With the emergence of Artificial Intelligence (AI) in the business
world, a new era of Business Intelligence (BI) has been ushered in
to create real-world business solutions using analytics. BI
developers and practitioners now have tools and technologies to
create systems and solutions to guide effective decision making.
Decisions can be made on the basis of more reliable and accurate
information and intelligence, which can lead to valuable,
actionable insights for business. Previously, BI professionals were
stymied by bad or incomplete data, poorly architected solutions, or
even just outright incapable systems or resources. With the advent
of AI, BI has new possibilities for effectiveness. This is a
long-awaited phase for practitioners and developers and, moreover,
for executives and leaders relying on knowledgeable and intelligent
decision making for their organizations. Beginning with an outline
of the traditional methods for implementing BI in the enterprise
and how BI has evolved into using self-service analytics, data
discovery, and most recently AI, AI Meets BI first lays out the
three typical architectures of the first, second, and third
generations of BI. It then takes an in-depth look at various types
of analytics and highlights how each of these can be implemented
using AI-enabled algorithms and deep learning models. The crux of
the book is four industry use cases. They describe how an
enterprise can access, assess, and perform analytics on data by way
of discovering data, defining key metrics that enable the same,
defining governance rules, and activating metadata for AI/ML
recommendations. Explaining the implementation specifics of each of
these four use cases by way of using various AI-enabled machine
learning and deep learning algorithms, this book provides complete
code for each of the implementations, along with the output of the
code, supplemented by visuals that aid in BI-enabled decision
making. Concluding with a brief discussion of the cognitive
computing aspects of AI, the book looks at future trends, including
augmented analytics, automated and autonomous BI, and security and
governance of AI-powered BI.
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