In today's digital economy, the importance of Data intelligence constantly. Companies from a wide range of industries are faced with the challenge of not only collecting large amounts of data (big data), but also analysing it in such a way that it produces usable information (smart data). Innovative business models can only be developed and processes sustainably optimised through the intelligent use of these data sources.
Data intelligence as the key to effective data utilisation
Big data refers to the huge, often unstructured volumes of data that are generated from various sources such as social media, online transactions, sensors or machines. Their sheer size and diversity make manual processing difficult. This is where the Data intelligence It makes it possible to structure and filter this flood of information and transform it into concrete findings using intelligent algorithms.
Industry, for example, obtains reliable real-time data from machines that enables preventive maintenance, thereby reducing downtimes. Energy suppliers use smart meter data to recognise consumption peaks and thus make the grids more stable. In retail, precise customer data helps to create personalised offers and flexibly adapt product ranges to demand.
These examples show how Data intelligence We accompany and support companies from various sectors in making better decisions and securing competitive advantages.
How can big data be turned into valuable smart data?
Under Smart Data is precisely the information that has been extracted from the data volume, cleansed and placed in the right context. It is characterised by high quality, relevance and data protection compliance. Big data is transformed into smart data in the following steps:
- Data integration: Different sources such as CRM systems, IoT devices and external data are linked together.
- Data cleansing: Incorrect or duplicate data is removed.
- Data analysis: Machine learning and statistical models are used to recognise patterns and create forecasts.
- Visualisation: Results are presented clearly so that decisions can be made quickly.
- Governance and data protection: Clear rules ensure responsible handling of sensitive information.
For example, a provider in the field of medical technology is able to automatically analyse large image data sets and improve diagnoses with AI-supported assistance. A logistics company uses smart data to dynamically adapt routes and thus shorten delivery times.
BEST PRACTICE at the 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.
Practical fields of application for data intelligence
The areas of application for data-intelligent solutions are wide-ranging. Some key examples from various industries are
- Industry: Monitoring of machines using sensors for predictive maintenance and quality control.
- Trade: Discovery of shopping patterns to generate personalised offers and dynamically adapt the product range.
- Finances: Analysing transaction data to detect fraud and assess risk.
- Energy supply: Utilisation of smart meter data for grid control and dynamic tariff design.
- Healthcare: Automated evaluation of medical image data and individualised therapy approaches.
All these examples illustrate how Data intelligence as a companion in various projects helps to derive practical benefits from complex data volumes.
Data intelligence as support for transformation processes
Companies often come to us with challenges such as integrating different data sources or ensuring data quality. Data intelligence. There, experts provide support in the selection of suitable technologies, draw up strategies for a sustainable data strategy and provide impetus for practical implementation.
BEST PRACTICE at the customer (name hidden due to NDA contract) An e-commerce company used data intelligence in a targeted manner to generate precise segments from extensive customer data. This made it possible to create personalised marketing campaigns that optimised the customer lifecycle and sustainably increased sales.
Digitalisation, accompanied by the intelligent use of data, enables the continuous improvement of products and services. The more data-intelligent methods are integrated into companies' day-to-day operations, the faster competitive advantages and innovative strength will develop.
My analysis
The use of Data intelligence is now more than ever a decisive success factor for companies in all sectors. Big data generates the raw data, while smart data delivers real added value through clever processing. Those who create this connection can optimise processes, open up new markets and improve customer satisfaction. The integration of intelligent analysis methods provides sustainable support for projects and helps to make information precisely usable.
This accompanies Data intelligence not only in the digital transformation, but also provides a solid basis for future-oriented decisions based on data quality and relevance.
Further links from the text above:
Big data explained simply: definition and meaning
Big data examples and applications
Smart data: definition and application
From big data to smart data with data intelligence
Big data & smart data for smart decisions
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