Big Data in Practice – Bernard Marr
Original price was: $27.00.$25.00Current price is: $25.00.
In StockThe best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data.
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Accelerate your learning with the Big Data in Practice – Bernard Marr course, priced at just Original price was: $27.00.$25.00Current price is: $25.00. on ESYSGB.com! Explore our extensive catalog of over 60,000 downloadable digital courses across Uncategorized. Experience flexible, self-paced learning from experts and save over 80%. Empower your future today!
DESCRIPTION
The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data.
Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective.
From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario.
- Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers
- Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more
- Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking
- Develop your own big data strategy by accessing additional reading materials at the end of each chapter
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