Taking a Look at Big Data

Every day, we produce 2.5 quintillion bytes of data. 90% of all data in the world was produced in the past two years. Data has been around forever; we have always gathered information. Paleolithic cavemen recorded their activities by carving them in stone or notching them in sticks. Egyptians used hieroglyphics to record significant events in history. The Library of Alexandria was home to half-a-million scrolls of the ancient world. Less than hundred years ago, we used punch cards to record and store information. As technology continues to evolve, the amount of data we store continues to grow. We’ve come a long way since stone tablets, scrolls, and punch cards. It’s important to understand the concept of big data and the impact is has created. This paper will define the classifications of data, explain the challenges of big data, and describe how big data analytics is being used in today’s data driven world.

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

What is Big Data? Big Data is the mass collection of user data by mathematical algorithms, databases, data mining, and the use of datasets that were once believed to be static and unusable. Big Data’s history goes way back “…70 years to the first attempts to quantify the growth rate in the volume of data, or what has popularly been known as the “information explosion” (Press, Gil).” Researchers had predicted the massive growth of information and how our ability to collect and store it would need to continue to grow as well.

Before watching Kenneth Cukier’s TED Talk, “Big Data is Better Data” I had never really heard of the term “big data” maybe only a couple of times. His TED Talk was intriguing at the fact because of this big data so much in our world today has changed already. I agree with the point that more data allows us to see more, new, and different because with only small data we would not have had some of the things we have today: finding cancerous cells, GPS, self-driving cars, and much more. For example, when you want to find someone’s location on iPhone’s all they have to do is share their location with you and by doing that it is recording all of their information for you. All of these changes and advancements in society can be a good thing, but

Big data is nothing but collecting of datasets. Organizations in current world demands data to be broken down which can used to get more high effectiveness and benefit. Big data refers to the large amounts of data which collected from various devices such as mobiles, sensors and social media etc. Generally, large amount of data have been regenerating by IT industry such as satellite data, mobile devices and etc. This data is being growing rapidly day by day and it would be referred as Big Data.

Big data is buzzword in every field of business as well as research. Organizations have found its application across various sectors from Sports to Security, from Healthcare to e-Commerce.

The industry is inundated with articles on big data. Big data news is no longer confined to the technical web pages. You can read about big data in the mainstream business publications such as Forbes and The Economist. Each week the media reports on breakthroughs, startups, funding and customer use cases. No matter your source for information on big data, one thing they all have in common is that the amount of information an organization will manage is only going to increase; this is what’s driving the ‘big data’ movement.

What does it mean to say “big data”? Big Data is more than just massive amounts of data stored together. It is more than just data delivered or analyzed fast. Meta Group’s Doug Laney described it as data that has volume, velocity, and variety (2001). This is the 3 V’s of Big Data and is widely used to define it. Additions to this definition include other V’s, such as veracity and value (XXX). What is volume? Volume could be 7 billion people speaking at once. It can be the data created by millions of Americans uploading photos, buying shoes online, or searching for the definition of Big Data. It is the volume of data being created by researchers at unprecedented amounts to chart the stars, to map the human genome, or to trend

The continuous flow of data and information flooding our lives in conjunction with further increases in technology, has created a world of endless possibilities in this day and age. The impact and influences that have been created through big data will shape our lives not only today, but well into the future. This report examines the benefits of big data and the impact it has currently having in our lives as we speak. It also explores the correlation between the lack of knowledge, security and privacy issues we are facing with big data concepts and principles today, and where we will see big data systems in the future.

“Why Big-Data Is a Big Deal”. Big-data is a logo used to describe a massive volume of both structured (is information already managed by the organization in relational databases ) and unstructured data (is information that is unorganized and does not fall into a pre-determined model) that is so large it is difficult to process using traditional database and software techniques. In most companies, the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big-data has the potential to help companies improve operations and make faster, more intelligent decisions.

Like the traditional data, big data through a series of steps that contain collection, storage and analysis to form a complete system to help both enterprises and individuals produce an optimum strategy or decision and maximize benefits in their stance. As for traditional data system, it is usually not enough accurate in analyze the phenomenon or the situation due to lack of sufficient data that results from the speed of collecting data is relatively low and the process

Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.

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

However, "Big Data" suggests something more than just an analysis of huge volumes of information. The problem is not that the organizations create high volume of data, but the fact that most of them are presented in a format consisting with traditionally poor structured form of database such as: a web-based magazines, images, videos, text documents, machine code and geospatial data . All of these are allocated in a distributed storages, sometimes even

Big Data can be understood and defined in different ways. In simple terms, Big Data is a collection of data from several sources like: traditional and digital from inside and outside of an organization that represents a source for ongoing analysis and discovery. It is a term applied to massive quantity of data that organizations can collect from their operation and that cannot be easily managed by traditional database systems (Colorado State University-Global Campus, 2016, p.1). It’s also important to understand that Big Data can be a mix of unstructured and structured data. Dumbill (2012, para. 2) states, Big Data has become viable as cost-effective approaches have emerged to tame Big Data 's three V 's of massive data. The three V 's are: