Every day, more companies unlock the potential of artificial intelligence (AI) and machine learning. When AI and machine learning are utilized in embedded analytics, the results are impressive. Much of this can be seen in modern solutions that offer advanced predictive analytics. Together, predictive analytics and AI can help application teams by streamlining processes, generating personalized recommendations, and creating a more intuitive and efficient user experience.

Your SAP system collects vast amounts of financial and operational data. But you only tap into a portion of SAP’s potential power when this data is kept siloed within separate departments, systems or spreadsheets. CFOs are under increasing pressure to provide actionable insights that guide leadership decision-making. In today’s turbulent market, it’s key that these insights include data inputs from across the whole organization, not just finance.

The AI technologies of today—including not just large language models (LLMs) but also deep learning, reinforcement learning, and natural-language processing (NLP) tools—will equip telcos with powerful new automation and analytics capabilities. AI-powered automation is already driving significant margin growth by reducing costs.

Python’s popularity has more than doubled in the past decade¹ and it is quickly becoming the preferred language for development across machine learning, application development, pipelines, and more. One of our goals at Snowflake is to ensure we continue to deliver a best-in-class platform for Python developers.

In today’s tough market, telecommunications companies are feeling the pinch. The telecom industry has undergone enormous change in the last few years. Rapid advances in technology such as the emergence of 5G Wi-Fi, the expansion of fixed wireless access and satellite services and the explosion of IoT devices have put increased pressure on aging legacy equipment, systems and communication networks.