Data analysis is a crucial step in the modern business world for gaining valuable insights from large amounts of data. It enables companies to make informed decisions and optimise their strategies. In this article, we will look at the basics of data analytics and show how it can be used in combination with big and smart data to improve business processes.
Basics of data analysis
Data analysis is the process of collecting, processing and analysing data in order to extract valuable information from it. This process is crucial for extracting targeted insights from large amounts of data, often referred to as big data. Big data is characterised by its size, complexity and speed, which makes it difficult to filter out relevant information without appropriate analysis techniques [1][8].
From big data to smart data
Smart data is the further development of big data. It is high-quality and specifically selected information that is obtained from large volumes of data. This data is processed to provide directly usable knowledge that supports companies in making strategic decisions [3][4]. One example of this is the use of sensors in industry, which enable predictive maintenance by analysing machine data, thereby minimising downtime [2][7].
Data analysis in practice
Data analysis is used in many industries to optimise business processes. In the financial sector, for example, data-intelligent analyses help to base portfolio decisions on reliable data instead of relying on unstructured amounts of information [4]. 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 [4].
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.
Data analysis in customer loyalty
In marketing, data analysis is used to analyse customer behaviour in real time and flexibly adapt campaigns. This leads to a noticeable increase in sales and improved customer loyalty [4]. Another example is the use of smart data in the healthcare sector, where personalised therapies are made possible by analysing patient data [7].
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.
Data analysis as a strategic success factor
Data analysis is a decisive factor for the success of companies. It makes it possible to gain targeted insights from large volumes of data and make well-founded decisions. By combining big and smart data, companies can optimise their processes and increase their competitiveness. Data analysis helps companies to refine their strategies and take targeted measures.
My analysis
To summarise, data analysis is an indispensable part of modern business strategies. It makes it possible to gain valuable insights from large volumes of data and make well-founded decisions. By combining big and smart data, companies can optimise their processes and increase their competitiveness. Data analysis is therefore a decisive step on the way to data-driven decisions and sustainable success.
Further links from the text above:
For more information on the topics of big data and smart data, you can consult the following sources:
– Smart data, or the intelligent use of data
– Smart data: definition, application and difference to big data
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