- In June 2024, IBM Corporation announced a collaboration with Telefónica Tech. This collaboration will drive the adoption of Artificial Intelligence (AI), analytics, and data governance solutions and respond to the continuous and dynamically developing requirements of enterprises
- In March 2024, Microsoft announced a collaboration with NVIDIA to advance healthcare and life sciences innovation using cloud AI and accelerated computing. The collaboration aims to improve patient care by accelerating access to precision medicine and AI-powered diagnostics, ultimately driving significant advancements in the healthcare industry
- In January 2023, Science Applications International Corp. introduced the "Tenjin" data science platform, a versatile solution that supports low-code to full-code development for AI and machine learning applications. Powered by Dataiku, Tenjin facilitates the entire lifecycle of AI and ML model development, from deployment to training and automation, along with advanced data visualization tools. This platform aims to simplify complex processes, making AI accessible to a wider range of businesses
- In October 2022, IBM Corporation launched the Diamondback tape library, an advanced storage solution utilizing LTO technology. This innovative product boasts an impressive capacity of up to 27 petabytes (PB) of data storage within a single server rack. The Diamondback is designed to meet the increasing demands for data storage, offering scalability and reliability for organizations needing to manage vast amounts of information securely and efficiently
- In June 2022, SAS Institute expanded its capabilities by acquiring Kamakura Corporation, enhancing its portfolio with integrated risk solutions. This acquisition focuses on delivering specialized professional services in Asset Liability Management (ALM) and other financial sectors, including banking. By combining resources and expertise, SAS aims to offer comprehensive solutions that address complex risk management challenges, helping organizations make informed financial decisions and navigate market uncertainties effectively
Frequently Asked Questions
The accelerated ai integration and platform consolidation, is emerging as a pivotal trend driving the global data science platform market.
The major factors driving the growth of the data science platform market are growing need due to exponential growth in data generation.
The primary challenges include data privacy and security concerns and competitive market dynamics challenging brand differentiation.
The platform segment is expected to dominate the global data science platform market holding a major market share with 83.4% in 2025, due to technological improvements, such as data mining, advanced computing, and robotics, significantly drive the segment's growth.
