Understanding What Big Data is

Understanding What Big Data is

The rapid emergence, prevalence and potential impact of Big Data is sparkling a significant amount of interest amongst Information Systems/Information Technology (IS/IT) industry and research. The concept of Big Data is true due to the inescapable significance of our capability to create and collect digital data at an extraordinary scale. 

Big Data is present around since 2005, when the term Big Data has been adopted from O’Reilly media. The increasing number of people, devices, and sensors that are now connected by digital networks (i.e., Internet of Things) has generated a vast amount of data. Accordingly, the great potential of Big Data is for both academics and practitioners and has become clear. In the business world, companies are leveraging technologies related to Big Data is effective for decision making, efficient business operations, and maximum business impact. According to McKinsey report, government administration in developed economies could save more than $149 billion in operational efficiency improvements alone by using Big Data. In short, Big Data is a solution to provide managers with the ability to make informed decisions that are based on evidences rather than making arbitrary decisions which are largely dependent on their intuitions and subjective judgments.


In other words, Big Data is an advanced information technology that allows users to capture, communicate, aggregate, store and analyze massive amounts of data. However, the value of Big Data largely depends on what types of software tools are available, what sizes of datasets are common in a particular industry, and their use in general (i.e., the way one is using it along with purposes). Despite the rapid emergence of Big Data technologies, empirical research in this domain is still quite limited. In addition, many organizations are still not aware about Big Data analytics along with their capabilities, benefits, and also challenges. Empirical research conducted by Russom showed that only 28% of respondents understand the concept of what Big Data is and have name it, most of them (around 85%) being from developed countries. Moreover, despite the numerous evidences showing Big Data is advantageous, its implementation and adoption in developing economies is still very limited and surrounded by a variety of challenges. 

Although Big Data is a serious problem just a few years ago, now it is considered as business opportunity. Using Big Data is a provider for organizations competitive advantage to differentiate themselves from others, and this can help them uncover people’s hidden behavioral patterns and even emphasis on their intentions. It can also eliminate the gap between what people want to do and what they actually do in addition to how they interact with others and their environment, which helps directly in decision-making. Previous research also showed that data-driven decision making is associated with higher productivity, profitability and market value. Indeed, companies that use data-driven decision making may enjoy 4% higher productivity, 6% greater profitability, and 50% higher market value. In addition, Big Data is analytics can positively impact product development, market development, operational efficiency, customer experience, and market demand predictions. With the rapid explosion of data, benefit for the government from the Big Data is by creating a system that collects and analyzes vast amount of data coming from different sources to help them in tracking criminals, preventing money laundering as well as improving homeland security. 

McKinsey Global Institute argued that five new kinds of value might come from Big Data

  1. Creating transparency in organizational activities that can be used to increase efficiency. 
  2. Enabling more experimentation to discover needs, expose variability, and improve performance. 
  3. Segmenting populations in order to customize actions.
  4. Replacing/supporting human decision making with automated algorithms.
  5. Innovating new business models, products, and services.

However, while Big Data is a yielder of extremely useful information, it also presents new challenges with respect to how much data to store, how much this will cost, whether the data will be secure, and how long it must be maintained. Big data is a  presenter of new ethical concerns. In fact, one of the major challenges of Big Data is preserving individual privacy. In their study, Agrawal et al. also identified many technical challenges with which Big Data is associated. These technical challenges include scalability (i.e., data volume is scaling faster than compute resources), heterogeneity (i.e., data comes from different sources), lack of structure (i.e., data must be carefully structured as a first step in -or prior to- data analysis), error-handling (i.e., data cleansing and error correction), timeliness (i.e., the larger the data set to be processed, the longer it will take to analyze), and visualization (i.e., present results in powerful visualizations that assist interpretation). Big Data is an adoption and is also facing several other managerial and organizational challenges. These managerial and organizational challenges include inadequate staffing skills, lack of business support, organization culture, and resistance to change.

Common Aspects related to Big Data

Over the past two decades, Big Data is related to the analytics and technologies have become increasingly important in both the academic and the business communities. Findings of this study revealed that Big Data is at a fancy stage and so is business analytics exploitations by companies. Both start-up and leading enterprises are not fully aware of what Big Data is and business analytics technologies along with their benefits and outcomes. Despite their general lack of awareness, we have observed that some organizations in Jordan have implemented some sort of business analytics including Database Management Systems (DBMS) and Google analytics. The value that can be derived from the analytics of Big Data is different from what traditional data analytics can offer.

In an IBM study, it has been discovered that over half of all defendants contemplate their datasets that are between one terabyte and one petabyte to be Big Data. This includes more than three-quarters of midsize companies. However, it has been established that size alone does not matter; Big Data is also about an extraordinary diversity of data types, delivered at various speeds and frequencies. Big Data is defined as “any dataset that cannot be managed by traditional processes and tools, any line that outlines “big” and “small” data is arbitrary because the key characteristic is that the data has a greater volume than the current data ecosystem can manage”.

Security has been emphasized as one of the main issues in Big Data is adoption literature Privacy is another huge concern, and one that increases in the context of Big Data. Another literature perspective adds, “We, however, face many challenges, such as legal, privacy, and technical issues regarding scalable data collection and storage and scalable analytics platforms for security”. Thus, securing both data and communication is really vital for Big Data providers and consumer. “Security and privacy are part of the main challenges when implementing Big Data”. Policy makers have long struggled to draw the line for ethical data use, the discussion has historically revolved around the definition of “sensitive data.” Yet, any attempt to exhaustively define categories of sensitivity typically failed, given the highly contextual nature of personal information. The technologies of Big Data is rising, business innovators are thrilled about the prospective benefits they are able to generate from the design and development of a wide range of new products and services based on the size, variety, and velocity of information available raises new questions. Some of those questions are about the implications of the acquisition, storage, and use of large quantities of data about people’s attributes, behavior, preferences, relationships, and locations. Ethical concern is the most sensitive topic. It is a big risk…providers may sell your data to advertisers. This may result in an unwanted intrusion to your life by others; a one big reason I advocate “permission based marketing. Unfortunately, there are no clear ethical standards in the world of what Big Data is although this is much needed now. 

Corporate culture is a significant organizational factor that impacts the adoption and implementation of what Big Data is. The corporate culture has huge influence not only on Big Data adoption but also on any novel IT initiatives. Chance to succeed in adopting Big Data is significantly higher in a given company if it enjoys a culture that supports technological innovations. 

Implications Related to Big Data

Understanding What Big Data is

The lack of awareness about Big Data is an important need for extensive workshops and conferences to fulfil this significant gap as well as to emphasize on the benefits and the importance of riding the Big Data wave as it is the way to future. Furthermore, the need to stress on the importance of pursuing the study of data sciences and analytics amongst high school students and undergraduates considering continuing their education since data scientists are huge assets to any developing country as well as the need to include Big Data courses in business and ICT majors in universities to ensure the planting of seeds to a fruitful future of Big Data.

There is a deep need for an intermediary to facilitate and assist in the implementation of what Big Data is in organizations and Big Data is integrating with the rest of the business processes and technologies. There should be more motivation for startups of Big Data is to be established to help in this aspect so more companies would adopt Big Data.

Big Data is concerned with the environment that should be aligned with organizational security and privacy requirements. Security measures need to be implemented so as to ensure the privacy of information.

The lack of focus on the customer needs and desires in companies has been noticeable where the use of Customer Relationship Management (CRM) tools was limited and performance was mainly measured strictly by revenue figures, whereas the core of successful Big Data is the implementation is always keeping the customer in mind and always caring for what is best for the customer. The need for the customer alignment with business models.