Big Splash of Big Data

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Zhiyao Wang's picture

Introduction

Unleashing the value of “big data” has become the buzz around us in recent years. However, not only the story of data growth could be traced back thousands of years, also the development of ways human beings extracting value from data has a long history. Therefore, what brings us the enthusiasm for big data? -- It is no other than the emerging predominance and the explosion trend of massive datasets. According to a BCG report, the quantity of information generated from the dawn of time until 2003--about 5 Exabytes--is now created every two days. [1] It should not surprise us much that Google deals with more than 400PB data every month, and Taobao, an e-commercial website originated from China, has a daily sales of 5.2 billion, generates 20TB of data per day—actually, we are now witnessing this prosperity in digital era.

 

More and more sectors have already embraced the opportunity brought by big data and begun to taste the first juice of grapes on the Alps. [2][3][4] And some skeptics who saw an over-hyped route to riches—having been burned, perhaps, by their own costly, complex and ultimately disappointing efforts to turn data into dollars—are increasingly becoming believers. They are no longer asking whether big data can generate value for them but how it can do so. [1]

 

What is “big data”? How much it is hype and how much it is reality? Could it really increase competitiveness and productivity? How? Whether it will only be a flash in the pan or it will have a brilliant future? What are the trends of its development? These interrelated questions are what this article attempts to tackle, and hopefully it will offer some insights in viewing this irresistible trend in our society.

 

 

Refresh Big Data

 

The word “data”, comes from the old Latin word “dare”, means “something given”. Obviously, as human beings, we are observing and being observed every day. We record what we observed in certain formats under certain standards, therefore we obtain sets of values of qualitative or quantitative variables—that’s, again, what we call “data”. Then, what scale of the data is so-called “big”?—the Oxford English dictionary gives the definition: big data-- data sets that are too large and complex to manipulate or interrogate with standard methods or tools. Therefore, although the absolute numbers of data will grow over time, the standard manipulate methods, for example the computer architectures and algorithms, will be the determinant for whether the data sets are really “big”.

 

According to the above definitions, it is not difficult for us to understand the essence of “big data”: thanks to the technological development, we are now capable to conduct in-depth observations of the world by different powerful and convenient digital tools. These observations serve a good purpose for us to discover the world and the dynamic society where we live in.

 

On the other hand, when talking about data, we are actually talking about the ways which we applied to generate value,i.e. data analysis. There’s much controversy that big data is with high volume but low value because we are lacking of advanced data analysis technologies to realize its potential. However, if we view back to the history, we will find that the technology of data analysis always develops together with the data collection technology and keep a dynamic balance.Take evidence-based decision making for example, a systematic and rational approach is required to researching and analysing available data to inform the decision making process. As a branch of evidence-based decision making, evidence-based medicine(EBM) serves a good example to illustrate the evolution of data analysis. The old testament outlines how King Nebuchadnezzar II ordered the children of royal blood to eat only meat and wine for three years (around in 605 to 562 BC). Daniel requested that he and three other children be allowed to eat only bread and water. Danial and the three children were noticeably healthier and more vivacious than those who were relegated to the wine and meat diet. This, the first record of clinical trial, can be considered the embryo of evidence-based decision making. In the following thousands of years, more and more clinical trials are designed in order to observe certain pre-set parameters, together with the development of statistics. From single-center to international multicenter trails, clinical practise data over the world has grown in exponential; from the paper-based medical record to the electronic medical record (EMR), data collection technology provides standardization and convenience; from the basic “stating numbers” to business intelligence/ data mining (e.g. SAS is broadly employed in clinical trial analysis)—the seed of EBM sowed. Now, came to the era of big data, remote patient monitoring technology and activity monitoring systems like Nike+ are providing us much more possibilities. Like what google did about predicting flu epidemics, these new trend of big data may even bring evidence-based medicine further to evidence-based prevetion.[exhibit 1 ]

 

Exhibit 1: The Intelligence Continuum, from Gartner[5].

 

Eventually, unlike last centuries when we observed only what we thought most important, we are going to convince us not to fully trust our previous believes. Big data analysis is nothing about pre-set thinking model but much about exploring model. Feasibility, although challenge enough, if we decide to explore proactively, we are capable to develop advanced exploring model algorithm to extract value from big data.

 

Win with big data

 

After identifying the essence of big data, it is not hard to understand the Gartner’s quantification model about big data—volume, variety, velocity and complexity.[5] With regard to volume, the large quantity of in-depth observations which are open to everyone could create transparency not only for sectors but also customers. On the subject of velocity, the ever-changing observations provide timely updates which may cause huge differences from second to second. As for variety and complexity, big data is a double-edged sword for business—they present challenges for data analysis but also provide huge opportunities for innovation.

 

Afterwards, the most significant part of leveraging big data that offer the transformational potential to create value is the reaction of every sector. How will the organizations change to adapt? What competitiveness will they gain from process improving? [exhibit 2][exhibit 3]

 

Exhibit 2.

Value

Competitiveness

Example

Global Standardization

Data transparency will create an open-accessed database globally which provide sectors opportunities to evaluate their performance in an international standard. Those who are leading global standards are gaining core competitiveness.

ICHOM, an NPO which analyzes and raises global standards of treatment, is using integrated electronic medical record throughout the world. Clinics and hospitals will improve their performance according to the global standard which will bring more benefit to patients.

Better and Faster Decision Making

The market is changing quickly, big data analysis acts as monitor to the market and provide business real-time evidences. Sophisticated auto algorithms exceed human judgement.

The automative industry is broadly employing proactive after-sales maintenance service for automobiles through the use of networked sensors.[2]

New Promotion Channel

Companies which are going to adopt cutting-edge marketing and promotion strategy will own larger customer pool.

Social media and location data facilitate marketing campaign—digital coupons will be sent to customers according to their location and transaction performance.

 

Exhibit 3.

Value

Productivity

Example

New Business insight

Accessing massive data will bring new insight to businesses, new customer group and niche marketing will be identified.

Adagio Teas, an on-line customazation tea shop profit from creating new product based on customer preference.

Optimize operating process

Cost saving, cut time to market and improve quality.

Pharmaceutical companies apply sencor monitoring and real-time management system for investigation products in order to minimize R&D overage and improve cut time to market.[6]

 

 

Seize the trends—let the market speak

Identifying the promising future of big data is just the first step in deriving value from it. As stated above, the crucial basis is what actions sectors going to take, including the radical refreshed mindsets and approaches. Nevertheless, it is also known to all that currently big data shows certain deficiencies in privacy protection. Moreover, some may argue that evidence-based decision making brought by big data is too young to shake the deep-rooted decision making practise. My answer is: let the market speak. When more and more customers are willing to sharing their data on websites which shows superiority on privacy protection; when the surprising seed of evidence-based decision making sprout at more companies—the invisible hand will change everything. 

References: 

1. Opportunity Unlocked: big data’s five routes to value. Access by:
https://www.bcgperspectives.com/content/articles/information_technology_...

2. Big data: the next frontier for innovation, competition, and productivity. Access by:
http://www.mckinsey.com/insights/business_technology/big_data_the_next_f...

3. Challenges and opportunities. 11 February 2011 VOL 331 Science www.sciencemag.org
4. Challenges and opportunities with big data. Access by:
Http://docs.lib.purdue.edu/cctech
5. Pattern-based Strategy: Getting value from big data. Access by:
http://my.gartner.com/portal/server.pt?open=512&objID=202&mode=2&PageID=...
6. www.novartis.com