Data intelligence is a decisive factor for companies that want to utilise their data efficiently. It helps companies to transform data into valuable information that can support business decisions and promote success. Big data and smart data play a central role in this context, as they offer different approaches to collecting and analysing data. Big data describes large and complex amounts of data that are often not structured, while smart data focuses on the quality and usefulness of the data by providing relevant information that is essential for business decisions.
Big data: the basis of data intelligence
Big data stands for a huge amount of data that is generated every day. This data can be both structured and unstructured and includes text, images and videos, for example[8][9]. Big data is characterised by the four Vs: Volume (quantity), Variety (diversity), Velocity (speed) and Veracity (credibility)[1][3]. Companies use big data to understand customer behaviour patterns or to optimise production processes.
An example from the retail sector shows how big data is used to increase customer satisfaction: A retail company analysed data on customer behaviour patterns in the online shop in order to create personalised recommendations. These measures led to a significant increase in sales and customer satisfaction.
Opportunities and challenges of big data
Big data offers many opportunities, but also harbours challenges. On the one hand, it enables deeper insights into customer behaviour and processes; on the other hand, it requires extensive resources to process and store the gigantic amounts of data[8]. Processing speed and quality are decisive factors in obtaining valuable information.
Data intelligence and smart data: the key to efficiency
Smart data, on the other hand, is the specifically processed and analysed version of big data that provides essential information for business decisions. It is often considered the "cleaned" version of big data, as it is free of errors and irrelevant information[1][3]. Smart data focuses on quality and value, making it easier to achieve business goals.
In Industry 4.0, smart sensors play an important role in the generation of smart data. These sensors capture precise data that can be immediately analysed and integrated into production to ensure more efficient processes[7].
BEST PRACTICE at the customer (name hidden due to NDA contract)An industrial company used smart data to increase production efficiency. By analysing sensor data, predictive maintenance applications were developed that prevented sudden machine failures and significantly reduced downtime.
Benefits of smart data
Smart data offers several advantages: It is more accurate, cost-efficient and supports better decisions as it contains only relevant and reliable information[3][5]. Application areas include customer journey analytics and voice of the customer, which help companies to improve customer satisfaction and strengthen their market reputation[7].
Practical implementation of data intelligence
In order to implement data intelligence effectively, it is crucial to use the right tools and strategies. This starts with the integration of big data tools for data collection and storage. Data should then be analysed using targeted algorithms and machine learning techniques to generate smart data[6].
Another example from the financial sector: a banking institution used data analyses to identify fraudulent activities and take preventative measures. By combining big data and advanced analysis techniques, the number of fraudulent transactions was significantly reduced.
My analysis
Overall, the use of data intelligence is crucial for companies that want to utilise their data efficiently and strategically. By combining big data and smart data, companies can improve their decision-making, optimise processes and ultimately increase business success. Expert guidance in this area can help companies to develop the best possible strategies and utilise data to its full potential.
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For more information you can visit the following links:
Differences between big data and smart data
Big data definition and advantages
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