{"id":351188,"date":"2024-10-07T04:45:29","date_gmt":"2024-10-07T02:45:29","guid":{"rendered":"https:\/\/sauldie.org\/de\/datenintelligenz-big-data-smart-data-unternehmen-17\/"},"modified":"2024-10-07T04:45:29","modified_gmt":"2024-10-07T02:45:29","slug":"data-intelligence-big-data-smart-data-companies-17","status":"publish","type":"post","link":"https:\/\/risawave.org\/en\/datenintelligenz-big-data-smart-data-unternehmen-17\/","title":{"rendered":"Unleash data intelligence: Mastering Big Data & Smart Data"},"content":{"rendered":"

In the digital age, data intelligence is gaining increasing importance. Companies face the challenge of extracting real added value from vast amounts of data. Data intelligence describes the ability to generate precise and contextually relevant smart data from the flood of big data. This is not just about the sheer volume, but particularly about the quality and expressiveness of the information. This intelligently processed data supports companies in making well-founded decisions and developing innovative solutions.<\/p>\n

Big data and smart data: the crucial difference<\/h2>\n

Big data refers to large, heterogeneous and often unstructured volumes of data. This raw information comes from numerous sources such as IoT sensors, transactions or user interactions. Without analysis, however, it offers little direct benefit. Smart data, on the other hand, is high-quality, filtered and contextualised information that is extracted from big data. It is precise, relevant and enables fast and reliable decisions.<\/p>\n

An example from the automotive industry: a manufacturer collects data from vehicles and customers. Through intelligent analysis, Smart Data is created, which supports product development and increases customer satisfaction. Another example from telecommunications: a provider analyses usage data to optimise networks. The raw data is confusing, but through targeted filtering and AI-supported processes, Smart Data is created that increases performance.<\/p>\n

Data intelligence: From a mountain of data to valuable knowledge<\/h2>\n

Data intelligence is the key to creating real added value from big data. It helps decision-makers to act more efficiently, securely and with foresight. In numerous industries, the targeted use of smart data facilitates strategic decisions and operational processes.<\/p>\n

In the energy sector, for example, vast amounts of data from different sources are brought together \u2013 weather data, consumption measurements, market prices. Here, data intelligence shows the best time for energy procurement or grid utilisation. A trading company can filter data from millions of customer interactions that provide insights into the purchasing behaviour of specific demographic groups. This leads to targeted marketing campaigns with a higher chance of success.<\/p>\n

Another example from the healthcare sector: hospitals use data intelligence to optimise patient flow and deploy resources more efficiently. Smart data, which improves the quality of care, is generated by analysing treatment data, waiting times, and capacity utilisation.<\/p>\n

Practical steps to data intelligence<\/h2>\n

To successfully implement data intelligence, businesses should follow these steps:<\/p>\n