Business Intelligence, Analytics, and Data Science A Managerial Perspective

What it’s about

In a world where data is the new currency, managers are under immense pressure to make faster, better, data-driven decisions. "Business Intelligence, Analytics, and Data Science: A Managerial Perspective" provides a comprehensive framework for harnessing the power of data. It guides readers through the entire analytics continuum, from descriptive analytics that reveal what has happened (statistical modeling, data visualization, and data warehousing), to predictive analytics that foresee what will happen (data mining, text analytics, and social media analysis), and finally to prescriptive analytics that advise on what to do (optimization and simulation). Packed with real-world case studies from sports, healthcare, retail, and more, this book demystifies complex topics like Big Data, IoT, and cloud analytics, equipping managers and aspiring data scientists with the principles and tools needed to gain a competitive edge and drive organizational success in the age of analytics.

The through-line

Who it’s for

A modern manager, business leader, or aspiring analyst who operates in a complex, competitive environment. They want to move beyond intuition-based decisions and leverage their organization's vast data assets to drive efficiency, increase profitability, and gain a sustainable competitive advantage.

The problem

Organizations are drowning in data (from transactional systems, social media, sensors) but starving for actionable insights. Making timely, optimal decisions is increasingly difficult due to the volume, velocity, and variety of this data. This data overload makes managers feel overwhelmed, uncertain, and anxious about falling behind competitors. They fear they are missing crucial opportunities or failing to identify significant threats hidden within their data.

The plan

1. Part 1: Understand the foundations of descriptive analytics, including data warehousing, statistical modeling, and data visualization.
2. Part 2: Master predictive analytics by learning the processes and methods of data mining, text mining, and social media analytics.
3. Part 3: Learn to recommend optimal actions using prescriptive analytics, including optimization and simulation modeling.
4. Part 4: Grasp the concepts of Big Data and future trends like IoT, cloud computing, and location-based analytics to stay ahead of the curve.

The payoff

Managers can confidently make strategic, tactical, and operational decisions backed by data. · Organizations gain a competitive edge by deeply understanding their customers, optimizing processes, and identifying new market opportunities. · Aspiring analysts develop a comprehensive skill set that makes them highly valuable in the modern data-driven economy.

See our guide

• Practice Business Intelligence & Data Science →

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• Practice Business Intelligence & Data Science →Cited source