Big Data Every Day


Want to start using Big Data to your organization’s advantage? Start by using Big Data in your personal activities. It provides great insights, opens a window into emerging approaches and best-of-breed applications, and just might save your life. Conversely: Try not using it. You will be equally amazed at its pervasiveness in almost everything we do today.

Our Strategy Lab session today reviews Big Data usage in day-to-day life.

Let’s start by reviewing the definition of Big Data:

“Big data represents the information assets characterized by such a high volume, velocity and variety to require specific technology and analytical methods for its transformation into value.”1

Big Data becomes self-reinforcing: Big Data opens up new ideas that in turn necessitate Big Data to offer value. This is a corollary to the network effect: Success begets success and opens new and mostly-unique new growth. Conversely, we see way too many business propositions that assume and rely upon network effect benefits from the get-go. Network effect is earned, and creates its own defensive perimeter. But, back to Big Data. Think huge, complex and / or valuable at real-time data sets.

Weather: The Ultimate Big Data Use Case

IBM’s acquisition of The Weather Channel makes perfect sense, if only because weather data is the ultimate Big Data laboratory exercise. Big Data powers micro-forecasts and more accurate global forecasts.

Use it to plan a trip, or just exercise. Leverage embedded web cameras to check traffic (seeing is believing), or check anticipated turbulence or airport delays.

At a micro-level, Big Data services collect and visualize weather data (every 2 seconds) at our home.

Health: The Trendiest Big Data Use Case

And, here we mean trendiest, because it is popular and because the identification and visualization and alerts around trends create incredible value. Give into it: Let a device track everything. Very reasonably priced sensors can track everything: Sleep, heart rate, respiration, steps, stairs, calorie count, exercise, blood pressure, etc. I use

Companies are building sensor-data Big Data based applications, some even receiving FDA approval for use cases and accuracy. This arena will explode in the next few years, targeting broad and niche-based health needs.

And, the fitness insights are life-changing. This is Huge Data.

Fitness: The Funnest Big Data Use Case

Strava received some negative press early this year, as news outlets used their Heat Map to identify military bases.

Strava has become the go-to Big Data application for runners and cyclists, though far from the only option. Beyond tracking personal achievements, the application — reliant on network benefits and huge data sets from personal sensors, GPS and mapping systems and exercise sentiment — suggests runs, summarizes and visualizes performance, and compares progress and results to personal and overall bests.

Want a remarkable piece of research based on Big Data alone? Take a look at this assessment from the New York Times of Nike’s wildly popular high end running shoe.

New shoe, new media approach, based on an astounding amount of personal information served up by Strava, based on sensors provided by Apple, Garmin, and others.

Traffic Data: Sensors Turned Around

For years, early Big Data prognosticators and progressive strategists forecast massive sensor networks that throughout our road infrastructure. They were totally right. And totally wrong.

The massive sensor network, at least for now, turns out to be our mobile devices. Yes, there are an increasing number of embedded sensors, and cameras, and other IoT devices. But, the epiphany came from companies that realized our phones could be used in a crowdsourced network model to turn the whole concept on its head.

This example bodes well for all sorts of companies that may implement Big Data in micro and macro forms. Data may come from unexpected places. Or, in this case, the most pervasive and pedestrian of devices.

Apps: Big Data At Every Turn

And, to state the very, very obvious: Most of us rely every day on apps that are delivering Big Data value and concepts all of the time. It’s interesting to note that they all use NoSQL efforts to support key components. Many have built their own massive and distributed systems (Facebook, Google, Amazon are just a few that developed their own data storage solutions); other become the marquee use cases for other initiatives (Carfax, Apple, Netflix are examples of companies using commercially-available solutions; in most cases multiple systems providers to match specific requirements with the best available tools).

We take for granted, about 1,000 times a day, just how pervasive Big Data implementations are, and how new these business models are.

Lessons Learned: Summary of Key Big Data Activities

In every day use — and just in a limited slice of those activities — we see creative uses of Big Data sets to simplify, magnify, expand and provide context to everything we do. Some of the lessons or categories include:

Leveraging Sensors — What sensors exist (everyone has a phone, a car, an internet connection) that can be leveraged?

  1. Collecting Data — What data can be sourced, and where can it be stored? What sensors already in place might turn into data sources?
  2. Aggregating Data — Where can data be stored?
  3. Visualizing Data — How can the data be simplified and provided to a customer?
  4. Comparing Data — How can we provide benchmarks, and which measures are of interest?
  5. Analyzing Data — Can we set an alert, or query more broadly the data set?
  6. Evaluating Options — What can we learn from looking at existing systems and use cases?

Use one; combine several; offer support in thinking through new ideas . . .

Take a look around your daily life. The Big Data leaders are everywhere, and they are throwing world-class ideas about Big Data at everyone. What ideas can we take and morph to our advantage?

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