The Knowledge Graph Cookbook

Why Read This Book?

The Knowledge Graph Cookbook will help you understand how knowledge graphs allow organizations to move from silo-controlled business intelligence based on traditional data warehouses to a holistic approach of augmented intelligence based on a semantic data fabric.

Augmented means that the Human-in-the-Loop (HITL) design principle is applied, in which various interest groups such as subject matter experts (SMEs) or business users engage in a continuous mutual dialogue with AI machines in their daily work, with the knowledge graph becoming the central interface between the various actors in such a system.

The results of this approach are:

• Higher data quality
• Reusability of data, e.g., to reduce the effort for data preparation
• Better interpretability of data and content
• Automatable processes for integrating and analyzing data
• Find relevant data, personalize and contextualize it, i.e. integrate it into concrete business processes
• Use of data for automatic reasoning

The Knowledge Graph Cookbook is a valuable resource for practitioners and decision-makers to take advantage of the many benefits of this methodology, especially the positive impact it has on the implementation of AI strategies.

More About This Book

Knowledge graphs are the ultimate linking engine for the management of enterprise data and drivers for new approaches in artificial intelligence. They are an extremely efficient approach to data governance, metadata management, and data enrichment, and are increasingly being used as data integration technology.

There are countless articles, slide decks and videos on the internet about knowledge graphs. Various standards, methods and technologies are available, but why isn’t there a recipe for how to create a knowledge graph, like there is for baking a pie?

The Knowledge Graph Cookbook explains why your organization should invest in the development of knowledge graphs, and most importantly, what recipes exist for developing and integrating them in an efficient, successful and sustainable way. After reading this book, you will be able to successfully tackle the chaos of contemporary enterprise data management.

By reading The Knowledge Graph Cookbook, you will also learn how contextualized and connected data helps companies achieve higher customer satisfaction or better service levels through holistic views of business objects, for example. You will also learn how knowledge graphs can be used to create reusable data sets that lead to better analytics and training for machine learning algorithms.

The Advantages of Knowledge Graphs

• Knowledge Graphs (KGs) solve well-known data and content management problems.
• They are the ultimate linking engine for enterprise data management.
• They automatically generate unified views of heterogeneous and initially unconnected data sources, such as Customer 360.
• They provide reusable data sets to be used by analytics platforms or to train machine learning algorithms.
• They help with the dismantling of data silos. A semantic data fabric is the basis for in-depth analysis.