Smart Data: Unlocking the value of your data assets.

Over the last decade, big data has steadily gained importance. Companies and government organizations have invested heavily in data sources and poured more and more information into their data lakes. And today, data is key in every successful organization. It drives decisions, empowers actions, boosts strategy. But new data does not necessarily equal new intelligence. What you need is smart data.

A new era of value over quantity

Big data is messy. Available in staggering volume, it is distributed, diverse, and out of context in most organizations and thus often difficult to use to its full potential. Most data sources need cleansing, verifying and standardizing. This means that expensive, highly-educated employees often spend around 80% of their time gathering, tidying up and contextualizing data. As a consequence, they have less time to actually leverage these data assets, say, by using consolidated data to inform the improvement process. For the promises of the current AI wave to be fulfilled, we need to say goodbye to the era of “more data is better” – it is time for a new era of smart data. Smart data is data that is based on standards and explicit semantics. It is both machine- and human-interpretable, linkable, contextualized, and reusable. In short: smart data is valuable data, making this new era rich in possibility. Using smart data, models can find and use the most impactful data faster, learning more accurately how the world works and making better decisions. Leaving behind the days of guessing and moving towards truly evidence-based action.

Ontologies – the key to smart data

To generate smart data, a knowledge representation in the form of a knowledge graph or ontology is essential. Ontologies serve as smart data management systems and help businesses and organizations unlock the value of data assets to drive flexible, agile solutions that fit their needs – boosting digital transformation by translating data into real knowledge. And these solutions are increasingly reliant on AI, where smart data is indispensable. Leading experts agree that the success of complex AI-based processes depends crucially on transforming big data into smart data using knowledge representations. No matter how well a solution is marketed, if it is not based on a knowledge representation that can generate smart data, it will be disappointing at best. Whether parsing, matching, classifying, or any other sophisticated solution based on AI, the key to high performance and great results is feeding the machine with real knowledge in readable form, i.e., with smart data from an ontology.

Over the past decade, our domain-specialized multilingual curation team has developed and continuously extended what has become the worldwide most comprehensive multilingual knowledge representation in the field of occupation-related data: our job and skills ontology JANZZon!. Hand-curated to ensure the highest quality standards of the recruiting and employment services industry, this architectural solution generates unique conceptual relationships and facilitates previously unknown intelligent possibilities by adding context to data when first created. JANZZ has done the hard work so it is simple for you: JANZZon! makes occupational data findable, accessible, interoperable, reusable and fast, thus delivering direct benefits by reducing investigation, cleanup, contextualization and analysis timelines. It turns messy occupation-related big data into valuable smart data.

Discover the full potential of your data

Based on this, JANZZ has created a variety of intuitive applications for search and match, parsing, analysis and data interaction, driven by JANZZon! at the heart of our technologies. These applications, as well as JANZZon! itself empower end users to unleash the full potential of their data, discovering important relations that were not visible before, and extracting meaningful and actionable insights easily and effectively.

The ontology can be accessed through the JANZZjobsAPI by anyone who does not want to simply accumulate data but actually utilize it in a smart way.