In times of rapid digitalisation, companies in all sectors are increasingly relying on data intelligence to extract valuable smart data from the flood of big data. This change is not just a technical challenge, but above all opens up opportunities to optimise business processes and tap into new potential. Data intelligence therefore represents an essential basis for sustainable corporate success.
Data intelligence as the key to transforming big data into smart data
Big data comprises large, complex and diverse amounts of data that are generated quickly. Many companies are faced with the difficulty of filtering out meaningful insights and managing unstructured raw data. The answer to this is data intelligence: it ensures that this volume of data is analysed, filtered and processed using algorithms such as artificial intelligence and machine learning.
Data intelligence transforms the confusing raw material of big data into smart data - structured, reliable and contextualised information that supports targeted decision-making processes.
An example from industry shows how a car manufacturer is using data intelligence to optimise its production. Using IoT sensors, they record machine data in real time, recognise potential failures at an early stage and thus reduce expensive downtime. This smart data enables flexible adjustments to demand and increases production quality.
In retail, companies use data intelligence to analyse the purchasing behaviour of their customers as well as external factors such as the weather or regional events. This leads to precisely segmented marketing campaigns that take individual needs into account and increase sales.
In the energy sector, an energy supplier uses smart data to predict consumption patterns and manage the electricity grid more efficiently. The result is cost savings, better integration of renewable sources and satisfied customers.
How data intelligence supports companies in various industries
The applications of data intelligence extend far beyond individual industries. In healthcare, for example, patient data is intelligently analysed in order to improve diagnoses and personalise therapies.
An insurance company uses data intelligence to assess risks more accurately and recognise attempted fraud at an early stage. This allows premiums to be calculated better and claims processes to be handled more efficiently.
In the financial sector, data intelligence allows transaction data to be analysed in real time. Banks identify unusual patterns, protect customers and develop customised offers.
BEST PRACTICE at the customer (name hidden due to NDA contract) A medium-sized production company was faced with the challenge of better utilising the enormous amount of sensor data from production. Through transruption coaching, a data strategy was developed that relied on data-intelligent processes such as machine learning. The results were improved quality assurance, predictive maintenance and a noticeable reduction in rejected products.
BEST PRACTICE at the customer (name hidden due to NDA contract) A retailer used data intelligence to analyse complex customer interactions in online and offline channels. This enabled needs to be identified at an earlier stage and personalised offers to be displayed in a more targeted manner. Customer satisfaction increased measurably, as did the conversion rate.
BEST PRACTICE at the customer (name hidden due to NDA contract) In the energy sector, data intelligence was used to develop a forecasting model for energy consumption that also takes external influences such as weather and events into account. This enabled dynamic pricing and more resource-efficient grid utilisation.
Tips for the successful use of data intelligence
In order for companies to successfully navigate their way from big data to smart data with data intelligence, the following impulses are helpful:
- Develop a clear data strategy that is aligned with business objectives.
- Regularly check data quality and consolidate data sources.
- Targeted use of artificial intelligence and automated analyses.
- Create interdisciplinary teams that combine technical and specialist expertise.
- Include data ethics and data protection as an integral part of data intelligence.
This enables a transformation that not only addresses technical aspects, but also develops the corporate culture. Companies that act in a data-intelligent manner can react more quickly to market changes and create innovative offerings.
My analysis
Data intelligence is the key success factor if companies want to master the transition from big data to smart data. Through intelligent analysis and processing, data is not only managed but also utilised as a valuable resource for strategic decisions. Across industries, data intelligence helps to secure competitive advantages, organise processes more efficiently and better understand customer needs. Investing in data-intelligent solutions and the support of specialised expertise will guide organisations safely along this path to success.
Further links from the text above:
From big data to smart data with data intelligence: How to ...
Unleashing data intelligence: Big Data & Smart Data for ...
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