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.
The advanced analytics veteran, which has never been a particularly active acquirer, has purchased the key synthetic data technology assets from Hazy. With the deal, SAS is aiming to augment its ability to provide its key audience of data scientists and developers in enterprises with synthetic data, which is becoming increasingly popular.
As artificial intelligence is increasingly regulated and generative AI shifts from experimentation to adoption, being able to govern AI models becomes more critical because the financial penalties and business risks from not doing so heighten. This could spur established enterprise software vendors to address this need with M&A.
As artificial intelligence is increasingly regulated and generative AI shifts from experimentation to adoption, being able to govern AI models becomes more critical because the financial penalties and business risks from not doing so heighten. This could spur established enterprise software vendors to address this need with M&A.
Having unveiled an optional add-on module to its core platform, as well as separately priced professional services, the data science platform provider is seeking to address a growing requirement to govern AI models. Its strategy is based on the premise that AI governance is not always effectively addressed by technology alone.
The success of enterprise artificial intelligence projects is increasingly tied to effective AI governance. Yet despite growing acknowledgement of the need to manage the risks that AI presents, the precise nature of governance technology is still not well understood.
Data-driven decision-making has not reached the level of ubiquity many organizations would like. Tableau Einstein, billed as the New Tableau, aims to make data-driven decision-making more pervasive by obviating the need to hunt for and interpret insights in dashboards. Tableau Einstein is being built out into a semantic-driven analytics platform, underpinned by Salesforce Data Cloud and Agentforce.
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