Data Acquisition And Recording Of Big Data

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.

What does it mean to say “big data”? Big Data is more than just massive amounts of data stored together. It is more than just data delivered or analyzed fast. Meta Group’s Doug Laney described it as data that has volume, velocity, and variety (2001). This is the 3 V’s of Big Data and is widely used to define it. Additions to this definition include other V’s, such as veracity and value (XXX). What is volume? Volume could be 7 billion people speaking at once. It can be the data created by millions of Americans uploading photos, buying shoes online, or searching for the definition of Big Data. It is the volume of data being created by researchers at unprecedented amounts to chart the stars, to map the human genome, or to trend

In 2012, the concept of ‘Big Data’ became widely debated issue as we now live in the information and Internet based era where everyday up to 2.5 Exabyte (=1 billion GB) of data were created, and the number is doubling every 40 months (Brynjolfsson & McAfee, 2012). According to a recent research from IBM (2012), 90 percent of the data in the world has been created in the last two years alone, and Internet activity in each second today will generate more data than all the data combined in the

Definition of Big Data: “Big Data technologies are the new generation of technologies and architectures that are designed to economically extract value from very large volumes of a wide variety of data, by enabling high velocity capture, discovery and/or

Big Data is a newer term that has been introduced to the technology world. By definition, the term “Big Data” refers to large amounts of complex sets of data, their relationships and their analysis. (Electronic Privacy Info Center). It can also be defined as a “collection of data from traditional and

The “Big Data” becomes a common word now in Information Technology and Business world. These two simple English words created history and meant a ton in Global market. In past the data refers to traditional data and data volumes either in single or multiple terabyte ranges. But today it’s beyond traditional data and includes real time transactional data which is a key to the business systems.

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.

Big data refers to the collection and subsequent analysis of any significantly large collection of data that may contain hidden insights or intelligence (user data, sensor data, machine data). when analyzed properly, big data can

The amount of users’ information tends to increase every year. As can be seen in Chart 1, between 2005 and 2011 the digital information created globally had a sharp increase, reaching a peak of 1.800 billion gigabytes in 2011. The business report – big data gets personal, emphasizes that in 2012 the amount of data created reached 2.8 zettabytes and also predicts that this amount of data will double in 2015, a number that is as gigantic as it sounds. As also shown in Chart 1, about 75% of all digital

Velocity defines the continuous arrival of data streams; from this we can obtain the useful information. Furthermore improved through-put, connectivity and enhanced computing speed of digital devices has not only fastened the production of data but also the retrieval and processing of the data. Veracity provides the quality and provenance of the information in the face of data uncertainty from many different places. There are changes in the structure of the data and how users want to interpret that data. Variety indicates how to handle different types of data, i.e. source data has become diverse and complex because it includes not only structured traditional relational data but it also includes quasi-structured, semi-structured and unstructured data such as text, sensor data, audio, video, graph and many more type. Value is essential to get the economic value of different data which varies significantly. The primary challenge here is to identify which are valuable and the way to perform transformation and the technique to be applied to perform data analysis and from this we get the required knowledge [1].

So what exactly is Big Data? This can be a point of contention amongst even those who work with big data all the time so the description that follows is only one of many. Big Data is best characterised by 3Vs: volume, variety and velocity. Volume refers to the extreme amounts of data, variety to the varying types of said data and velocity to the speed at which the data must be processed. Big Data does not actually refer to a specific quantity of data as many might assume by looking at the term but it is often used when speaking about massive volumes of data in the range of Exabyte’s (Rouse, 2014), most of which cannot be integrated easily.

Now-a-days the Data usage has increased a lot. Data that the human race has accumulated in the past one decade, far exceeds the data that are available to mankind during the preceding century. They also expect that different stakeholders such as consumers, companies and businesses are likely to exploit the potential of Big Data. Several estimates about the accumulation of data have challenged our earlier imagination. Data scientists are increasingly using data quantities in Peta and Zeta bytes. There is no doubt now that

In modern times, the amount of data being stored is terrifically large. Companies must deal with such abundance of data on a daily basis in both storing and analyzing as

Initially, with the advent of computers and means for mass digital storage, we started collecting and storing all sorts of data, counting on the power of computers to help sort through this amalgam of information. Unfortunately, these massive collections of data stored on disparate structures very rapidly