Published: 09 September 2024
Summary
The proliferation of AI within analytics, data and software development is supercharging the collision of once-distinct markets, tools and user groups. To drive competitive breakthroughs, data and analytics leaders must navigate significant changes in products, investments and practices.
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Overview
Impacts
Owing to the rapid introduction and significant growth of artificial intelligence (AI) capabilities embedded within data engineering, business intelligence (BI), data science and machine learning (DSML), and software development, the formerly distinct practices for these technologies are colliding.
The convergence of AI with data, BI, DSML and software development facilitates stronger, more complete and more effective links between data, analytics and application investments, practices, processes and key business outcomes.
The infusion of AI has accelerated the clustering of new technical capabilities into ecosystems and extended the reach and value of analytics.Orchestration and oversight have become increasingly critical but much more challenging.
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