The Importance Of Big Data

Big data analytics is the process of analyzing large data to find useful information such as improving efficiency of business, market trends, customer’s preferences, information of competitors, and other useful business information. According to the IT Glossary, “Big Data is high-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” In other words, it is an abundant array of information used to acquire insights and make business decisions.

What is big data and how is it defined in today’s modern world? In 2001 Doug Laney Articulated what Big Data meant and this has become the industry standard for the idea. (SAS, 1) More accurately he described the three main attributes that defined Big Data. Laney articulated this idea during a period when Big Data was in its infancy. The amount of Data that could be stored did not allow for the level of analysis that is now common practice fourteen years later. This level of analysis is both changing the way we do business and changing the way we save lives. The amount of data collected from social media alone has completely revolutionized the marketing world allowing for targeted marketing campaigns at certain demographics. Laney described big data in three ways. (SAS, 1)

They used facts and arguments from various sources, such as studies and authors. As they are introducing the topic, they use the ideas of Lev Manovich to justify their argument that the name “Big Data” can be misleading. Manovich observed that Big Data has been used to refer to data sets large enough to require supercomputers, yet large amounts of data can now be analyzed on much simpler computers. Boyd and Crawford contend that the value of the industry does not simply come from the large data sets, but the “patterns that can be derived by making connections between pieces of data…” By relating Manovich’s idea, their argument made more sense. As computers become more advanced, bigger data sets look much simpler. But the connections Big Data makes are still valuable, no matter how advanced computers

Now that we have figured out how to harvest the free and ubiquitous big data, the next huge challenge is to figure out how to analyze and display the information in a useful and meaningful way. The big question today is how you present big data in a way that human beings can quickly understand and make decision. Most big corporations and government entities are drowning in a pool of their own data, because they lack the corresponding manpower to understand the data and extract meaningful knowledge out of it (Bizer, Boncz, Brodie, & Erling, 2012).

Many times it is the responsibility of the community to speak out about problems. Communities are “the only effective power that can limit consumption, pollution, and the degradation of nature” (Ehrenfeld 21). A program such as Neighborhood Watch is a good example of people coming together on a community level to fix and prevent problems.

Big Data is becoming more meaningful with the ever more powerful data technologies, which enable us to derive insights from the data and help us make decisions. Big Data also creates new courses and professional fields such as the data science and data scientist, which are aimed at analyzing the ever growing volume of data. Some might think this exaggerated because data analysis, after all, not a new invention. However, we might all agree that the progress of digitization associated with the generation of ever larger amounts of data have totally changed the ways we deal with data.

A very simplified way of looking at big data refers to, “the sheer mass of data produced daily by and within global computer networks at a pace that far exceeds the capacity of current databases and software programs to organize and process” (Dewey, "Big Data"). The world of big data has evolved primarily from the business intelligence and analytics field of information technology. Big data and big data analytics involve big data sets. The information that is stored requires unique ways of holding and organizing the data in order to process it correctly. Common methods of data storage are just not possible. The internet has added to the amount of data that can be captured. With the ability of advertisers to utilize technologies to capture user information through web interfaces, the sheer magnitude of information that can be kept is staggering. All of this information can be put to use by any number of businesses and governments (Chen, Chiang, and Storey, "Business Intelligence and Analytics: From Big Data to Big Impact."). The ability to direct or channel all of that information opens unbelievable doors to virtually any organization. All kinds of organizations would benefit including businesses, governments, schools and hospitals (Dewey, "Big Data"). “Big data may be as important to business –

Big Data is has been around in Information Sciences since the 1990s. Over the past years, the amount of data we create, communicate and store has grown exponentially. Big Data is already a big influence on our lives. Whether you contribute to the ever-growing dataset of Facebook or your supermarket gives you discounts for items you never expected to need , Big Data is all around us and has an impact on all of us.

Big Data is the extremely large datasets that their sizes are beyond the ability of capturing,

Five years ago, few people had heard the phrase ‘Big Data.’ Today, it’s hard to go an hour without seeing it implemented practically in our daily life. The promise of a highly accurate data-driven decision-making tool is an attractive lure for any organization in any industry. However, big data is not without its own problems.

Although we hear the term ‘big data’ frequently now, the true definition of big data does not seem to have a singular, agreed upon definition. Depending on who you ask, big data can mean many different things. What would seem to be the most intuitive definition of ‘big’ data is not necessarily the correct one. Though the size of the data is an important aspect, it is not always the defining factor. According to Dell EMC’s video, Big Ideas: How Big is Big Data, big data is “any attribute that challenges the constraints of system capability or business need.”1 Will Hakes, Co-Founder and CEO of Link Analytics, claims that big data cannot be defined in precise terms and is, effectively, a “rallying cry.”2 Hakes does, however, agree that any

The way big data is used these days is to gather deep and useful information about people’s behaviour and sentiments. According to Katina Michael and Keith Miller - “Organizations use various analytical techniques— from crowdsourcing to genetic algorithms to neural networks to sentiment

The term big data came into the picture to refer the big volumes of information’s both the companies and governments are storing. The data may be where we live, where we go, what we buy and what we say etc. all will be recorded and stored forever. More than 90% of data is generated in the past 2 years only and this volume is increasing day by day and doubling for every two years. In this world, the organizations are using the data generated by us and no one knows what they are doing with the collected data. Big data is defined as a lot of structured and unstructured data from different sources, such as E-commerce websites, online transactions, social networks, medical records, internet search indexes, banking and financial services, scientific searches, weblogs, and document searches and so on. Big data also can be described by four V’s: Volume, Velocity, Variety and finally Value.

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

When Big Data meets Computer Networks , designing and managing the IT infrastructure become a non-trivial and a challenging task .