Algorithms For Dummies

 

   

  PART 4 

 Struggling with Big Data

The veracity characteristic helps the democratization of data itself. In the past, 

organizations hoarded data because it was precious and difficult to obtain. At this 

point, various sources create data in such growing amounts that hoarding it is 

meaningless (90 percent of the world’s data has been created in the last two 

years), so there is no reason to limit access. Data is turning into such a commodity 

that there are many open data programs going all around the world. (The United 

States has a long tradition of open access; the first open data programs date back 

to the 1970s when the National Oceanic and Atmospheric Administration, NOAA, 

started releasing weather data freely to the public.) However, because data has 

become a commodity, the uncertainty of that data has become an issue. You no 

longer know whether the data is completely true because you may not even know 

its source.

Data has become so ubiquitous that its value is no longer in the actual information 

(such as data stored in a firm’s database). The value of data exists in how you use 

it. Here algorithms come into play and change the game. A company like Google 

feeds itself from freely available data, such as the content of websites or the text 

found in publicly available texts and books. Yet, the value Google extracts from the 

data mostly derives from its algorithms. As an example, data value resides in the 

PageRank algorithm (illustrated in Chapter 11), which is the very foundation of 

Google’s business. The value of algorithms is true for other companies as well. 

Amazon’s recommendation engine contributes a significant part of the compa-

ny’s  revenues.  Many  financial  firms  use  algorithmic  trading  and  robo-advice, 

leveraging freely available stock data and economic information for investments.