The Pros And Cons Of Big Data

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

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

Despite the potential challenges, it is still believed that big data is the new way of the world, and that businesses should aim to overcome these challenges. The first typical challenge small businesses will face is finding “talented people who know big data and analytics” (Taylor, 2012, para. 6). Unfortunately, since small business owners tend to not be familiar with big data, then they will be challenged to know how to use it. Big businesses have the money, reputation, and influence to hire people who are very knowledgeable with big data. Also, if the storeowner is technologically challenged, it’ll be even harder for him/her to know how big data can help him or even what big data is in order to go out and look for someone to help his/her store with big data. Even if the storeowner is comfortable with technology and is familiar with big data, the storeowner could be averse to change, and that would be another reason why using big data would be a challenge for this category. The storeowner who is used to doing things a certain way will not be eager to start using big data to improve his business. S/he will probably think that if the business is doing well, then they don’t need to change. This will prevent them from increasing profits and will stagnant them from keeping with current times and current technology. For

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.

Big data is sprouting up everywhere and using it appropriately will drive competitive advantage. Ignoring it will simply put an organization at risk, and cause it to fall behind its competition.

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.

Industry is thriving to capture the flood of data present today. Every sector has millions trillions of data which is increasing with extreme velocity to be handled. Social media has been fueling up data growth exponentially. Although human race has been generating data for thousands of years but recent decade has put forward a new

‘Big Data’ is a new innovation. Processing big data and converting it into useful information can result in many benefits to a company such as increase its profitability, improve their business practice. Companies do spend lots of resources to harness this new technology. “Google Spent $7.3 Billion on its Data Centers in 2013. (Miller, 2013)” Big Data is regularly being generated by our activities such as surfing internet, using social media, blogs etc. Every digital process leaves a trail of information about consumers and their behaviour. These consumer behaviour and purchasing patterns can be used to visualize information. The big companies use big data to improve their customer’s

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.

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.

In comparison to the traditional business intelligence, big data does provide major improvements. Traditional business intelligence is top down approach whereas big data is bottom up and empowers end users with a valuable analysis thus enabling them to take prompt and smart business decisions. The value generated from big data analytics is applicable to all sectors. The advantages of big data analytics are huge but it also raise serious concerns

ig data is a large amount of data, structured as well as unstructured, that records or entails information about business on a daily basis (“Big data: What,” n.d.). This huge amount of data contains information about different aspects but not all this information is important to us, therefore, mining for information through such a large amount of data is a very important step. Most of the time, the magnanimity of such data is so much that it is difficult to process it using conventional database and software programs (Beal, 2016). In this age of modernization, the fame and popularity of the term “Big Data” is constantly increasing. Owing to its renown and eminence, Oxford English Dictionary added it in 2013 and it also appeared in Merriam-Webster’s Collegiate Dictionary (Dutcher, 2014).

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.

Big data is critical for businesses and marketers. At the same time, big data can be a big mess without an intelligent plan. In my opinion, data for data’s sake doesn’t do any

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.