The earliest writing was cuneiform from the Mesopotamian civilizations. The writing was hard to do (reeds and clay tablets) and difficult to read (at one point over 1,000 symbols). A specialized class called dubsars, better known by the more generic term scribe, developed over time. To become a scribe required extensive training. The scribe maintained a significant amount of control on all correspondence due to the difficulties associated with cuneiform. The scribes deliberately kept cuneiform difficult to use. As a result, they became a powerful class in the ancient city states.
By around 100 B.C., cuneiform was abandoned for a phonetic alphabetic script. The alphabet was much easier to understand as letters represented sounds and groups of sounds were words. The role of the scribe continued due to the lack of literacy but they no longer enjoyed the same level of power and control. In addition, it was possible to learn to read and write without extensive training. As the means to write became easier, literacy grew. The printing press further encouraged literacy by mass producing written works. Eventually in the Western world, literacy became widespread.
A similar literacy evolution is occurring. Not long ago, the ability to analyze mass amounts of data was difficult and limited. Expensive machinery and highly trained technical staff were required. Highly trained individuals were needed to interpret the results. The barriers to enter into this field were high.
In the past few years, the volume of data has significantly increased – better known as Big Data. A host of tools are now available to analyze this quantity of data. The power of these tools continue to grow while becoming easier to use. The barriers to extensive analytic activities are falling and thus we see the recent rise of the Data Scientist.
Much like the advent of the alphabet and mass printing allowed literacy to spread, the availability of mass data and the means to analyze it are starting a new “data literacy”. In modern times, some people are more skilled at writing, but most people can write. And writing is embedded into everyday life. The Data Scientists are the new data literates who will spearhead the widespread use of analytical approaches to everyday decision making. Just like writers, Data Scientists (or whatever they are eventually named) will be the experts, but the average person will have more data analysis as part of their day to day activities.
It is intriguing to think of how this new literacy will impact the future.