{"id":349176,"date":"2025-10-29T14:03:03","date_gmt":"2025-10-29T13:03:03","guid":{"rendered":"https:\/\/sauldie.org\/de\/datenintelligenz-gezielte-datenverwertung\/"},"modified":"2025-11-17T17:31:39","modified_gmt":"2025-11-17T16:31:39","slug":"data-intelligence-targeted-data-utilisation","status":"publish","type":"post","link":"https:\/\/sauldie.org\/en\/data-intelligence-targeted-data-utilisation\/","title":{"rendered":"Unleashing data intelligence: KIROI 3, Big Data & Smart Data"},"content":{"rendered":"

Data intelligence as the key to targeted data utilisation<\/h2>\n

Data intelligence is becoming increasingly important in today's business world. Companies are confronted with a flood of data, but the sheer volume of data alone does not guarantee value. Rather, it depends on how companies analyse and use this data intelligently. Data intelligence provides crucial support here by paving the way from mere data collection to concrete, usable insights. This speeds up decision-making processes and reduces risks.<\/p>\n

Examples from various industries illustrate how data intelligence can help. In retail, companies use special algorithms to analyse purchasing habits in order to create personalised offers. In healthcare, intelligent data analyses improve diagnostic reliability through automated image evaluation. In logistics, too, data intelligence enables the optimisation of delivery routes and helps to reduce costs.<\/p>\n

Data intelligence in the interplay of big data and smart data<\/h2>\n

The difference between big data and smart data is central to the successful development of data intelligence. Big data describes large quantities of different raw data that is often unstructured and complex. Although it forms the basis, it harbours the challenge of being used economically. This is where smart data comes into play: it is extracted from big data using intelligent algorithms and contains high-quality, targeted and contextualised information. <\/p>\n

Companies in the financial sector use smart data to better assess risks in real time. Media streaming portals optimise recommendations through the targeted analysis of relevant viewer data. Car manufacturers can use smart data to make more precise forecasts for maintenance and production.<\/p>\n

Another example is the use of KIROI 3, a platform that combines big data and smart data to make data intelligence a reality. It supports companies in quickly and efficiently extracting relevant information from the flood of data and utilising it for operational and strategic decisions.<\/p>\n

Practical support through transruption coaching<\/h3>\n

Many companies already have extensive data sets, but fail to implement a customised data strategy. Transruption coaching helps here by supporting individual data intelligence projects and helping to implement the right technologies.<\/p>\n

In the field of medical technology, the integration of AI methods for image analysis was realised through such support. The result is more precise diagnoses and more efficient work processes. For a manufacturing company, focussing on smart data led to a reduction in production errors and increased adherence to deadlines.<\/p>\n

BEST PRACTICE with one customer (name hidden due to NDA contract)<\/b> This online retailer used data intelligence to analyse customer data in depth. This resulted in targeted cross-selling campaigns that significantly increased sales and improved customer loyalty at the same time.<\/i><\/p>\n

Tips for the effective use of data intelligence<\/h2>\n

To use data intelligence successfully, companies should consider the following steps:<\/p>\n