This is the age of big data. Data is becoming an ever more important part of everything from banking to marketing. The information that is produced by the computers used in these activities is huge, it is constantly being refreshed, and it continues to grow as more is collected. But what are the questions we should ask when we think about what makes big data so different from traditional methods of analysis? We’ll talk about five key characteristics that aren’t always considered when talking about big data analytics.
So which of the following characteristics about big data isn’t true? The first one is “It’s expensive.” In order for a company to collect and analyze large amounts of data it generally needs to buy or lease computers with multiple high-speed processors, thousands of gigabytes of memory, and a network that can cope with the massive amounts of storage needed. These types of systems can be very expensive to operate and maintain. Furthermore, many firms with such a large data set up cannot afford to keep them up-to-date because of the cost involved.
The second, which of the following characteristics about big data analytics is not true? The third is “In the future everyone will use big data.” While certain technologies like HD and 3D scanning do make their presence felt right now, it’s still a ways away from becoming a primary means of data collection for most people. It’s not only expensive to collect data with current technologies; it is also extremely inefficient and wasteful, since much of the data collecting takes place while people are sitting in front of their personal computers. This leads to a situation where companies must either spend enormous amounts of money collecting data that doesn’t yield much positive results or spend even more time gathering data that simply won’t yield.
Another, which of the following characteristics about big data analytics is not true? The fourth is “Data is messy.” Most large-scale data sets contain hundreds, sometimes thousands, of unrelated factors which can lead to a lot of unnecessary confusion and even inaccurate calculations. Today’s sophisticated computer programs make it far easier to take care of the complexities inherent in large-scale data sets; as a result today’s computers can handle large volumes of data with far less mistakes than they did a decade ago.
The fifth, which of the following characteristics about big data analytics is not true? The sixth is “No one cares about your business.” While it is true that most people don’t give a thought to the inner workings of their car when they leave the garage, the same is increasingly true about big data. While some people may not care about your business, the amount of time people spend on their smartphones and social media accounts makes it clear that they do care. As a result, you want to put a great deal of thought into how you develop your social media strategy so that you can ensure that people are aware of what is happening within your company.
The seventh, which of the following characteristics about big data analytics is not true? The eighth is “Big data is expensive.” Even if you use a server with a tremendous amount of storage capacity, it will not be very useful if you have a low cost of purchasing the same data that drives your CRM or ERP program. Today, the trend is toward using more affordable, lower-cost solutions in the place of traditional, high-cost software solutions. While it may cost you more initially to get started, the long-term savings that you realize on purchasing cheaper, more sustainable solutions will be worth it.
The ninth, which of the following characteristics about big data analytics is not true? The second thing is “Big data is accurate.” While it is true that the volume of data that drives any analytics solution can increase as time goes by and therefore the potential accuracy of any solution can also increase, this is not always the case. Today, thanks largely to advances in technology, there is usually some sort of artificial intelligence that drives the solution even in the event that you do not have the human intervention necessary to get things done. Therefore, the potential accuracy of any solution that uses big data is typically greater than what you would obtain without the help of artificial intelligence.
The eleventh, which of the following characteristics about big data analytics is not true? “Big data analytics is scary.” While it is certainly true that most people do not enjoy the prospect of having their information mined and stored in huge databases, this need not stop individuals from doing exactly that. In fact, it is through the use of big data analytics solutions that today’s organizations are able to build up massive sets of information about everything from customer demographics to financials that they need in order to do their business properly and at a high level of efficiency.