The article proposes algorithms for processing big data to optimize business processes. The methods of data integration, distributed computing and machine learning for analysis and forecasting are considered. Testing on business cases has shown cost reduction and increased accuracy of solutions, confirming the practical value of the developed approaches. In the modern world, the volume of data is growing exponentially, thanks to the development of technology and the ubiquity of digital devices. Petabytes of information are generated daily: This is data from social networks, electronic devices, online stores, IoT sensors, banking transactions and many other sources. This scale requires new approaches to data collection, storage, processing and analysis. Big Data has become a key asset for businesses. Their use allows you to identify hidden patterns, develop personalized offers, predict demand and minimize risks. Big data plays an important role in strategic planning, improving efficiency and optimizing business processes. Effective work with big data requires the use of complex algorithms and technologies such as distributed computing, machine learning and streaming processing. Thes
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