What will I learn about: The explosive growth of Big Data has been driven by our changing digital consumption habits combined with drastically plummeting data storage costs?

The explosive growth of Big Data has been driven by our changing digital consumption habits combined with drastically plummeting data storage costs.

What will I learn about: More than 80 percent of organizational data today is unstructured, meaning companies must look beyond traditional spreadsheets to analyze complex information like social media activity?

More than 80 percent of organizational data today is unstructured, meaning companies must look beyond traditional spreadsheets to analyze complex information like social media activity.

What will I learn about: Advanced visualization techniques, such as heat maps and time series analysis, are essential for distinguishing actionable, long-term business trends from temporary market anomalies?

Advanced visualization techniques, such as heat maps and time series analysis, are essential for distinguishing actionable, long-term business trends from temporary market anomalies.

What will I learn about: Traditional software is insufficient for Big Data, requiring businesses to adopt versatile platforms like Hadoop or outsource complex analytical challenges to crowdsourced platforms like Kaggle?

Traditional software is insufficient for Big Data, requiring businesses to adopt versatile platforms like Hadoop or outsource complex analytical challenges to crowdsourced platforms like Kaggle.

What will I learn about: The future of consumer technology relies on passively generated data, where internet-connected devices automatically track user behavior to learn preferences and create smarter environments?

The future of consumer technology relies on passively generated data, where internet-connected devices automatically track user behavior to learn preferences and create smarter environments.

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Too Big to Ignore

The Business Case for Big Data

Phil Simon

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Technology & the Future

If You're Curious About These Questions...

You should listen to this audiobook

💡How did analyzing unstructured data from social media save Netflix from a massive subscriber exodus?
💡Why might a sudden spike in retail sales be misleading, and how can time series analysis prevent companies from making costly inventory mistakes?
💡How is the shift from actively created data to passively generated data transforming everyday objects into smart, predictive devices?

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Key Takeaways from Too Big to Ignore

✓The explosive growth of Big Data has been driven by our changing digital consumption habits combined with drastically plummeting data storage costs.
✓More than 80 percent of organizational data today is unstructured, meaning companies must look beyond traditional spreadsheets to analyze complex information like social media activity.
✓Advanced visualization techniques, such as heat maps and time series analysis, are essential for distinguishing actionable, long-term business trends from temporary market anomalies.
✓Traditional software is insufficient for Big Data, requiring businesses to adopt versatile platforms like Hadoop or outsource complex analytical challenges to crowdsourced platforms like Kaggle.
✓The future of consumer technology relies on passively generated data, where internet-connected devices automatically track user behavior to learn preferences and create smarter environments.

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Too Big to Ignore

The Rise of Big Data+

Nature of Big Data+

Business Insights+

Data Visualization+

Tools & Management+

Organizational Readiness+

Security & Ethics+

Future of Big Data+

Quiz — Test Your Understanding

Question 1 of 9

What are the two primary drivers behind the rapid growth of Big Data according to the text?

A. Government regulations and corporate data mandates
B. Changing consumption patterns and plummeting technology costs
C. The invention of Microsoft Excel and relational databases
D. Increased privacy laws and the rise of cybersecurity threats

Question 2 of 9

Why is unstructured data, which makes up over 80 percent of organizational data today, difficult to manage?

A. It cannot be easily organized into traditional relational tables because it contains multiple, complex relations.
B. It requires constant internet connectivity to be accessed by internal data scientists.
C. It is exclusively generated by passive devices like smart thermostats and autonomous cars.
D. It is heavily encrypted by social media platforms, making it illegal to process.

Question 3 of 9

How did Netflix use unstructured data to recover from losing 800,000 customers in the summer of 2011?

A. They used heat maps to identify which geographic regions were canceling subscriptions the fastest.
B. They outsourced their customer service data to Kaggle to predict future subscription drops.
C. They monitored social media to realize customers were driven away by the Qwikster rebranding and repricing.
D. They conducted a time series analysis to see how the loss correlated with customer payday dates.

Question 4 of 9

What is a primary advantage of using a time series analysis for business data?

A. It displays several variables at once using color intensity.
B. It helps differentiate between long-term trends, seasonal trends, and irregular fluctuations.
C. It automatically restructures messy social media data into clean, relational tables.
D. It breaks down massive data tasks into smaller, manageable subtasks for processing.

Question 5 of 9

Why might a company choose to use a heat map instead of a traditional graph to analyze a massive dataset?

A. Heat maps are the only tool capable of predicting irregular sales fluctuations.
B. Heat maps automatically filter out unstructured data from social media platforms.
C. Heat maps provide an intuitive overview of several variables at once using color intensity.
D. Heat maps are required by open-source platforms like Hadoop to process data.

Question 6 of 9

How does the platform Hadoop handle massive Big Data tasks?

A. It organizes all unstructured data into a single, standardized Microsoft Access database.
B. It breaks down large data tasks into smaller subtasks that are processed individually.
C. It outsources the data processing to a network of freelance data scientists.
D. It relies solely on passive data generation to reduce the overall processing load.

Question 7 of 9

According to the text, what is a crucial first step an organization must take before investing heavily in Big Data tools?

A. Hire a team of at least 100 data scientists to manage the new infrastructure.
B. Transfer all existing relational data into unstructured formats like tweets and posts.
C. Ask specific questions and outline short- and long-term goals to ensure they gather useful information.
D. Purchase proprietary software since open-source tools like Hadoop are not reliable.

Question 8 of 9

What is a major ethical and security concern amplified by Big Data mentioned in the text?

A. The high cost of data storage makes it impossible for small businesses to compete.
B. Centralized databases are frequently deleted by automated passive data generators.
C. The massive accumulation of customer data creates lucrative targets for hackers and threatens privacy.
D. Data scientists often use predictive models to manipulate stock market prices.

Question 9 of 9

What does the text predict regarding the future generation of data?

A. There will be a slow move from actively created data to passively generated data by connected devices.
B. Consumers will stop generating data entirely due to rising privacy concerns.
C. Data generation will shift exclusively back to relational tables as unstructured data becomes too expensive to store.
D. People will only generate data through active usage of laptops and smartphones.

Too Big to Ignore — Full Chapter Overview

1Recommendation
2Changing consumption habits and falling technology costs have fueled the rise of “Big Data.”
3Big Data can give you a deeper understanding of your customers and business.
4Visualizing your data helps you analyze trends.
5Use innovative new platforms to manage your Big Data work – or outsource it.
6Make sure your organization is truly ready for Big Data.
7Big Data intensifies existing security and ethical issues.
8Big Data will make products “smarter.”
9Final summary

Too Big to Ignore Summary & Overview

Too Big to Ignore explains why Big Data is tremendously important for your business. It illustrates the ways that Big Data analysis can revolutionize your company, and takes you step by step through the tools you need to harness it. It also looks ahead to our Big Data future.

Who Should Listen to Too Big to Ignore?

Anyone interested in entrepreneurship or business
Anyone interested in technology
Anyone looking to use Big Data in their company

About the Author: Phil Simon

Phil Simon is a technology consultant, and the author of The Age of the Platform. His work has been featured on NBC, CNBC, ABC, in BusinessWeek and The Huffington Post.

© [Phil Simon: Too Big to Ignore] copyright [2013], John Wiley & Sons [Inc. or Ltd. as applicable] Used by permission of John Wiley & Sons [Inc. or Ltd. as applicable] and shall not be made available to any unauthorized third parties.