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A Day in the Life of Big Data

February 13, 2014 No Comments

Big data is being used all around us. Most of us are unaware of its influence, but it impacts our lives on a day to day basis. Certain use cases, such as home automation, haven’t been adopted by everyone but are available now. Others, such as self-driving cars, are still in development, but our days could be very similar to the following in the near future.

6:30 a.m.: Measure Workout Results

Head out on your morning run and track how far you go and calories burned as you beat your friend’s distance from last night with the data collected on your fitness band. While you’re looking at your data, check out how well you slept the night before and what your activity level was throughout the day before.

8:00 a.m.: Personalized Wardrobe

Getting ready for work, you pull out your new outfit that was custom designed for your body measurements and fashion preferences.

8:15 a.m.: Coffee’s Ready

Walking over to the kitchen, your coffee is ready, which automatically started brewing while you were getting dressed. Since you’ll be going out for coffee tomorrow morning, you use your smartphone to change the settings on the machine.

8:30 a.m.: Head to Work in Your Self-Driving Car

After merging on the freeway, you let the car take over driving as you look over your schedule for the day and respond to a couple emails. As you back into your favorite parking spot, the car automatically alerts you when you are approaching the other car parked behind you. Meanwhile, an alert pops up on your phone that its time to gets your brakes maintenanced and let’s you set up an appointment with your mechanic.

9:00 a.m.: Read Accounting Report

On your desk is a report from accounting outlining how your department can eliminate unnecessary spending based on data analysis of last quarter’s spending. The report also gives several specific ideas on how to increase output and improve ROI.

10:30 a.m. Get Offer for Favorite Starbucks Drink

You haven’t been out for coffee for a while since you’ve been so swamped from work, but since Starbucks sent you an offer for your favorite latte at your usual coffee break, you head down the street to grab a drink.

2 p.m. : Book Cheapest Flight for Business Trip

You’re visiting a client next week but need to keep travel costs down, so you hop online to a travel comparison site that gives you access to the cheapest flights and lets you know if prices are expected to go up or down in the next week. With an 80 percent chance of prices going up, you book the flight.

3 p.m. Review Gaming Results for Job Applicants

A recent round of job candidates completed a test where they were asked to complete certain tasks in a game format. Now, you are looking through the results to learn how the candidates work and how that compares to your top performers’ work style.

7 p.m.: Browse Movie Recommendations

Back home, you’re ready to relax, so with a click of a button your home automation system dims the lights and turns your TV on. You decide to watch a movie, so you start scrolling through the personalized recommendations and quickly find something that looks interesting.

9 p.m.: Review Energy Usage

At the end of the day, you pull out your smartphone to review your energy usage from the day. You set up your dryer to start in the middle of the night in order to take advantage of a cheaper rate, and adjust your thermostat’s settings a few degrees to lower your energy bill.

For some of us, some these types of technological advances may sound completely futuristic but more than likely many of these examples were strangely similar to your life already. As you can see, it’s not just large enterprises who should care about big data. Big data cloud computing and mobile devices makes it easier than ever for individuals to connect with the objects around them and take advantage of the data they produce for the better.


gil allouche 150x150 A Day in the Life of Big Data

Gil Allouche is the Vice President of Marketing at Qubole. Gil began his marketing career as a product strategist at SAP while earning his MBA at Babson College and is a former software engineer.


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