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Transforming Industry Through Data Analytics by Raghunath Nambiar

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Chapter 1. Introduction

Everything is going digital. By the year 2020, seven billion people will have access to the internet, roughly half through a traditional wired connection, the other half wirelessly via mobile devices.

Similarly, current growth predictions put the number of devices connected to the internet by the year 2020 at 50 billion; by the year 2030 this number skyrockets to 500 billion (see Figure 1-1).

Pillars of digital transformation
Figure 1-1. Pillars of digital transformation

In terms of data, by the year 2020, there will be 50 zettabytes of stored data. To give some perspective, that’s equivalent to 50 billion one terabyte disk drives. What’s more, by the year 2030, this number will increase by an order of magnitude.

These are impressive numbers by themselves, but it pales in comparison when you consider that when you connect something to the internet, it is not just connected to the network, it is connected to everything else.

Thus, we see an unprecedented opportunity as the number of connections explodes. The greatest opportunity exists where those connections are most dense, yet these are the areas where it is most difficult to make predictions. We humans have a tendency to overestimate what will happen in the next two years and underestimate what will happen in the next 10 years. This has never been truer than it is now as we approach this singularity of connections.

The rapid pace of technological change is often cited by senior executives as the biggest threat to their business. Consider that only 12 percent of the Fortune 500 companies from 1955 still exist today, and only 50 percent of current Fortune 500 companies are expected to still be in business just 10 years from now. Note that today’s Fortune 500 companies represent more than two-thirds of the GDP in the United States.

Examples abound:

  • Amazon put Borders bookstores out of business and all but destroyed the brick and mortar bookstore business.

  • Netflix drove Blockbuster out of business and has its sights set on premium cable TV (Netflix’s subscription revenue now exceeds that of HBO). It’s worth noting that originally Netflix mailed DVDs to its customers, building its business through low-cost, convenience, a wide selection and an analytics-driven recommendation engine. That business is all but dead, having been replaced by Netflix’s own streaming service.

  • Uber and other ride-hailing services have transformed the taxi industry.

  • Airbnb is threatening the hotel business, and the list goes on.

It’s called creative destruction, and it’s an extinction event for companies that are unwilling or unable to adapt. Analytics capabilities have become the differentiator. Analyzing data to understand the business and how to guide it through treacherous technology revolutions is the difference between a growing, thriving company and extinction.

To understand how to proceed let’s first look at the specific challenges we face as we work to tame the deluge of data being generated, changing it from meaningless bits into actionable insight. Next, we’ll review the four different types of analysis, what they are, how they’re used, and what kind of analytical system is required to enable them. Lastly, we’ll look at how the incredible explosion of connections, in the form of devices and people, and how our ability to make use of the data they generate, will affect our cities, the energy sector, the manufacturing industry, transportation, and, arguably the most important, health care.

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