Krishna Roy is a senior research analyst in the 451 Research technology research group within S&P Global Market Intelligence. She leads the data science and analytics coverage areas for the Data, AI & Analytics channel. Prior to this, Krishna was a research analyst in the Data, AI & Analytics channel covering business intelligence and data management, including data integration and data warehousing. Krishna arrived at S&P Global Market Intelligence through its 2019 acquisition of 451 Research, where she was a senior research analyst. During her 20-year tenure with 451 Research, she was responsible for many coverage areas, including business applications and business intelligence. Prior to joining 451 Research, Krishna held several journalist roles in London, New York and San Francisco. Krishna’s recent areas of concentration include data-driven decision-making, AI governance and compliance, and generative AI’s role in data science and analytics. Krishna holds a Bachelor of Arts, First Class Honors Degree, in English literature and American studies from Brunel University, London.
This report highlights the key topics we expect to be prominent in 2025 in the data, AI and analytics space. While generative AI remains a predominant theme, for the technology to succeed, preexisting issues must be resolved around data management, data operationalization, machine learning operationalization and other infrastructure-related tasks.
As generative AI moves from experimentation to deployment, the discipline of large language model operationalization (LLMOps) becomes critical to project success because LLMs are the first type of GenAI to be adopted by enterprises. However, LLMOps is still nascent; this report explores what it is, why it matters, and adoption challenges it faces.
The company is targeting personas who prefer to code data science jobs in R or Python. The RStudio open-source integrated development environment has been a linchpin in this strategy. Positron is now in public beta in a bid to make Python and R-based data science easier.
Findings from our Generative AI 2024 survey show that data science and analytics tools and platforms play a key role in data-driven decision-making. Data science platforms are also emerging as a popular alternative to purchasing new software platforms specifically for generative AI project operationalization.
Karini AI emerged onto the generative AI scene in early 2024 with a no-code offering for the operationalization of certain types of large-language-model-driven applications by subject matter experts who know their business domain but are not highly technical, such as marketers, accountants and sales personnel.
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