Personal Information in a modern, Digital Age:: 8 Works Cited
Length: 1790 words (5.1 double-spaced pages)
In the past when you wanted to purchase goods you could go to the store, pick up your items, pay and leave. While these activities are still possible, more and more today we find ourselves pressured to get “savers cards.” Modern businesses, like never before, track who you are and what you are burying in an effort to be able to better serve you and become more efficient. While great for the companies implementing these policies, what does it mean for your privacy, and your wallet?
Now more than ever our lives are electronically based. People can access their banking information over the Internet, setup all kinds of funds transfers, as well as purchase and sell items. Our consumer lives are being tracked, and that information sold to other businesses. Business communicate and sell their consumer lists with each other.
Data is one of the most important corporate assets of companies, governments and research institutions. It is now possible to have fast access, to correlate information stored in independent and distant databases, to analyse and visualise data on-line and use data mining tools for automatic and semi-automatic exploration and pattern discovery. (acs)
This opens the door for a new kind of scam for a new age, identity theft. If someone were able to pass themselves off as you, they could effectively become you, for the purposes of getting credit, making large purchases, or even committing crimes.
After collecting this data it is entered into what is called a data warehouse. Companies and governments store all of their accumulated in their data warehouses. Data warehousing is defined as
A collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. Development of a data warehouse includes development of systems to extract data from operating systems plus installation of a warehouse database system that provides managers flexible access to the data. The term data warehousing generally refers to the combination of many different databases across an entire enterprise. (webopidia)
Today businesses accumulate all the data they can gather into a data warehouse, from which they can do data mining. This means that when you go to the grocery store and use your saver card, to get the tiny percent off, that store tracks what you buy and enters it into their data warehouse.
This allows them to later go through that information and look for trends, to see what products are popular what time of year, and what you are most likely to purchase. This information can then be used to plan what to stock in their store when. Even how to layout what products should be placed near other products. The act of looking through the data warehouse is referred to as data mining.
[Data mining is] a class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. For example, data mining software can help retail companies find customers with common interests. The term is commonly misused to describe software that presents data in new ways. True data mining software doesn't just change the presentation, but actually discovers previously unknown relationships among the data. Data mining is popular in the science and mathematical fields but also is utilized increasingly by marketers trying to distill useful consumer data from Web sites. (webopidia)
Since companies keep their customer databases a secret from each other, many copies of your personal information are on record in many places. This means that there are now many chances for someone to steal your information, false information to accrue, or to just use it for bad purposes. Having personal information in others hands is always a risk, but it is up to the individual to decide how much they feel is appropriate.
Examples of identifying information which can be used to locate or identify an individual include an individual's name, aliases, Social Security Number, e-mail address, driver's license number, and agency-assigned case number. Non-identifying personal information includes an individual's age, education, finances, criminal history, physical attributes, and gender.11 The main concern with aggregating such personal information and mining it is that profiles of individuals can be created using information held in disparate systems located both in the commercial and government sectors. (nascio)
A companies data warehouse can be further combined with radio frequency identification tags, or RFID tags. These are used like bar codes, for businesses to track their products. However, unlike bar codes the RFID tags can be scanned from a distance. Meaning now individual cans of soup inside a box, on a palate being shipped, can be individually tracked. This means, possibly, great things for businesses, as they can now become more efficient, by being able to track even small quantities of their products.
These dust sized RFID chips are capable of transmitting their own SKU (Sales Keeping Unit), the same info currently encoded in barcodes, distances of up to 20 feet to an "RFID Reader". But that's not all these diminuitive little chips can do. They are capable of sending a unique serial number that can identify the item it's embedded in - down to it's date and location of manufacture. Barcodes were limited to carrying information that identified classes of products. RFID carries information equivalent to the product DNA, while allowing a number for every item on the planet! (privacynotes)
This type of technology is currently being used by some of the largest retailers on the planet (including Wallmart) and down to their suppliers. It allows them to track their products on a level never before even dreamed of. To the end consumer this means even lower prices, less stock outs, and more of the products you want. Companies can keep track of their products at a previously unheard of level. This enables greater shipping, and much greater reliability. This does have a downside, however, in that companies now know more about you than ever before.
At the very least, the Internet has made it far easier for anyone to obtain not only someone else's birthdates and Social Security numbers but also liens, lawsuits, divorces and other personal and potentially embarrassing -- but technically public – information. (seattlepi)
Furthermore, it may become dangerous for companies to become too reliant on the information in their data warehouses. Somewhere along the chain of collecting and buying information, some of it may become stale, or may just be inaccurate. If a company was to make a decision based on this, wrong, information, it might have disastrous consequences. “The effect of this bad data may not be felt until much later. Whenever the company explores this data to identify patterns or tendencies, the presence of bad data can skew the results” (zdnet).
Another possible worry of businesses is that they might collect too much data, or assume that just because something appears to be related to something else, that they are in fact caused or at all related. “Most businesses already perform these data gathering tasks to some extent -- the key here is to locate the data critical to your business, refine it and prepare it for the data mining process” (about). Since the reason for data warehousing is to then use the data for data mining having too much data means that there is more that must be sorted through. Too much data may take too long to be analyzed, or may show strange relationships that may not occur. The goal is to find meaningful trends, not just any trend.
In the short term it seems that data warehousing and data mining will enable companies to branch out and serve niche markets better than ever. “the results of data mining will be in profitable, if mundane, business related areas. Micro-marketing campaigns will explore new niches. Advertising will target potential customers with new precision” (utexas). While in the long term data mining may enable individuals access to information before figured too technical, or difficult. “data mining may be as common and easy to use as e-mail. We may use these tools to find the best airfare to New York, root out a phone number of a long-lost classmate, or find the best prices on lawn mowers” (utexas). Data mining has a great future ahead of it, and as of yet, we have only scratched the surface of its capabilities.
It is very important for individuals to know that their personal information is being collected in this manner, and since it can be put at risk, and to opt out if they feel it necessary. It is up the the individual to decide how much information collecting is enough for them. It is also necessary for companies to keep track of the data they have collected to be sure that the data are still valid. The possibility of thinking data is accurate, and basing decisions off of it, is probably much worse than not having had the data in the first place.
Data mining combined with data warehousing is a powerful tool for business as it enables greater efficiencies, better service, and lower costs. However, some people might not like the amount of information that is gathered about them. The privacy implications of this technology are high, as are the business gains. This technology opens up a new dimension for business. No longer will companies have to guess about future trends, as with data mining, the trend should become apparent.
During the research for this assignment I have learned that companies really do track an incredible amount of your consumer buying habits. I had no idea the world of data warehousing was this vast and prevalent. Data warehousing is a fairly recent development as computers that are powerful enough to track the information, and analyze it have only become recently available. This technology is still only in the realm of large business, as it is too expensive for small companies to be able to afford. The risks could be considered large, from possibly alienating your customer base, but the rewards are probably even higher.
Data Warehouse (n.d.) Retrieved March 12, 2005 from http://www.webopedia.com/TERM/D/data_warehouse.html
Valentine, Mike (n.d.) The Coming Privacy Storm Over RFID Chips Retrieved March 12, 2005 from
Data Mining (September 2004) Retrieved March 12, 2005 from https://www.nascio.org/nascioCommittees/privacy/data mining.pdf
Privacy (n.d.) Retrieved March 14, 2005 from http://seattlepi.nwsource.com/business/154986_privacychallenge02.html
Privacy in Data Mining (August 1999) Retrieved March 12, 2005 from http://www.acs.org.au/nsw/articles/1999082.htm
Fisher, Tony (February 9, 2005) Data monitoring from the pilot's seat Retrieved March 13, 2005 from http://news.zdnet.com/2100-9592_22-5569538.html
Chapple, Mike (n.d.) Data Mining: An Introduction Retrieved March 15, 2005 from http://databases.about.com/od/datamining/a/datamining.htm
Alexander, Doug (n.d.) Data Mining Retrieved March 11, 2005 from http://www.eco.utexas.edu/~norman/BUS.FOR/course.mat/Alex/