Big Data And Information Privacy

The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.

2) In fact, big data’s analyses and predictions is very tough because it requires a firm masters

Big Data is garnering great recognition for its data-driven decision making methodology. Right from data acquisition where there is a flood of data available, we need to make effective decisions about usage of data. Privacy, scalability, complexity and timeliness are the problems that hinder the progress of Big Data.

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.

the ‘big Data era’ has arrived — multi-petabyte data warehouses, social media interactions, real-time sensory data feeds, geospatial information and other new data sources are presenting organisations with a range of challenges, but also significant opportunities. IDC believes that as CIOs start to adopt the new class of technologies required to process, discover and analyse these massive data sets that cannot be dealt with using traditional databases

Big Data is becoming more meaningful with the ever more powerful data technologies, which enable us to derive insights from the data and help us make decisions. Big Data also creates new courses and professional fields such as the data science and data scientist, which are aimed at analyzing the ever growing volume of data. Some might think this exaggerated because data analysis, after all, not a new invention. However, we might all agree that the progress of digitization associated with the generation of ever larger amounts of data have totally changed the ways we deal with data.

Big data is an extremely important topic for future developments, growth trends and similarities between certain things. From a Microsoft blog published in 2013 big data is “the process of applying serious computing power” (HowieT, 2013). Another article describes big data as data that “exceeds the processing capacity of conventional database systems” (Dumbill, 2012). Based on these definitions and many more alike, big data refers to or can be described as recorded information that exceeds capacity. As brief as this is, data can be recorded using many instruments and even through observation. This topic is interesting to research and develop as new technologies are more capable at storing and reading mass data. With technology advancements, a method that took half a day, more than ten years ago, would only take a couple of minutes using present technologies. As big data is getting more widely used more businesses and enterprises will be interested in the trends shown.

Big data is an emerging term which has been noticed since it influences our daily life gradually. The big data is a large concept that is vague because different people look at big data phenomenon from a different perspectives, it is not easy to make a precise definition (Moorthy, et. al., 2015). The definition of big data is a matter of debate, however, a typical reference is to the collection, management, and analysis of massive amounts of data (McNeely & Hahm, 2014).According to George et. al. (2014), big data include Internet clicks, mobile transactions, user-generated content, and social media and content from sensor networks or business transactions, such as sales queries and purchase transactions. These procedures are significant to

Understanding what big data means is really simple.” It is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it” (Big Data Analytics).Big data is being produced by everyone and every day that finding ways way to manage this data is becoming a challenge. It arrives from multiple sources or touch points such as websites, social media or apps on smart phones at a high velocity, volume and variety. “All kinds of technologies or approaches including mobile devices, remote sensing technologies, software logs, wireless sensor networks, social media etc. are used by organizations to collect big data. (issue, 2013)” Now that the meaning of ‘big data’ is clear, it’s important to know that this information is useless unless it’s processed properly with the right tools. To extract meaningful value from big data companies spends fortune; it requires optimal processing power, analytics capabilities and skills.

Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.

It is hard nowadays not to hear news about “big data”. As technology continues to grow, companies are constantly trying to leverage them to remain competitive. Scientists, governments, and even the media are now also invested in extracting big data for their uses. McKinsey Global Institute (2011) defines big data as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”. Furthermore, Barnatt (2012) explains that big data can be categorized into the three V’s: volume, velocity, and variety. Technologies like the internet, smartphones, computers, appliances, and automobiles are creating expansive amounts of data every second which contributes to the volume of data.

Social Scientists exhibit overconfidence in the reliability of the statistical data which was achieved by single or a small sampling. However, the reliability of data is mostly confined to a smaller volumes. Statistics, when dealing with larger volumes of data exhibit inaccurate results. There are many factors which affect the end results. This might be due to the improper sampling, improper handling of large volumes of data or inefficiency in analyzing the large volumes. Growing technologies are able to handle the data management and analyzing problems. Big Data, is a modern technology which can handle such large data, analyze it and can get better results.” Long before the term big data emerged, Europe already had a pioneer in the field-Alan Turing, the British mathematician who broke Nazi Germany 's Enigma code and is widely viewed as the father of modern computing and algorithms.”(Blau, 2015).

In short, Big Data refers to various kinds of data sets whose volume, velocity and complexity make it hard and merely impossible to store and mange using current architectures and databases that exist in the market. These analytic tools are designed to enable users to rapidly analyze large amounts of data.

In recent years, there has been an increasing emphasis on big data, business analytics, and “smart” living and work environments. Though these conversations are predominantly practice driven, organizations are exploring how large-volume data can usefully be deployed to create and capture value for individuals, businesses, communities, and governments (McKinsey Global Institute, 2011). Big data refers to data volumes in the range of exabytes (1018) and beyond. Such volumes exceed the capacity of current on-line storage systems and processing systems. Data, information, and knowledge are being created and collected at a rate that is rapidly approaching the exabyte/year range. But, its creation and aggregation are accelerating and will

Data is a powerful weapon as well as a resource. Having data does not make you powerful but what you do with it makes all the difference. Companies like Amazon, eBay and Netflix are already using data to predict user behavior and utilizing that to increase their revenue. But processing data in real time is not an easy task. The data today has great volume, is veracious in nature and is increasing at an enormous rate and hence has been given the term Big Data. There is a constant research going on to find a solution to process such huge amount of data in real time.