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Partial book profile

Data Smart Using Data Science to Transform Information into Insight

John W. Foreman

This book teaches practical data science techniques using familiar spreadsheet software, making complex concepts like clustering, regression, and optimization accessible to a broad business audience without requiring coding skills.

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What it’s about

You've heard the buzz about 'data science' and 'big data,' but the hype and complex tools can be intimidating. 'Data Smart' demystifies these powerful techniques by stripping away the code and focusing on the core concepts. Using the familiar environment of a spreadsheet, this book provides hands-on, practical walkthroughs of key data science methods like clustering, regression, optimization, and forecasting. You'll learn not just what these techniques are, but how to implement them from scratch to solve real-world business problems, from segmenting customers to predicting purchases. By the end, you'll be equipped to identify data science opportunities in your own organization, prototype solutions, and make smarter, data-driven decisions without needing to be a coding expert.

The through-line

Who it’s for
A business professional (manager, analyst, marketer, CEO) who is intrigued by the promise of data science but feels intimidated by the technical jargon, coding requirements, and expensive tools. They have access to business data and want to use it more strategically to solve problems, segment customers, predict outcomes, and reduce costs, but they don't know where to start.
The problem
Lacking the technical skills (coding, specialized software) to implement data science techniques and feeling lost in the hype of 'big data'. Feeling anxious, overwhelmed, and left behind by the data revolution, and frustrated by the inability to unlock the value hidden in their business data.
The plan
  1. Learn the essential spreadsheet skills that form the building blocks for data science.
  2. Master specific data science techniques (like clustering, classification, optimization, etc.) through hands-on business cases, one at a time.
  3. Learn how to transition from spreadsheet prototypes to a more powerful, production-ready environment like R.
The payoff
Feeling confident and excited about using data to solve business problems. · Being able to identify data science opportunities and prototype analytical models in a spreadsheet. · Making better, data-driven decisions and communicating effectively with technical teams and consultants.

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