Knowledge Graphs in Action
Padma Purushothaman
Driving Data Governance with AI & BI @ S&P Global | Ex-Jana Bank, PayPal, Target, FICO|
Knowledge graphs could be used in organizations to ??unravel the intricacies of their own business processes, relationships, supply chains, etc. as a business supporting/enabling technology. ??Enterprise Knowledge Graphs may also provide great value when being used to support the daily operations of a business and, in that context, the enterprise is their end user. This role is known as the Supporting Role. Wherever there is a ??vast amount of data with complex interconnections and valuable insights to be extracted, there’s a use-case for a Knowledge Graph?
Examples of Knowledge Graphs in action:
??Google has been using it for a long time. Google’s Knowledge Graph is being used to power better search results, based on answers that reflect context. The 500+ billion facts contained in the Knowledge Graph is also used by voice assistants like Google Assistant to answer queries.
??LinkedIn uses their own Knowledge Graph to discover data insights that lead business decisions and find new ways to increase member engagement.
??Social platforms like Facebook are based on a social graph structure, formally integrated into their own Knowledge Graph, which they call the Entities Graph.
??NASA uses Knowledge Graphs to map out their Air Traffic and Aviation data, manage systems engineering, and to find the best talent for their skill-specific roles.
??Amazon uses a product graph to categorize products on its retail website and to make better product suggestions to customers to fulfill the role of Disruption Enabler.
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??AirBnb uses Knowledge Graph to enhance its customer experience by integrating and conducting computer reasoning on data coming from different data sources
??Uber uses their Knowledge Graphs to optimize their ride-sharing platform, as well as powering Uber Eats’ food recommendations.
??Siri, Alexa, etc. – Virtual assistants can provide meaningful answers to requests because they are powered by Knowledge Graphs and the semantic models they’re based on. People are using Amazon’s Alexa, ordering food through Uber Eats, or booking a listing on Airbnb, all powered by Knowledge Graphs.
??PayPal uses a Knowledge Graph to analyze financial transactions.
??Bosch uses a Knowledge Graph to analyze sensor data from its manufacturing processes.
Creating a knowledge graph can be a ??time-consuming task, but it is seen as the ??only option when highly specialized systems, data types, and architectures are involved. As many technology companies already have the dedicated staff capable of creating and delivering a proprietary solution, a ??custom-made Knowledge Graph is frequently the result. But this takes a lot of time and effort.
I resolve employee promotion grievances through strategic skill alignment and engagement, enhancing stability and reducing attrition. My approach fosters a high-performance culture, making Best Place to Work Culture.
1 年I cant be further in detailed explanation of knowledge graph, its varied uses in various fields. It is imperative to say that knowledge graph helps in analyzing various trends in behaviours in various businesses though it consumes a lot of time Padma Purushothaman
Organization Transformation and Innovation Lead Business Process Agility | Compliance |Automation | Data Modeling | Auto ML | SAFe 5.0 | Cloud Architecture | DevOps I Data Science | Analytics | Market Data
1 年Thanks for Great insight! "Knowledge Graphs serve as the cornerstone of modern organizations, unraveling the intricacies of complex business processes and supply chains. They empower industry leaders such as Google and LinkedIn by furnishing them with vast reservoirs of data-driven insights, bolstering decision-making prowess and elevating user engagement. Notably, giants like NASA, Amazon, and PayPal harness the power of Knowledge Graphs to meet their distinctive needs, spanning aviation data management, product classification, and financial transactions. Crafting these intricate Knowledge Graphs may demand time and resources, particularly when dealing with specialized data ecosystems. However, the substantial dividends reaped from these tailor-made knowledge repositories render them indispensable assets for forward-thinking enterprises in today's data-driven landscape."