Applications for Big Data Analysis

Big data analytics can be used by company to make informed business decision by examining large amount of varied data to get customer preferences, market trends and other useful information. Company can use it to explore new revenue opportunities, improved operational efficiency, better customer service and competitive advantages over rivals.

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

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

Big data analytics is the process of checking and handling large data sets which normally contains variety of data types. Through handling these data it helps to know the patterns and even the correlations which are not known. Handling of the large data sets also helps in knowing the market trends and even in knowing what the customers prefer. The information which these data analytics gives are important information for business. Most of the surveys which have been done have shown that big data analytics have revolutionized supply chain. Most companies and

Big data is the present most-liked theme of today 's technology. These research goes through all description of techniques and technologies of extracting of the data, storing of data, distribution of data, analyzing of data, managing of data with high velocity and from the structured data and helps in the handling of the extreme data. Big data has the presentation the capacity to improve predictions, saving money and enhancing the decision making process in the fields of the traffic control, weather forecasting, disaster prevention, fraud control, business transaction, education system, health and the national security.

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.

Big data analytics is the process of comprising, organizing and analyzing large sets of data called big data to discover, design and extract other useful information.

Abstract - Considered as another subversive technology revolution in IT other than Internet of Things and cloud computing, Big Data has the most valuable property. Its value hides in the great storage that needs to be analyzed while cloud computing merely serves as a method or a step to save and store the messages. As rapidly increasing attention is drawn on in recent years, Big Data has wider and wider influences in many fields. With the explosive demands on Big Data analytics, Big Data broadened its definition from an IT term of extremely large data sets to a set of new technologies.

Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. And big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses. More accurate analyses may lead to more confident decision making. And better decisions can mean greater operational efficiencies.

Let us start by defining Big Data. Big Data is the term for datasets that are too big to process in traditional ways such as databases and simple analytics software. The size of big data is a moving target as storage and processing capacities grow. Because these datasets are so big (100 petabytes if you are Facebook for example) when working with them, you face a few challenges: storage space, searching, analysis, and

Every year the data transmitted over the internet is growing exponentially. By the end of 2016, Cisco estimates that the annual global data traffic will reach 6.6 zettabytes. The challenge will be not only to “speed up” the internet connections, but also to develop software systems that will be able to handle large data requests in optimal time. For the definition of the Big Data, there are various different

Big Data has taken the business world by storm. By 2020, it is expected that the amount of digital information in existence will have grown from 3.2 zettabytes in 2014 to 40 zettabytes. Companies are doing all they can to capture this digital information and turn it into actionable insights. Currently, the total amount of data being captured and stored by industry is doubling every 1.2 years. Therefore, companies must find increasingly efficient solutions to store and analyze this incredible amount of data.

The emergence of new technologies, applications and network systems makes it hard to run the current business models and huge data types, and thus emerged various types of analytic tools like Big Data, which make this work easier by way of proper organization of data. Big Data is all about analyzing different forms of data (Structured, Semi-structured and Un-structured) and it is not about the procedure, creation or consumption of data.

arouse mainly because data is asset to Organization , analyzing data is inexpensive and 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