If You're Curious About These Questions...
You should listen to this audiobook
- Did you know that in the era of big data, understanding *why* something happens is becoming far less important than simply knowing *what* will happen next?
- Have you ever wondered how the world's most successful companies are turning 'messy' piles of information into a goldmine of profit and innovation?
- What if you could predict future trends and human behaviors with startling accuracy, and what are the hidden risks of living in such a data-driven society?
Listen to Big Data — Free Audiobook
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Key Takeaways from Big Data
- Discover how analyzing data on a massive scale unlocks unprecedented predictive insights, like forecasting viral outbreaks, that are completely invisible at smaller scales.
- Understand the rising trend of datafication, where everyday physical actions from the way you sit to how you walk are continuously captured to drive product innovation.
- Learn why big data eliminates the flawed reliance on traditional sampling, empowering you to analyze entire populations and confidently draw conclusions about highly specific subgroups.
- Find out why leveraging massive volumes of uncurated, messy data ultimately produces far more accurate and useful results than relying on small, meticulously accurate datasets.
- Recognize why simply knowing that two data points are strongly correlated is often enough to make highly effective decisions, even when big data cannot explain why they are connected.
Learning Tools
Reinforce what you learned from Big Data
Mind Map
Big Data
The Shift in Analysis
From Sampling to N=All
Embracing Messiness
Correlation over Causality
Datafication & Value Extraction
Datafication
Secondary Uses
Combining Datasets
The Big-Data Mindset
Enhancing Products & Services
Utilizing Data Exhaust
Risks & Ethical Pitfalls
Privacy Framework Failures
Predictive Justice Dangers
Perils of Data Obsession
Quiz — Test Your Understanding
Question 1 of 10
According to the text, what is the inherent problem with traditional data sampling methods that big data helps to overcome?
Big Data — Full Chapter Overview
Chapter 1: Recommendation
Chapter 2: Data is increasingly collected and used in every part of our lives, from the size of our bums to how we walk.
Chapter 3: Big data releases us from the limits of representing whole populations with small data samples.
Chapter 4: Huge, messier data sets can be more valuable than smaller, more precise ones.
Chapter 5: Big data does not explain why two things are linked, only that they are, but this alone is often sufficient.
Chapter 6: Although data is usually gathered for one purpose, secondary uses can sometimes be even more valuable.
Chapter 7: Anyone can discover new ways to create value from surrounding data – all it takes is the right mindset.
Chapter 8: Merging different data sets can produce more value than each one alone.
Chapter 9: Online platforms like Facebook track everything we do on their sites and exploit this data to improve their services.
Chapter 10: Existing privacy rules and anonymization techniques fail and waste effort when used with Big Data.
Chapter 11: Big data enables predictions of crime, but we must never condemn people before they actually offend.
Chapter 12: Being too data-driven is risky: we may track the wrong metric, push the wrong behavior or depend on faulty data.
Big Data Summary & Overview
Big Data provides an insightful look at why a change to “big data” is a major shift in how we collect, use and think about the data around us. It provides great explanations and examples of how individuals and companies already ahead of the curve are using the tools of big data to create value and profit. Casting an eye forward, the book also outlines the future implications for a big-data society in terms of the risks, opportunities and legal implications.
Who Should Listen to Big Data?
- Anyone who is interested in learning more about what “big data” is and what it means for society
- Anyone who is looking to make a career using big data
- Anyone from a company who is looking for opportunities to use the data the company collects
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