Big Data And Its Opportunities

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

Inspired in part by MapReduce, Hadoop provides a Java based software framework for distributed processing of data intensive transformation and analytics. The top three commercial database suppliers Oracle, IBM, and Microsoft have all adopted Hadoop, some within a cloud infrastructure.

According to the article, 2.8ZB of data has been created and replicated in 2012. The proliferation of devices such as PCs and smartphones worldwide, increased Internet access within emerging markets and the boost in data from machines such as surveillance cameras or smart meters has contributed to the doubling of the digital universe. IDC projects that the digital universe will reach 40 ZB by 2020, an amount that exceeds previous forecasts by 14%. Thus, data is not narrowed to big only; it is actually huge. Like, 40 ZB data is the equivalent of 1.7 MBs of new information created by the every single human for every second of the day. Developing countries like China and India are currently covering 36% of digital universe; the prediction says it will be increased up to 62% by 2020. So the companies will have numerous scopes to dig out more data and analyze them as per their requirement. Despite the unprecedented expansion of the digital universe due to the massive amounts of data being generated daily by people and machines, IDC estimates that only 0.5% of the world’s data is being analyzed.

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.

Not only the development of Big Data brings big opportunities, but it also brings big

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.

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

“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.

The “Big Data” becomes a common word now in Information Technology and Business world. These two simple English words created history and meant a ton in Global market. In past the data refers to traditional data and data volumes either in single or multiple terabyte ranges. But today it’s beyond traditional data and includes real time transactional data which is a key to the business systems.

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

Big-Data can be defined as the large amounts of digital information companies and governments collect about human beings and the environment we are living in. The amount of data that is getting generated is expected to double every two years,

Today data is being flooded in all means as it is being collected in unprecedented ways. Decisions which were taken by way of guesswork and difficult models can now be made on the base of data itself. Big data analysis can be dream on every aspect of today’s society - Mobile services, manufacturing, retail, life sciences, financial services and physical sciences. Big Data has the potential to revolutionize scientific research, education, use of Information

Thought behind the motivation of the author is throw insight on Big Data its emergence, necessity, essence etc. In this paper the fact that everyone are a part of big data is been mentioned, web is the main source of data. Big data is defined as quintillion bytes of data His exact words are given as “Big Data is the fuel. It is like oil. If you leave it in the ground, it doesn’t have a lot of value. But when we find ways to ingest, curate, and analyze the data in new and different ways, such as in Watson, Big Data becomes very interesting.”Tools that are used to nalyse the big data such as Google BigTable ,Hadoop and MapReduce that revolutionized the organizations has been discussed. Parallel and distributing computing model and the importance of 7 V’s (volume, velocity, veracity, validity, variety, volatility, variety) in finding the true value of Big data has been discussed

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: