Behind the Scenes: Unveiling Cymonix's Approach to Building Robust Knowledge Graphs Inside CymonixIQ⁺

In the dynamic realm of data intelligence, Cymonix stands at the forefront, revolutionizing the landscape with their innovative knowledge graph solutions embedded within CymonixIQ+. In this exclusive peek behind the scenes, we embark on a journey through Cymonix’s development process, uncovering the methodologies and cutting-edge technologies that form the backbone of their robust knowledge graph solutions. 

As the technological landscape evolves, shifting its focus from applications to data, the potential for organizations to transform into data-informed enterprises is substantial. The accumulation of data not only enhances products and services but also acts as a magnet for new customers while deepening relationships with existing ones. However, despite more than two decades of collecting, storing, and analyzing vast amounts of information, the question arises: are organizations truly reaping the expected value from their substantial investments in Big Data? 

According to an insightful study by Accenture Research, the answer appears to be negative. The study indicates that a significant number of firms still grapple with fully unlocking the potential of data. Merely 32 percent of companies reported tangible and measurable value derived from their data investments, and an even smaller fraction—27 percent—stated that data and analytics projects yield insights and recommendations that are highly actionable. 

Further compounding this challenge, Forrester research reveals that a substantial portion, ranging between 60 percent and 73 percent, of all data within an enterprise remains unused for analytics purposes. As an illustration, Forrester Consulting’s study, “The Future of Retail Revenues Must be Data Led,” highlights that a staggering 85% of grocery retailers lack the capabilities, technology, and expertise to leverage insights for monetizing their data and enhancing customer experiences. 

To address the issue of data proliferation, especially with semi or unstructured data, and to overcome the limitations of rigid data management approaches, McKinsey & Company proposes a strategic shift. They advocate for organizations to invest in flexible, integrated data stores containing readily usable data. This approach includes the utilization of “flexible ontologies and knowledge graphs to map the relationship between different classes of data and data points.” By doing so, organizations can accelerate the development of data products such as customer 360 profiles and enable more sophisticated analytics. This strategic pivot holds the promise of not only harnessing the power of accumulated data but also transforming it into actionable insights that drive business success.