Security Factors Of Big Data Analytics

As defined by the magazine, CQ Researcher, big data is the collection and analysis of enormous amounts of information by supercomputers (CQ Researcher, 1). This collection and analysis has led to many great feats in the fields physics, medicine, social

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

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.

According to Investopedia, Big Data is, “The growth in volume of structured and unstructured data, the speed at which it is created and collected, and the scope of how many points are covered. Big

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.

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

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

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.

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.

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 a broad term for data sets so large or complex that traditional data processing applications are inadequate. Big Data focus more on finding new correlations of massive of data sets not only the causation. Big data as a term maybe new, but many IT and business analysts have worked with huge amount of data in various industries for years.

Data itself is useless, until it is mined and transformed into a valuable source of knowledge discovery. Due to its conversion into useful information, data mining has become the leading source being used in many fields worldwide. “Data mining is based on complex algorithms that allow for the segmentation of data to identify patterns and trends, detect anomalies, and predict the probability of various situational outcomes.”[1] Many organizations from healthcare to multimedia and more are relaying on data and getting developed through the use of it. Regardless of how, data warehouse changed its rhythm and dimension in terms of measurements such as: variety, volume and velocity. Today, one can see the current trends of data mining in different fields such as social networks, healthcare and businesses. As data mining is giving the opportunity for those fields to get advanced, "Big Data" is also opening up new doors within itself as the new trends emerge.

The Hadoop based batch processing is a powerful tool for analyzing data offline. But it fails to process anything in real time. Highly sensitive situations like crediting card fraud detection, networking fault prediction; threat detection and so on cannot be postponed for an offline analysis. Situations like these need instant results because if something is not done to mitigate a potential threat in real time, the damage may be catastrophic.

Firstly it repersents the volume attribute lot of data sizes which are explained numerically. For example, users of YouTube uplosds new vedios every minute of a day in 48 hours. Second is taht the velocity is other attribute of big data. When data is sensetive for time the velocity attribute exists. Further data can be structured or unstructured then it brings the 3rd attribute named as velocity. Moreover, validity is another factor for big data. Data can be logical is defination of validity. Further more, is veracity which means conformity of facts and accuracy. Lastly, visibility is also a big data charactrstic. When data is seprate from other resources it can be seen.