Chapter 1: The Era of Big Data

We are currently situated in an era referred to as the Information Age, more specifically the Big Data Era. The evolution of data and digital storage has revolutionized how we share and consume information. A vast repository of knowledge is now just a few clicks away.

Technological advancements have led to the rise of “smart” devices connected through the Internet of Things (IoT). These once conventional devices—like your toothbrush, watch, or refrigerator—are now equipped with connectivity features, transforming the industry. According to Intel, by 2025, IoT is expected to generate 55% of all data.

Recently, I bought a new GE window air conditioner. With fewer people in my home and an aging central AC system, I am looking for ways to lessen my carbon footprint. The weight of this new unit is quite similar to the older models I remember from my apartment days. However, I was taken aback by its IoT Wi-Fi capabilities.

Why would a basic air conditioning unit require Wi-Fi? In reality, it doesn’t need to. Nevertheless, I decided to connect it, despite my concerns about privacy and the prospect of “big brother” monitoring my energy use.

The SmartHQ app from GE allows users to connect their units to the internet. It enables monitoring of external temperatures, fan speeds, target settings, filter statuses, and even includes an economy mode. Users can remotely check indoor temperatures and schedule operational times.

How to predict the future with big data: Thomas Nørmark discusses how big data can be utilized to forecast future events and trends.

Section 1.1: The Dual Nature of Data Sharing

The interconnectedness of our world through data sharing presents both advantages and challenges. While we become increasingly surrounded by connected devices, we may also feel more isolated. My own experiences reflect this, as I strive to spend time unplugged. Yet, this connection holds potential for our planet’s future.

If you’ve persevered through this discussion, allow me to clarify: we face significant challenges including Global Warming, a devastating pandemic, unstable economies, and the threat of economic collapse. So, why is Data Science important?

Section 1.2: The Power of Data in Decision-Making

When asked about their feelings, many individuals respond with vague terms like “fine” or “okay.” Yet, who has more insights about us than Google? Specifically, Google Trends holds a vast trove of our data. According to the Electronic Frontier Foundation, a staggering 92% of internet searches are conducted through Google.

The immediacy of global data can empower scientists, marketers, manufacturers, and governments to identify current trends. For instance, when a COVID outbreak occurs, Google is often the first to detect it. Current Google Trends for the U.S. indicate rising COVID concerns.

Through data compilation and analysis, we can identify trends in health issues, economic difficulties, civil unrest, and environmental problems. By willingly sharing our data, we provide Data Scientists with the insights they need to help us prepare for future challenges and make necessary adjustments to avert crises.

> “Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.”

> — Aaron Levenstein, Business Professor at Baruch College.

Chapter 2: Learning from Current Observations

Machine learning and climate change: This video explores how machine learning can help us learn from present-day observations to predict future climate scenarios.

Gain Access to Expert View — Subscribe to DDI Intel