Your modern data infrastructure isn’t delivering even after modernization? The limiting factor could be the processes and operations surrounding the systems. Learn how to improve your operating model to best leverage infrastructure and technology
investments.
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Despite growing investments and sustained C-suite interest in advanced analytics, BI and data infrastructure, businesses and their customers often are underwhelmed by the capabilities of their data systems. And the competitive pressure from nimbler competitors and new entrants is on the rise. We also can expect growing regulatory requirements in the data realm – from customer privacy, data sovereignty, compliance, cybersecurity, to fairness and inclusivity.
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Learn MoreThe year 2022 left a marked impact on the global and U.S. analytics market with Generative AI (GenAI) and large language models (LLMs) getting unprecedented attention and playing a substantial role in driving growth. In 2023, enterprises and providers were making investments and taking initiatives to convert the GenAI hype into reality by generating the necessary momentum. This momentum, with the backdrop of enterprises increasingly relying on data-driven decision-making, further propelled the growth of the analytics market in the U.S. Ongoing economic uncertainty combined with reduced consumer activity has pushed enterprises to seek new ways of generating revenue, based on strong data-led business decisions.
In 2022, enterprises in the U.S. invested significantly in analytics solutions to empower their business leaders and employees to make decisions using a data-driven approach. The market witnessed a notable change in the mindset of enterprise executives, reflected in the changing pattern of their investments that shifted from capturing and storing data to actively deriving value out of data. A burgeoning competitive environment and new-age startups with disruptive business models necessitated investments in analytics solutions that drive real-time insights and enable decision-making that is essentially data-driven. While the changing market dynamics demand a variety of analytics solutions and platforms, ISG’s analysis reveals that most of the U.S. enterprises are still in their early stages of analytics and data maturity, which warrants the adoption of tools and platforms that help in delivering visualized insights, data-led storytelling and eventually decision-making.
Use data to assess your supplier delivery against regulations and monitor customer-specific requirements. Complexity and regulatory scrutiny of third-party relationships are on the rise. Get a comprehensive and data-driven way to control risk throughout the life of the relationship.
Advanced technologies address some challenges and introduce others. It’s not science fiction to imagine that the technology is based on machine learning, which is based on identifying and repeating certain patterns. Does this mean the software could, therefore, "learn" that most candidates hired come from a specific school or town? Does this encourage bias – or even profiling?
