In a world in which the amount of available data is constantly growing, the concept of Data intelligence is becoming increasingly important. Companies are faced with the task of not simply collecting large amounts of data, but analysing and implementing it with a clear focus on quality and relevance. This is the only way to turn confusing big data into truly usable smart data that can serve as the basis for smart, fact-based decisions.
Data intelligence - quality over quantity
The term big data refers to huge, unstructured volumes of data from a wide variety of sources such as social media, sensors or business transactions. In itself, however, sheer volume rarely delivers added value. Data intelligence aims to structure this mass of data in a meaningful way in order to generate valuable smart data. This data is precisely filtered, processed and checked for reliability so that it can be used specifically for business issues.
The automotive industry is an exemplary field: manufacturers use data intelligence to analyse sensor information generated by big data for the preventive maintenance of their machines. This allows potential breakdowns to be recognised at an early stage and production to run more smoothly. In the energy industry, companies are using this technology to optimise grid control and predict consumption peaks. Finally, in the retail sector, targeted analysis of customer behaviour can be used to identify which products are particularly in demand in order to dynamically adapt the product range and increase customer satisfaction.
BEST PRACTICE at the customer (name hidden due to NDA contract) A leading e-commerce provider used data intelligence to extract individual purchasing patterns from huge clusters of customer data. This made it possible to develop personalised recommendation algorithms that measurably increased sales in the online shop.
Smart data as the basis for well-founded decisions
Smart data refers to the targeted selection and processing of information obtained from big data. Machine learning processes and artificial intelligence help to eliminate irrelevant data and only emphasise the really valuable findings. This turns the flood of data into a clear knowledge advantage - a key benefit for commercial enterprises.
This is exemplified in marketing: instead of broadly distributed mass advertising, data-intelligent analyses enable precise target group segmentation. Campaigns react in real time to changes in customer preferences, minimising wastage. In logistics, on the other hand, data intelligence enables bottlenecks to be recognised at an early stage. This optimises the flow of goods in the best possible way, deliveries are made more punctually and stock levels remain manageable.
In the healthcare sector, smart data helps to make patient-specific therapy decisions. The combination of electronic patient records, laboratory values and wearables creates a holistic database. Doctors benefit from clearly structured information that helps them to adapt treatment plans more effectively and thus achieve better medical results.
BEST PRACTICE at the customer (name hidden due to NDA contract) A hospital network optimised patient data analysis with the help of data-intelligent evaluations. Based on the smart data obtained, the length of stay for inpatient treatment was significantly reduced without compromising quality.
Practical tips for the effective use of data intelligence
A strategic approach is essential in order to truly utilise the potential of data intelligence. The first step is to precisely define relevant data sources and check their quality. A clear objective helps here, for example in which area better decisions should be made.
It is important to integrate modern technologies such as AI-supported analytics or machine learning in order to recognise patterns and trends automatically. Hierarchical data management helps to consolidate data and make it accessible to the specialist departments.
Companies should also promote the transfer of knowledge: regular workshops or training sessions familiarise employees with the benefits of smart data and create acceptance for the new tools. Collaboration across departmental boundaries also makes sense in order to eliminate silos and promote holistic perspectives.
BEST PRACTICE at the customer (name hidden due to NDA contract) An industrial company introduced a data-intelligent system for predictive maintenance. Employees at all hierarchical levels were involved in a training programme. This not only facilitated the technical implementation, but also sustainably improved day-to-day use in operations.
Data intelligence as the key to future innovations
The importance of data intelligence continues to grow as companies increasingly develop data-driven business models. Particularly in the age of digitalisation, it offers new opportunities to use sound analyses for strategic decisions and secure competitive advantages. The combination of big data and smart data is proving to be a key instrument for success.
Whether in production, marketing or healthcare: Organisations that handle their data intelligently can react more quickly to changes, identify trends and better tailor products or services to their target groups. The resulting increase in efficiency has a direct impact on sales and customer satisfaction.
In the insurance business, for example, data intelligence means calculating claims more accurately in advance and thus offering customised tariffs. In public administration, authorities use smart data to make citizen services more efficient and optimise the use of resources.
My analysis
To summarise, it can be said that Data intelligence is the decisive lever for transforming big data into valuable smart data - data that really helps companies and organisations move forward. The targeted selection, processing and intelligent use of information provide decision-makers with the necessary impetus to take well-founded and forward-looking steps. Practical experience shows that many companies are seeing initial success when they see data intelligence as a supporting companion in projects relating to digitalisation and innovation. This opens up sustainable potential for growth, efficiency and customer satisfaction.
Further links from the text above:
[1] From big data to smart data with data intelligence: How to ...
[2] Data intelligence - big data & smart data for decision-makers
[4] Big data vs. smart data: is more always better?
[5] Smart Data: Definition, application and difference to Big ...
[7] Smart data, or the intelligent use of data - Appvizer
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