Big Dat A New Buzzword

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.

Big data describes large scale data sets which are analyzed, using algorithms, to determine and eventually predict patterns in human behavior, interactions and the environment (oed.com). Big data is used by government entities to protect against terrorism as well as commercial entities for marketing. Big data needs ethical standards to prevent violations of four central principles, which are privacy, confidentiality, transparency, and identity (Richards 395). Big data is awareness and empowers those who control it. This revolution in information enables companies to shape consumer identity by influencing every interaction the user has with their service. Due to its predictive and persuasive nature, restrictions are necessary for consumers to

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 is a term to describe the 2.5 quintillion bytes of data that we create each day. There are many ways that the big data is collected and used; some types may be good, and some might not. As we read the book “Too Big to Ignore” by Phil Simon, you will see this is a controversial debate inside of the book. The book talks about whether big data collection is good, such as data mining or bulk data collection. In the story, it tended to lean towards the side of agreeing with the use of data collection.

Technology companies are using big data to analyze millions of voice samples to deliver more reliable and accurate voice interfaces. Banks are using big data techniques to im- prove fraud detection. Health care providers are leveraging more detailed data to im- prove patient treatment. Big data is being used by manufacturers to improve warranty management and equipment monitoring, as well as to optimize the logistics of getting their products to market. Retailers are harnessing a wide range of customer interactions, both online and offline, in order to provide more tailored recommendations and optimal pricing.96

Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as

Big Data is the act of compiling large sets of data based on a single individual or groups. Everyone encounters data in their daily life--you are experiencing it when you log onto a social media account, when you stream entertainment online, or even when you are online shopping. When you do any of these things you are leaving behind a digital trace that can be accessed by just about anyone. In “Six Provocations for Big Data,” danah boyd and Kate Crawford raise questions regarding the nature of Big Data. What is considered public information? What is the ethical way to go about retrieving data from online sources? Is Big Data more harmful or helpful? How often do you encounter Big Data, or data in general? What is the relationship between data

Big data is an interesting concept, in which people use data to analyze trends, patterns, and associations and make use of these revelations to predict outcomes. You are using data every day that is being recorded to identify people’s desires and requests, and more specifically your desires and requests. Big data is used in retail, government, healthcare, car companies, and education, basically everywhere. Big data can allow for great advancements and prevention in all aspects of life, more specifically in healthcare. Big data is important to healthcare, because it can allow professionals to identify who has a greater risk of a disease and thus allows early detection and prevention. It allows tracking which medicine is more effective than the other. It allows for healthcare providers to have better records and accuracy in each and every patient. Big data is important to healthcare and here is why.

What is Big Data? Big Data is the mass collection of user data by mathematical algorithms, databases, data mining, and the use of datasets that were once believed to be static and unusable. Big Data’s history goes way back “…70 years to the first attempts to quantify the growth rate in the volume of data, or what has popularly been known as the “information explosion” (Press, Gil).” Researchers had predicted the massive growth of information and how our ability to collect and store it would need to continue to grow as well.

Big Data is defined as extremely large data sets that can be used to analyze and compute to reveal patterns and trends, and associations. The US first started to collect data through the First Census and crop yields to track our harvest and how to improve on it. Today we do the same thing but on a much larger scale. In 2011 we hit 1.8 zettabytes of data generated in that year, that is 1,000,000,000,000 gigabytes of data we have to analyze and compute, and it was estimated to quadruple in 2013. The reason we continue to generate more and more data every year is through the technology we have today and the information that they record and transmit to us. Now we have finally come up with a name for this, Internet of Things. The internet of things is every device that can connect to the internet and transmit data, these thing can range from your: car, phone, fridge, thermostat, smart watch, computer, etc. Big Data today will be measured in 3 fields volume, velocity, variety. Volume how big the data actually is, how many zettabytes how much space and energy does it cost to have this volume. Velocity how fast we can analyze this data and put it to good use as well as how fast can transfer such volume of data from one location to another. Lastly variety, since the volume of data is so enormous we have and equally wide variety ranging from cat videos on the internet to private leaks to research and scientific papers written

Big data is nothing but collecting of datasets. Organizations in current world demands data to be broken down which can used to get more high effectiveness and benefit. Big data refers to the large amounts of data which collected from various devices such as mobiles, sensors and social media etc. Generally, large amount of data have been regenerating by IT industry such as satellite data, mobile devices and etc. This data is being growing rapidly day by day and it would be referred as Big Data.

Big data is a relatively recent concept in the marketing world that describes the process of analyzing massive data sets to uncover trends. The data sets are so large that it would be almost impossible to find such trends without high-powered analytical technology. Big data has been facilitated by the ability to gather massive amounts of information about consumer profiles and shopping trends. The primarily facilitators of big data collection are credit card companies and online companies like Google and Facebook that track people's purchasing and computer usage patterns. Big data has been used in a lot of different industries to revolutionize everything from health care to manufacturing to government (Manyika, et al,

The term “Big Data” has been around for quite some time and has been catching everyone’s attention with remarkable speed. A plethora of questions do pop up in our mind sometimes. What is big data, is this something absolutely new, how can it be leveraged to create value for an organization and so on. For many years, companies have used various transactional records stored in relational databases to make competitive business decisions. But how long can we sustain or depend on these traditional methods of doing analysis and coming to a conclusion. There is an ocean of non-traditional, less structured data such as weblogs, social media, email, sensors, and photographs that can be mined not only for useful information but also to make strategic decisions.

Big data is not as new as many people believe it to be. It is actually a concept that has been around for almost a century. It is just the “same old data marketers have always used, and it’s not all that big, and it’s something we should be embracing, not fearing” (Arthur). In 1944, Fremont Rider “predicted that the amount of data in the world would increase exponentially” (Hopp). Rider was right on target with his prediction seventy years ago. Data has grown much greater than he probably could have ever imagined back then.

Big data analytics is the use of advanced analytic techniques against very large and diverse data sets. Data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low-latency are termed as big data. Big data comes