Big Data, Who Are You?

Big Data, Who Are You?

Copyright: © 2019 |Pages: 27
DOI: 10.4018/978-1-5225-7609-9.ch001
(Individual Chapters)
No Current Special Offers


When you hear “big data” probably you think like most, to a rather heavy file that includes diverse information, or a real iceberg that hides a large portion of its real mass. But we have not to think so about big data. Yes! You can worry about it. But you can very well choose to see it as a potential which allows you to create value. I would say even more that you must choose to take advantage of this large amount of data! Data or big data are primarily a way to segment your target. It is a collection of information that is analyzed, processed, and arranged to be profitable. So, do not let data phobia hold you back, just keep calm because this first chapter gives you an overview of what the concept big data encompasses, and you will realize by yourself that it is an exciting field.
Chapter Preview


Data! data! data!, he cried impatiently. ‘I can’t make bricks without clay’

Sir Arthur Conan Doyle (1892). (Adventures of Sherlock Holmes, p.289)

You have probably seen it yourself in magazines, on TV or even heard by your friends, the term “Big Data” is now more than ever a fashion word. But what lies behind this little vague concept? An explanation is needed. The concepts behind big data are actually nothing new because data existing over the time, but what makes it so important is the rapid rate and different types in which it is produced in recent time. This brings us to say that data become big: it is “big data!”. In another word, big data is the new form of data which seemed to come back to presenting old wine in a new bottle.

Data has grown from kilobytes (KB) to petabytes (PB). This huge amount of data is referred to as big data and requires advanced tools and software for processing, analyzing and storing purposes. This phenomenon has radically changed the way data are collected and analyzed since it introduces new issues concerning volume, velocity and the variety of data.

I already hear many people questioning the impact of big data and the risk of restricting the creative process. Think again! We should rather see big data as a support for creation. The data will never dictate how to produce creative content, but it can clearly indicate what it should contain in order to capture the interest of events and generate value. People in the business context no longer have to depend on their intuition to ensure the success of their creations. They now have at their disposal a tool that supports them, and which has a much weaker bias.

So should we be afraid of big data or should we exploit it? Between those who think that it is a time saver and a factor of considerable growth and those who are against the exploitation of the data because they consider that it is a violation of their private life; the answer can be found and discovered by yourself by reading this chapter.

Because the new business revolution is based on these data, these billions of tiny pieces of information that allows reinventing, to adapt and to redraw all businesses and services, provided that we can draw useful information and create a minimum of readability in this galaxy of data. This is the real challenge.

Big data is the revolutionary word in today’s world because of its influence on several domains. It is said everywhere that it is the future and that you have to start exploring big data as soon as possible. All right, but where do you start? What to learn? How to extract value from a large volume of available data? Which technology must you adopt? And so on.

Rather than propose an endless inventory types formations, with titles that will maintain this sense of key buzzwords, we preferred to discuss the big data overview: How and why did we get there?

It is by having a better vision of what big data is that you will deduce by yourself what you must look for to become an ace of the subject. Especially, what you need to learn by yourself. This chapter will clarify what big data really is, where it comes from and how it is processed.


Not Only Big But All About Data

Nowadays it does not take much to convince managers or decision-makers alike of the importance of data for their business activities because most of the business activities are associated with the use, the understanding and the exploiting of data (Sedkaoui, 2018a). “Data is everywhere”, “data is the new oil”, “digital oil”, “data is power” … words are diverse and do not miss to describe the importance of ‘data’.

Real atom, data are, over the time, at the heart of thinking about new business strategies, and often the fantasy of all business models for its value. So why suddenly the term ‘data’ is in every conversation and many research are published on the subject throughout the world? What has changed so much and justifies such enthusiasm sometimes verging on collective madness?

Key Terms in this Chapter

Analytics: As emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain, and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

Big Data: A generic term that designates the massive volume of data that is generated by the increasing use of digital tools and information systems. The term big data is used when the amount of data that an organization has to manage reaches a critical volume that requires new technological approaches in terms of storage, processing, and usage. Volume, velocity, and variety are usually the three criteria used to qualify a database as “big data.”

Data Analysis: This is a class of statistical methods that make it possible to process a very large volume of data and identify the most interesting aspects of its structure. Some methods help to extract relations between different sets of data, and thus, draw statistical information that makes it possible to describe the most important information contained in the data in the most succinct manner possible. Other techniques make it possible to group data in order to identify its common denominators clearly, and thereby understand them better.

Hadoop: Big data software infrastructure that includes a storage system and a distributed processing tool.

Information: It consists of interpreted data, and has discernible meaning. It lies in descriptions and answers questions like “Who?” “What?” “When?” and “How many?”

Yottabytes: A unit of data storage, equal to one sextillion (102 4 ) bytes.

Data: This term comprises facts, observations, and raw information. Data itself has little meaning if it is not processed.

Small and Medium Enterprises (SMEs): Are companies that fall under specific legal limitations regarding the number of employees and the annual turnover. However, this differs from one country to another.

Algorithm: A set of computational rules to be followed to solve a mathematical problem. More recently, the term has been adopted to refer to a process to be followed, often by a computer.

Zettabyte: A unit of data storage, equal to one sextillion (10 21 ) bytes, one trillion gigabytes, or one billion terabytes.

Knowledge: It is a type of know-how that makes it possible to transform information into instructions. Knowledge can either be obtained through transmission from those who possess it or by extraction from experience.

Open Data: This term refers to the principle according to which public data (that gathered, maintained, and used by government bodies) should be made available to be accessed and reused by citizens and companies.

Internet of Things (IoT): The inter-networking of physical devices, vehicles, buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data and send, receive, and execute commands. According to the Gartner group, IoT is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment.

Complete Chapter List

Search this Book: