— Overview
Big data, in this essay, is not as new as the recent attention might suggest. People have long gathered data and turned it into something useful; what has changed is that the same aim now runs on digital tools. The main reason the idea has come forward, the writer says, is the growth of information technology. In 1946, in this account, the first digital computer was developed; through later generations machines became smaller and faster, and from the 1980s onward they took a form the essay calls a fifth generation, close to the computers we now use.
Those dates stay with that sketch. Hardware such as USB storage and servers also advanced, and prices and service costs fell, so that more users could run large analyses. A second factor is open source: global digital firms such as Google and Facebook, in this account, broke an older habit of keeping code closed, and more people could then run analyses of their own. Data science, close to this idea, joins statistics and mathematics with programming, in order to collect and manage data and to create value from it.
The steps, drawn from an explanation on Oracle’s site as the essay cites it, run from a broad plan, through a prepared workplace and access rights, collection and storage, exploration, building and training a model, to deploying that model. No year is given for that Oracle page, and none is added here. The writer then runs three tools. On Naver’s trend tool, five keywords — employment, changing jobs, a tight job market, study abroad, and “specs” — were compared for people in their twenties and thirties, on mobile and PC, over the three months the essay used, without a calendar window in the extracted text.
In that run, employment was the most searched term among people in their twenties; interest in employment continued in the thirties, but changing jobs stood out as a difference; “specs,” study abroad, and a tight job market showed no clear gap between the two ages. No search-volume figures are given, and none are invented. Google Ngram, for books from 1900 to 2019, showed that digital and computer were scarce until the late twentieth century, then widely used in books; technology and computer drew sharp interest in the late 1900s, then declined after 2000, in this reading because they had become familiar, while digital kept being mentioned, which the writer ties to a fourth industrial revolution and a digital age, and expects may later fall as that age matures.
Google and Amazon, hard to see on the full graph, were searched again on their own and were mentioned more often after the 2000s; Google’s mentions rose rapidly from 2000. A limit, the essay notes, is that a word search cannot tell whether amazon names the firm or a rainforest. Google Trends, which starts only from 2004, because wider internet use is relatively recent, showed Google and Amazon still rising, though Google, after a steep climb, later declined at an unspecified point; technology, computer, and digital, searched on their own, all declined from 2004.
The essay reads the fall in technology and computer, and the rise in amazon, as in line with Ngram, and the different paths of google and digital as a difference between books and web search. As a firm case, LG Household & Health Care applied a personalization tool developed by the affiliate LG CNS, with collaborative filtering, purchase-cycle analysis, and related-product analysis, and used Hadoop to process large data quickly; after the technique was applied, as the essay states it, LG more than doubled sales.
That result is left as the essay gives it, without a year and without a later official figure. This page stays with the 1946 beginning, the Ngram window through 2019, and Trends from 2004.
— Contents and key concepts
A computer from 1946, and the work of data science
Big data, in this essay, is an older aim on newer tools. In 1946, in this account, the first digital computer was developed; from the 1980s onward, machines took a form the essay calls a fifth generation. Hardware prices fell, and open source, from firms such as Google and Facebook in this account, made analyses easier to run. Those dates stay with that sketch.
Data science joins statistics and mathematics with programming, to create value from data. The steps, drawn from an Oracle explanation as the essay cites it, run from a broad plan, through a prepared workplace, collection, exploration, a trained model, and deployment. No year is given for that page, and none is added here.
Naver’s three months, Ngram to 2019, and Trends from 2004
On Naver, over the three months the essay used, employment was the most searched term among people in their twenties; changing jobs stood out in the thirties. No volumes are given, and none are invented. Google Ngram, from 1900 to 2019, showed technology and computer rising in the late twentieth century, then declining after 2000, while Google’s mentions rose rapidly from 2000. A word search, the essay notes, cannot tell whether amazon names the firm or a rainforest.
Google Trends, which starts only from 2004, showed technology, computer, and digital all declining from that year, while Google and Amazon still rose, though Google later declined at an unspecified point. After a personalization tool was applied, as the essay states it, LG more than doubled sales; that result is left as given, without a year. This page stays with the 1946 beginning, the Ngram window through 2019, and Trends from 2004. The same Korean report, at fuller length, is on CampusDown.
Sources
- Big data: an older process of turning data into useful information, now digital. Main factor: growth of information technology. 1946, as the essay states it, first digital computer; later generations smaller and faster; from the 1980s, a form the essay calls a fifth generation, close to present computers — dates left with that sketch. USB, servers, and other hardware advanced; purchase and service costs fell; access to infrastructure rose. Open source: Google, Facebook, and other global digital firms, in this account, opened code that had often been kept closed. Data science: statistics and mathematics plus programming, to collect, manage, and create value; algorithms, systems, scientific method. Steps, from an Oracle site explanation as cited, no year given: a broad plan (purpose, expected course, a later guideline); prepare the workplace and access rights and tools; collect and store, with a plan for how much and where; explore characteristics and trends; build and train a model, evaluate and revise; deploy. Fan example: a search for a fan is followed by fan ads, from search-engine personal data; worldwide live search implies a vast scale. Naver trend tool: employment, changing jobs, a tight job market, study abroad, “specs”; mobile and PC, no sex distinction; last three months as the essay ran it, no calendar window in the extract; twenties vs thirties. Employment most searched in the twenties; employment interest continues in the thirties, but changing jobs stands out; “specs,” study abroad, tight job market, no clear age gap. No volumes given, none invented. Google Ngram, books 1900–2019: digital, technology, computer, amazon, google. Digital and computer scarce until the late 20th century, then widely used in books. Technology and computer rose sharply in the late 1900s, then declined after 2000, read as familiar rather than new; digital kept being mentioned, tied to a fourth industrial revolution and a digital age, and may later fall as that age matures. Google and Amazon, low on the full graph, re-searched alone: more frequent after the 2000s; Google rose rapidly from 2000. Limit: a word search cannot tell amazon the firm from a rainforest. Google Trends: same keywords, web search rather than books; data only from 2004, because wider internet use is relatively recent. Google and Amazon rising; Google, after a steep climb, later declined at an unspecified point. Technology, computer, digital, searched alone, all declined from 2004. Fall in technology and computer, and rise in amazon, in line with Ngram; google and digital differ, likely a difference between print and web users. Firm case: LG Household & Health Care, a personalization tool from the affiliate LG CNS, collaborative filtering (CF), purchase-cycle and related-product analysis, Hadoop for fast large processing; after the technique was applied, as the essay states it, LG more than doubled sales — left as given, no year, no later official figure. This page stays with the 1946 beginning, Ngram through 2019, and Trends from 2004; no later official user or search-volume figures invented.
Last updated: 14 November 2026
Refund policy
- Change of mind / refund requested after partial use / more than 7 days after purchase
◆ Exceptions
- File errors / cannot download or open the file
◆ How to request a refund: send a 1:1 inquiry via Customer Service at the top