The analysis of big data is the process of organizing, collection, analyze and examining the large volume of data to find patterns, market trends and useful information. This analysis helps organizations to better understanding about the information within data, and helps analyst to make better
This article offers a view of the technical and non-technical requirements of making big data a successful endeavor for an organization. To achieve this goal the 10 step process if big data is defined, the data mining technologies are reviewed and data platform issues are briefly discussed.
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.
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.
Therefore, the consecutive sections discussed the definition of big data, tools for analyzing big data, data mining, knowledge discovery, visualization and collaborative
Firstly, the main problem is deciding which data should be selected. The data, explaining customers’ desires and needs, is important to be collected while most of the enterprises are confusing about what data they should concentrate on. A recent Gartner report (2014) stresses that 64% of firms raced to plan or launch a Big Data project, though they did not have enough professional knowledge yet. To understand what customers need through Big Data possibly turns into the core of companies’ target. The large data volumes and different varieties of data lead to data complexity.
Big Data is defined as data sets that are so large that they defy conventional applications, frameworks and methods for analyzing them. The proliferation of Big Data is attributable to the amount of data companies across all industries are capturing on transactions with suppliers, customers, distribution channels and services organizations over years of activity. Big Data, by its very nature of spanning a multitude of databases and conventional data storage platforms within organizations, becomes difficult to capture, store, search and complete analytics on. For the manager in an organization who has these conventional methods of data search, analytics and visualization available to them, Big Data can quickly become overwhelming given the limited scope of tools available and the sheer amount of data available (Jacobs, 2009). For the manager attempting to gain greater insights into their organization's processes, strategies and overall performance, Big Data can quickly becoming overwhelming. The intent of this analysis is to provide guidance to managers on how they can better manage Big Data to provide the maximum analytical insight and intelligence about their organizations.
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.
Data is the backbone of business today and has always played a critical role in business. Today in the era of “Big Data” and Digital Business, data has become the primary driver of decision making, growth and innovation. The big data today is radically different from the data of yesterday. The Big Data age has brought with it a tremendous increase in the amount of data and types of data available to businesses. New data is produced every day, generated by social networking sites, mobile phones, location, third party, business transactions, etc. We are in an era which is characterized by the 5 V’s of Big Data: Volume, Velocity, Variety, Veracity and Value. The Big Data opportunities are enormous, as are its challenges. In this context it is especially important to understand the Opportunities and Problems that business faces to extract value from Big Data Analytics.
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
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
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.