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CAMELOT Consulting Group
IT systems can generate knowledge from experience through machine learning. The basis for this is the analysis of huge amounts of data using algorithms. With the help of machine learning, IT systems identify patterns and principles in order to develop solutions. Here, you will find use cases and inspiration for applying machine learning in your company.
Integration of cloud strategy for enterprise reporting can bring IT and business together in a best course. Learn more about enterprise …
read moreMore and more data are generated in today’s enterprise data landscapes. If we do not change the approach of data …
read moreTo reliably predict customer demand, companies predominantly rely on statistical forecasting by selecting the most suitable model(s) for their products. …
read moreThis blog article introduces these concepts to help practitioners improve their demand forecasts and boost their demand planning process.
read moreThe Camelot Supply Chain Resilience Cockpit application powered by SAP Data Intelligence and SAP Data Warehouse Cloud analyses how external factors …
read moreThe Supply Chain Resilience Cockpit provides transparency for SAP DWC: The free content package for SAP DWC makes weather data available …
read moreAfter a short history of neural networks in our previous blog, this article focuses on the Perceptron as the most basic …
read moreWhen navigating through the world of Machine Learning, Artificial Intelligence or Data Science (you name it), it is usually not long …
read moreNowadays, Data is being gathered from IoT devices, social media and almost any (business) application we are using in our daily …
read moreAs a major user of energy and natural resources, as well as origin of major waste streams, manufacturing operations need to …
read moreToday’s supply chains face huge challenges: Sudden changes in customer demands as we saw in lockdowns during COVID-19 call for …
read moreHow SAP C4C helps you comply with the new European General Data Protection Regulation (GDPR) Data privacy – currently more in …
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