In the age of digitalisation, the term data intelligence is becoming increasingly important. Companies are faced with a veritable sea of data, often referred to as big data. The challenge is not only to store this wealth of information, but also to gain meaningful and usable insights from it. This is precisely where the concept of data intelligence comes in: It combines Big Data and Smart Data to provide decision-makers with a supportive basis for making informed decisions.
Big data and smart data: the combination for valuable insights
Big data stands for extensive, diverse and fast data volumes. Smart data, on the other hand, describes high-quality and specifically selected information that is obtained from this data. The true power of data intelligence lies in transforming big data into smart data using modern technologies such as artificial intelligence, machine learning and data analytics.
Although many companies collect huge amounts of data, they find it difficult to derive specific recommendations for action from it. Smart data closes this gap by eliminating unnecessary information and providing precisely the data that is relevant for strategic decisions. This saves time and resources and increases the quality of decision-making.
Practical examples from various industries
In the financial sector, data-intelligent analyses help to base portfolio decisions on reliable data instead of relying on unstructured amounts of information. In logistics, the targeted filtering of big data enables supply chains to be made more transparent and bottlenecks to be recognised at an early stage.
In the manufacturing industry, companies benefit from this by monitoring key production figures and initiating adjustments promptly. In marketing, smart data enables more precise targeting and greater campaign efficiency. In healthcare, too, personalised therapies are prepared with the help of intelligent data analysis.
Data intelligence as the key to successful project decisions
Decision-makers often report how data-intelligent approaches provide valuable impetus in the planning and implementation of complex projects. By selecting relevant data, risks can be minimised and opportunities identified more quickly. In this way, data intelligence helps managers to react in a well-founded and agile manner.
For example, a retail company helps to filter data from millions of customer interactions that provides information about the purchasing behaviour of certain demographic groups. This results in targeted marketing campaigns with a higher chance of success. In the automotive industry, data intelligence is used to continuously analyse vehicle conditions. This supports predictive maintenance, for example: Smart data is used to analyse only truly relevant sensor values in order to detect failures at an early stage and optimally plan workshop appointments.
Data-intelligent working also brings benefits in the healthcare sector. Large amounts of data from patient records, laboratory results and wearables are processed in such a way that doctors can create more individualised treatment approaches. This improves the course of treatment and can reduce costs.
Best practices from the field
BEST PRACTICE with one customer (name hidden due to NDA contract) A logistics company used data intelligence to extract relevant KPIs from big data. This made it possible to forecast delivery times more accurately and manage stock levels better. This helped to reduce costs and increase customer satisfaction.
BEST PRACTICE with one customer (name hidden due to NDA contract) A marketing agency implemented data-intelligent systems to analyse customer behaviour in real time. This enabled campaigns to be flexibly adapted and wastage significantly reduced. This led to a noticeable increase in sales and improved customer loyalty.
BEST PRACTICE with one customer (name hidden due to NDA contract) The introduction of data intelligence in production led to a significant reduction in unproductive downtimes. Thanks to real-time monitoring and algorithm-supported optimisation, maintenance measures could be planned in a targeted manner and expensive downtime prevented. This not only increased efficiency, but also significantly improved product quality.
My analysis
Data intelligence is more than just a trend. It is a decisive factor for success in a data-driven world. Companies that specifically combine big data and smart data gain a clear competitive advantage. They can make faster and better decisions, utilise resources more efficiently and address their customers in a more targeted manner. Data intelligence creates the basis for sustainable innovation and growth.
Further links from the text above:
Big data vs. smart data: is more always better?
Data intelligence: big data and smart data for decision-makers
Smart data, or the intelligent use of data
Smart data: definition, application and difference to big data
Unleashing data intelligence: Big Data & Smart Data for Business
Smart data - definition of terms in the AI glossary
Making decisions with smart data
Data intelligence: clever use of big data and smart data
Big and smart data - from statistics to data analysis
How to secure your lead with Big & Smart Data
Smart + Big Data | Artificial Intelligence
How to turn big data into smart data
What is smart data? Definition and explanation of the term
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