Big Data And Analytics Analysis

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

Businesses are struggling with the rapidly increasing volume, speed and variety of information being generated today -- what 's come to be known as big data. Companies are seeking technologies that not only help them process and manage all that data, but tap into it to develop insights about the markets they compete in as well as their own performance within those markets.In addition to the growth in importance of analytics and its prospects for the future, other central themes emerged, including the varied ways in which analytics is structured and managed within these enterprises.

Big data is anything which is too large for traditional databases to handle. They range from Terabytes of data to petabytes of data. Big data is generated from various sources, such as social media networks, oil wells, mobile phone conversations, weather data etc.

Big data is a term that describes a large volume of data. This data comes in the form of structured and unstructured data. Structured data is information taken and sorted in rows and columns while unstructured data is pictures, tweets, videos, and location-based data. It is not surprising to see many businesses today utilizing data for financial gain. Businesses are harnessing data and using it to make investment decisions, marketing strategies, fraud reductions, and much more. These businesses and organizations can expect to become more profitable, effective, and efficient, but pushes the limits

What is big data? Big data is structured and unstructured data that is difficult to process using traditional database and software techniques. This is because of its extensive size. Big data ranges “from a few dozen terabytes to many petabytes of data in a single data set – and are constantly growing” (Hopp). A terabyte is equal to 1,024 gigabytes, while a petabyte is equal to 1,024 terabytes. A regular iPhone has 16 gigabytes, so a terabyte contains the same amount of digital storage as 64 iPhones, while a petabyte contains the same amount of digital storage as 65,536 iPhones! Structured data is in a fixed field within a record or file (usually databases or spreadsheets). Unstructured data is unorganized and hard to interpret by traditional databases or data models (like photos, webpages and emails). Structured data is a lot easier to work with and can be easily classified, so it is preferred in big data over unstructured data.

According to google big data is defined as, “Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions”. Big data has taken off with the use of cloud computing. Though they sound the same, the main difference between cloud computing and big data is the cloud is the actual infrastructure while big data is the actual content you will see in the database. Today’s industry is built on information, the more information a person can get to know about you, the more they can use to their advantage. A good example of this is the shirts you buy off an online retailer. If you have information and trends that show you may get suggestions similar to that brand with recommendations or even get promotional coupons depending on how much information you have given to this company about yourself. These companies with their powerful databases can look at an individual user making this concept very powerful in today’s market. According to Ularu, Puican, Apostu, and Valicanu (2012), “IBM’s view Big Data has four aspects: Volume… Velocity… Variety… Veracity.” These are all determined from the how big the size and complexity of each set of data. Volume is the

When you hear the word “big data” what it is that first comes to your mind, a straight forward answer would be huge amount of data ranging between tens or hundreds of peta bytes to few zeta bytes of data. In a way, Big Data is not just about the amount or volume of data but one way it is about deriving business value from a range of new and emerging data sources, including social media data, location data generated by smart phones and other roaming devices, public information available online and data from sensors embedded in cars, buildings and other objects — and much more besides. Another way to define big data would be a 4V model wherein Vs stand for Volume, Velocity, Variety and Veracity. The next question that pops in would be what led to this huge pile of data, well certainly days or months or years is

Big Data is a term for very large amounts of formal and informal information that can be analyzed to find trends and patterns. The information can be about anything, but it needs to be processed in a way that will give it value and relevance. It can come in multiple formats and from different sources such as large databases, electronic records, social media, mobile phones, apps, wearable devices such as pedometers, and others. Different data sets are combined and contrasted in different ways to give perspectives and insights about a topic. It can be used in a seemly endless number of ways and people are discovering new ways to use it all the time, some of them entertaining. The largest areas of use include those relating to consumer behavior and choices, business procedures, healthcare, science and research, and law enforcement. People are also discovering its use in their personal lives as well for things like buying a home, dating, fitness routines and travel.

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.

Big Data refers to the large amounts of data that businesses deal with on a day-to-day basis. Big Data can be defined in many ways, but this is one of the most general definitions. One of the primary uses businesses have for Big Data is to provide assistance for decision making. In order for Big Data to be effective, organizations must utilize the data to their advantage. The quality of information is what matters, not the quantity. Organizations may have virtually unlimited amounts of data to work with, but they must locate the helpful portions of data in order for it to be effective and serve its purpose. In addition, some data may not be helpful at the present moment in time, but will be needed for analysis in the future (“What Is Big Data?”,

A very simplified way of looking at big data refers to, “the sheer mass of data produced daily by and within global computer networks at a pace that far exceeds the capacity of current databases and software programs to organize and process” (Dewey, "Big Data"). The world of big data has evolved primarily from the business intelligence and analytics field of information technology. Big data and big data analytics involve big data sets. The information that is stored requires unique ways of holding and organizing the data in order to process it correctly. Common methods of data storage are just not possible. The internet has added to the amount of data that can be captured. With the ability of advertisers to utilize technologies to capture user information through web interfaces, the sheer magnitude of information that can be kept is staggering. All of this information can be put to use by any number of businesses and governments (Chen, Chiang, and Storey, "Business Intelligence and Analytics: From Big Data to Big Impact."). The ability to direct or channel all of that information opens unbelievable doors to virtually any organization. All kinds of organizations would benefit including businesses, governments, schools and hospitals (Dewey, "Big Data"). “Big data may be as important to business –

Big data refers to the large amount of data that is impossible to handle by using traditional or conventional methods such as relational databases or it is a technique that is required to handle the large amount of data that is generated with advancements in technology and increase in population. Big data helps to store, retrieve and modify these large data sets. For example, with the advent of smart technology there is rapid increase in use of mobile phones due to which large amount of data is generated every second, so it is impossible to handle by using traditional methods hence to overcome this problem big data concepts were introduced.

Big Data can mean different things to different people/organisations – one organisation’s big data of a few terabytes may seem small compared to another organisation’s big datasets in petabytes or exabytes. Big Data is typically described by the following characteristics, known as the “5 Vs”:

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