In a world that is increasingly dominated by data, data intelligence plays a central role for decision-makers. It enables companies to gain meaningful insights from huge amounts of data and make well-founded decisions. Big data and smart data are two key concepts that are frequently discussed in this context. While big data focuses on the quantity of data, smart data aims to increase the quality and relevance of information in order to gain useful insights[1][2].
Big data: the challenge of large amounts of data
Big data describes large, often unstructured volumes of data that are characterised by their size, variety and speed. This data comes from various sources, such as transaction data in the financial sector or sensor data from Industry 4.0[1][11]. The challenge, however, is that big data is often not directly usable, as it first has to be processed in order to provide usable information[5].
One example of this is the automotive industry, which relies heavily on vehicle data. Companies need to analyse data from vehicle systems and sensors in order to support predictive maintenance and detect failures at an early stage[1].
Smart data: the key to valuable insights
Smart data, on the other hand, is high-quality, context-rich and action-relevant information that is extracted from big data. This data is targeted and helps companies make practical and valuable use of it to make informed decisions[3][4]. For example, companies can develop targeted marketing campaigns by analysing relevant data on purchasing behaviour or customer preferences[2].
Another example is the healthcare sector, where smart data is used to develop more personalised treatment approaches. By analysing patient records and laboratory results, doctors can design better treatment courses and reduce costs[1].
Application of smart data in practice
Smart data is widely used in various sectors to optimise business processes and gain competitive advantages. In industry, sensors are used to monitor machine conditions and prevent breakdowns through predictive maintenance[7]. In marketing, smart data enables the development of personalised advertising campaigns that are tailored to specific customer needs[8].
BEST PRACTICE at the customer (name hidden due to NDA contract) is to use smart data to improve customer loyalty. By analysing customer data, companies can develop individualised offers that better meet customer needs and increase loyalty.
Data intelligence: the enabler for well-founded decisions
By combining big data and smart data, companies can optimise the use of data intelligence. This combines the volume of data with the added value of smart information to provide decision-makers with a supportive basis for well-founded decisions[1]. Companies thus benefit from more efficient business processes, improved marketing strategies and increased efficiency through the targeted use of data[8].
My analysis
Data intelligence is crucial for companies that want to remain competitive in a data-driven market. Through the targeted use of big data and the transformation to smart data, companies can make informed decisions and stand out from the competition. The future of data analytics lies in the ability to transform complex data sets into actionable insights to make business processes more efficient.
Further links from the text above:
For more information on data intelligence and the use of big data and smart data for companies, please visit the following sources:
Data intelligence: big data and smart data for decision-makers
Big data vs. smart data: is more always better?
Smart data: How intelligent data is shaping our future
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