May 2024
Beginner to intermediate
360 pages
9h 2m
English
Content preview from Predictive Analytics for the Modern Enterprise
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Preface
The predictive analytics market has experienced remarkable growth over the past decade. This trend is expected to continue, as the market’s value is projected to surge from $10.5 billion in 2021 to $28.1 billion by 2026. This expansion is being propelled by an increase in automation across industries, the widespread adoption of Internet of Things (IoT) devices, and the advent of high-speed 5G internet connectivity. Enterprises, recognizing the value of processing vast datasets and forecasting future scenarios, are leveraging predictive analytics to gain a competitive edge and bolster revenue streams. Moreover, the COVID-19 pandemic has further underscored the significance of predictive analytics, with organizations now turning to it for strategic planning, operational optimization, and cost savings.
In this era of data-driven decision making, predictive analytics has become an operational imperative. Data professionals today find themselves more intricately linked with business objectives than they ever were before. It is against this backdrop that this book was crafted, aiming to furnish data professionals with the requisite background, tools, and best practices for conceptualizing, implementing, and operationalizing predictive analytics. Through a blend of industry use cases and comprehensive hands-on examples, this book seeks to empower practitioners to navigate the intricacies of predictive analytics with confidence and precision.
Due to the vast nature of predictive ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.