Cluster reduction. The story of Rumpelstiltskin was about a weird little man with the ability to weave raw hay into gold.  Well, there may be a bit of truth in that old story, as leading organizations today are learning to weave raw data into business gold.Â, We understand that when raw oil is refined into high-octane fuel, the refined high-octane fuel is 16.9x more valuable than the raw oil.  But how much more valuable would that barrel of high-octane be if that fuel never depleted, never wore out and could be used over and over again across an unlimited number of use cases?Â. This is because it is similar to a lump of clay with no identity and also of no practical use. In honor of the Theoretical Law and Economics Conference, to be held at the Yale Law School December 7-8, 2012 and sponsored by the Oscar M. Ruebhausen Fund, here are some of the best places to find economic data 1. empirical economics research using text as data. Answer: Continuous Series. collected from a source. Raw data is a term used to describe data in its most basic digital format. To create value out of oil, oil must first be refined.  For example, when raw oil (West Texas Crude) is refined into high-octane fuel (VP MRX02 high-octane racing fuel), the high-octane fuel is 16.9x more valuable than the raw oil[1](see Figure 1). Definitely, we need … Comprehensive-Raw data are large and entangled, whereas classified data are comprehensive and easily manageable. In other words, a variable is a characteristic or a phenomenon which is capable of being measured and changes its value over time. It is represented exactly as it was captured at its source without transformation, aggregation or calculation. Generally, we can do this by distributing data into various classes on the basis of some attribute or characteristic. One key point to remember is that an attribute is qualitative in nature i.e. Finally, one must apply Data Science to quantify the attribution of the use case’s business and operational value to each of the contributing data sources (see Figure 6). A variable is classified into two: A discrete variable’s value changes only in complete numbers or increases in jumps. This process is usually thought of as producing a “golden record” for each cluster. Transformation, normalization and standardization of data elements. To do so, an investigator has to classify the data in the form of a series. For example, converting from Euros to US Dollars. This is to ensure that we are comparing apples to apples in our analysis. we cannot measure an attribute in quantitative terms like 5, 1, 2 etc. Archives: 2008-2014 | The origins of indifference analysis can be traced back to the work of late 19th Century Irish economist Francis Edgeworth, and later, to Italian economist Vilfredo Pareto. Secondary sources repackage primary-source data … 1 Like, Badges  |  And for those folks who need a refresher on some economic basics, check out my blog “. Of course not. Report an Issue  |  Revise With the concepts to understand better. More, The Big Data craze caught fire with a provocative declaration that “Data is the New Oil”; that data will fuel the economic growth in the 21, ; to give the Big Data conversation an easily recognizable face.  The Economist recently declared data “. Now learn Live with India's best teachers. This is because it is similar to a lump of clay with no identity and also of no practical use. This qualification is further of two types: Unlike qualitative classification, quantitative classification allows numerical division of data into classes. It is important to realize that organized data facilitates comparison and meaningful conclusions. Raw crude oil goes through a refinement, blending and engineering process where the crude oil is transformed into more valuable products such as petroleum naphtha, gasoline, diesel fuel, asphalt base, heating oil, kerosene, liquefied petroleum gas, jet fuel and fuel oils.  This is a critical process that needs to be performed before the downstream constituents (like you and me and industrial concerns) can actually get value out of the oil (as gasoline or heating oil or diesel fuel).  Oil in of itself, is of little consumer or industrial value.  It’s only through the refinement process that we get an asset of value (see Figure 2). Typically, raw data tables are much larger than this, with more observations and more variables. 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