Current Trends Of Data Mining

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

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Companies and organizations all over the world are blasting on the scene with data mining and data warehousing trying to keep an extreme competitive leg up on the competition. Always trying to improve the competiveness and the improvement of the business process is a key factor in expanding and strategically maintaining a higher standard for the most cost effective means in any business in today’s market. Every day these facilities store large amounts of data to improve increased revenue, reduction of cost, customer behavior patterns, and the predictions of possible future trends; say for seasonal reasons. Data

Data, Data everywhere. It is a precious thing that will last longer than the systems. In this challenging world, there is a high demand to work efficiently without risk of losing any tiny information which might be very important in future. Hence there is need to create large volumes of data which needs to be stored and explored for future analysis. I am always fascinated to know how this large amount of data is handled, stored in databases and manipulated to extract useful information. A raw data is like an unpolished diamond, its value is known only after it is polished. Similarly, the value of data is understood only after a proper meaning is brought out of it, this is known as Data Mining.

Several explanations were given about the buzzword “Big Data”. Big Data describes a process in which “serious computing power” is applied to “seriously massive and often highly complex sets of information” (Microsoft Research, 2013). Big data is also defined as a cultural, technological, and scholarly phenomenon” based on three elements such as Technology, Analysis and Mythology (Boyd and Crawford, 2012). The first reason behind the quick expansion of Big Data is the extensive degree to which data are created, shared and utilized across the organizations and virtual networks formally and informally in the recent times. Digitization, that is, the transformation of analogue signals into digital ones, reached massive popularity in the early 1990s. The data-information-knowledge-wisdom hierarchy offers an alternative view, according to which information appears as data that are structured in a way to be useful and relevant to a specific purpose (Rowley,

The world is changing with respect to the growth in big data and to the way in which it is used. Growth in big data brings with it many challenges, but it also presents new opportunities. Figure 1, helps understand some of the big data related activities that are taking place in the world with respect to volume of data that is being consumed by these activities over the next 5 years.

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 is defined as “large data sets or to systems and solutions developed to manage such large accumulations of data, as well as for the branch of computing devoted to this development.” (“Big Data”) This definition of big data was not added to the dictionary until 2014. The next big thing in business analytics is a relatively new, yet, explosive business practice known as data mining: the collection and analysis of big data. (Fayyad) These large, seemingly random, sets of data are condensed and analyzed for patterns and trends by people with a very broad set of skills. These people are known as data scientists and are considered unicorns in today’s job market.

You may have heard the term “Big Data” often these days and the importance of analytics attached to it. The availability of good data set and analytics of it provide organizations ability to understand consumer behavior and future prospects. This has now become an essential part of every business operation. Data itself is not a new thing to humans, written records have been in existence since 4th millennium BC. What has changed recently is that with digital inventions and significant growth in internet access, most people are on the electronic grid for longer periods and spending lot of time on emails, messaging, entertainment and social media applications. This huge growth in data generation has given birth to the concept of

Big data is not a hype, but it is the future. The big data industry continues to advance, and big data service providers are making it easier for companies to work with big data in driving their businesses. Progressively, greater volumes and varieties of data will be incorporated with more business processes to support better decision making and greater insight. Moreover,

The variety, volume and velocity (Lohr, 2012) of data have evolved in the present contemporary times with various companies and business embracing the benefits and advantages leveraged out of Big Data and its plethora of real life applications. This concept have taken a huge leap ahead in time and have find some innovative and creative ways to collect, store and analyze data which his enormous these days. The realm of e business and its applications in this industry are conquered by the means of big data.

The data stored in data warehouse will not provide any benefit to the organization until the hidden information is extracted from it. There are various way to extract the data, however data mining is the best method to get the meaningful trends and patterns from the data warehouse. Therefore, data mining can be defined as the method of extracting the valid, comprehensible and previously unknown information from the huge storage to use on the decision making process (P. 1233).

Big data refers to large data sets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze. Big data is used to analysis the

In the last few years the global marketplace has seen exponential growth in data volume. Every day people create unstructured large datasets of different types such as GPS coordinates, payment transactions, web data, e-mails or smart meter values that are termed as "big data" \cite{nasscom}.