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Organizations have been analyzing internal and external data to inform their decision-making process for centuries. In the late 1800s, Frederick Winslow Taylor famously studied the organization and its workflows to improve business productivity, which gave rise to an entire field of study dedicated to helping companies grow and become more efficient by measuring data. In the decades that followed, the world witnessed the emergence of vendors and service providers that catered to data analysis needs in specific areas, such as finance, operations optimization, and supply chain efficiency. These providers largely operated in silos.

The near-ubiquity of cloud computing has completely revolutionized the analytics delivery model. With massive amounts of standardized data being generated from the activities of increasingly connected enterprises and being stored on public and private cloud, businesses can now approach data analytics and artificial intelligence (AI) from a whole-of-enterprise perspective like never before.

This study takes a look at the competitive forces and Mega Trends shaping the data analytics and AI ecosystem today. These developments have resulted in the compression of customer value chains and the creation of expansive new analytics partnership ecosystems that will define how analytics and AI services are extended and consumed in the future. In addition, this study helps end-users understand the evolving analytics and AI marketplace as they consider investing in cognitive capabilities. It also offers direction to market participants on how to chart their strategic priorities, such as partnerships, acquisitions, and building new capabilities in response to the changes in the analytics and AI space.