What is 'Data Exhaust'

Data exhaust is the trail of information left behind as a result of a person’s digital activity. Data exhaust can be mined to create a fairly accurate portrait of a person’s daily life given that so much of our lives has a digital component.

Activity monitors and smartphones have a data exhaust that can piece together daily movements, working hours can be tracked through office applications, and social media can often fill in remaining gaps. Data exhaust as a concept is particularly interesting for marketers and researchers as it is hard data rather than self reported preferences that are prey to reporting bias. Data exhaust is big data in that it can be mined, but the data sets making up data exhaust are much larger than data sets and sources big data works with.

BREAKING DOWN 'Data Exhaust'

Digital activity may understate the volume of data that makes up data exhaust. Data is generated from every transaction, every device, and every click of a button within a system. Sometimes this data is being collected and shared back with the person that generates it, as with the results from a step tracker. However, it is equally likely that the data is being unthinkingly generated and may not be actively mined for any purpose. When it is collected with a purpose in mind, it can be combined with other sources and mined with big data techniques. There is simply too much data exhaust, however, for it all to be relevant enough to be used for purpose driven big data analysis. Although our computers and techniques are improving, there is still a processing cost to be paid that keeps data intake from including every possible data set.

Data Exhaust in the Workplace

Even just looking at a widely used office application like email, there is data exhaust such as average response time, number of bounced emails, times the program is accessed and so on. This data exhaust could be captured and combined with the data coming out of other workplace applications, access card swipes, vending machine purchases, employee social media updates and so on to paint a picture of the productivity of the office over time.

From this mass of data, insights could be teased out that offer any number of tweaks to increase that productivity. For example, what seating configuration has a positive impact on average email response time? At what temperature are people most efficient? Around what times in the day do task completion times start to slow? If this line of reasoning has you imagining a nightmare scenario where you are being constantly evaluated and experimented on, ending with you sitting in a cold corner of the office with a locked down computer watching a timer countdown in your inbox, you are not alone.

Your Personal Data Exhaust

More and more people are attempting to take ownership of their data exhaust. In this context, the data exhaust can become big data that serves you. Want to be more efficient at work? Start collecting more data on when your peak periods of productivity are and work back to things like what you ate before this period, how you slept, and even what playlist was on during your peak performance. Of course, you don’t need to stop at work.

The data exhaust that is so attractive to marketers is even more meaningful in your hands. How much time do you spend online? What is the composition of a regular day? How often do you eat out alone? How well do you stick to your budget? All of these questions correspond with established research on health, happiness and satisfaction. If you can capture data exhaust, you can start benchmarking your performance and making tweaks for a better life.

We create data exhaust almost constantly in our digitally connected world. When a marketer or researcher captures it, they can use big data techniques to better understand you and people like you. If you start capturing your data exhaust, it becomes personalized data that tells you about who you are now and can help you make those small changes that will improve things for you in the future.   

Risks Associated With Data Exhaust

As with anything related to data retention, there are risks that come with data exhaust. Sometimes knowing too much about consumers and their behavior might be detrimental to a company. For example, an insurance company may raise its rates for some customers if they can track where customers drive through or regularly park. In addition, some of the data retained may not be useful, and hanging on to it could become costly and unnecessary.

  1. Exhaust Price

    A discount price at which a broker must liquidate a client's ...
  2. Big Data

    Big data is the growth in the volume of structured and unstructured ...
  3. Data Science

    Data science is a field of Big Data which seeks to provide meaningful ...
  4. Data Mining

    A process used by companies to turn raw data into useful information. ...
  5. Demarker Indicator

    An indicator used in technical analysis that compares the most ...
  6. Exhausted Selling Model

    A pricing model used to estimate when the price floor of a security ...
Related Articles
  1. Tech

    Big Data in Financial Services Comes With Some Risks

    Big data is playing a larger role in finance but its application does not come without risks.
  2. Tech

    Data Analyst: Job Description & Average Salary

    Learn about a data analyst career and how much money you can expect to make. Understand the skills and education needed to become a data analyst.
  3. Tech

    Financial Advisors' Next Big Tech Tool: Big Data

    Here's how big data is playing a crucial role in the work life of financial advisors and some strategies on how to take advantage of the technology.
  4. Small Business

    Starting A Small Business

    Starting a small business can be a daunting task. This tutorial will break the process down into easy steps.
  5. Tech

    Common Interview Questions for Data Analysts

    Learn how to prepare for your data analysis job interview by having solid answers to these common questions that measure your knowledge and effectiveness.
  6. Tech

    Data Analyst: Career Path & Qualifications

    Explore becoming a data analyst, one of the hottest careers in the current economy; learn about the career paths and the qualifications you need to get hired.
  7. Trading

    Measuring Stock Market Sentiment With Extreme Indicators

    Pay attention to how the exhaustion principle helps technical indicators signal trend reversals when abrupt value changes coincide with high trading volume.
  8. Tech

    Common Interview Questions for Financial Data Analysts

    Learn what kinds of questions are frequently asked at job interviews for financial data analyst positions and how to give responses designed to impress.
  9. Tech

    Blockchain Could Make You—Not Equifax—the Owner of Your Data

    All hype aside, blockchain technology is really good at one thing: taking out the middlemen. Leaky data brokers' days may be numbered.
  1. How are Exhaustion Gap patterns interpreted by analysts and traders?

    Learn how to spot and interpret exhaustion gap patterns like traders and analysts do, and see why these patterns are considered ... Read Answer >>
  2. How effective is creating trade entries after spotting an Exhaustion Gap pattern?

    Understand the components of the exhaustion gap pattern, how and why it occurs, and how it can be used to create an effective ... Read Answer >>
  3. How do I build a profitable strategy when spotting an Exhaustion Gap?

    Learn potentially very profitable trading strategies traders use to take advantage of a market reversal after identifying ... Read Answer >>
  4. What are the main differences between a Runaway Gap and a Exhaustion Gap?

    Discover the primary differences between runaway and exhaustion gaps, and see why gap differentiation depends on subsequent ... Read Answer >>
  5. Why is the Stochastic Oscillator important for traders and analysts?

    Understand how and why analysts and traders consider the stochastic oscillator a useful tool for anticipating trend exhaustion ... Read Answer >>
  6. How effective is creating trade entries after spotting a Sanku (Three Gaps) Pattern?

    Learn about the sanku, or three gaps, pattern including formation, interpretation and additional confirmation necessary to ... Read Answer >>
Hot Definitions
  1. Call Option

    An agreement that gives an investor the right (but not the obligation) to buy a stock, bond, commodity, or other instrument ...
  2. Standard Deviation

    A measure of the dispersion of a set of data from its mean, calculated as the square root of the variance. The more spread ...
  3. Entrepreneur

    An entrepreneur is an individual who founds and runs a small business and assumes all the risk and reward of the venture.
  4. Money Market

    The money market is a segment of the financial market in which financial instruments with high liquidity and very short maturities ...
  5. Perfect Competition

    Pure or perfect competition is a theoretical market structure in which a number of criteria such as perfect information and ...
  6. Compound Interest

    Compound Interest is interest calculated on the initial principal and also on the accumulated interest of previous periods ...
Trading Center