relationships between data points and provide a 360 degree understanding. This enriched perspective is then able to enhance existing machine learning and AI strategies, by supplying a more advanced set of patterns to work off of. More robust AI initiatives will ensure a higher level of performance and a greater level of security. In this webinar from Neo4j, Google Cloud and analyst firm ESG, industry experts will break down the key challenges posited by data proliferation and explore the different ways graph technology can strengthen operations across different industries. Tune in to learn more about: — Why context is critical to maximize the value of company data — Where organizations are most vulnerable to data inefficiencies and silos — How to achieve a holistic view of data — and how it will enhance your operations — And much more