The discussion about what are the three distinct characteristics that distinguish big data from traditional data has been going on for quite some time now. While some people believe that it is inevitable that big data will displace traditional data, there is actually a possibility that the two can coexist. In fact, big data has already proven to be beneficial to businesses in many ways. However, if one only thinks about the impact that big data can have on business operations, one might not necessarily associate it with traditional data sets.
Most analysts and business experts agree that one of the three distinct characteristics that distinguish big data from traditional data is the massive amount of information that can be assimilated and used. Traditional data sets typically comprise just text and are limited to how much it could be stored. Big data, on the other hand, encompasses a vast amount of data that is processed and analyzed in order to yield useful insights. In other words, big data may provide answers that traditional data sets cannot.
In addition, traditional data sets only have a singular form. It is difficult to extract relevant information from large sets of data without making any changes. With big data, however, this problem is almost eliminated. Since the volume of data is huge, it becomes possible to apply advanced algorithms and software to extract relevant information from huge amounts of data. This makes traditional data sets vulnerable to artificial intelligence. Artificial intelligence basically refers to the ability for an entity to process data and predict future data sets based on certain criteria.
Moreover, big data can provide immediate feedback as well as deeper and more in-depth analytics. Traditional data sets usually require a long period of analysis and tracking in order to determine what has actually been happening. However, with big data, the same information can be identified and analyzed within a few minutes.
On the other hand, traditional data sets usually require long hours of processing. Big data does not have this problem. Once data is collected, analysts and designers can immediately use mathematical algorithms in order to detect patterns and relationships. In many cases, developers and designers can determine what is important and what is worth investing in very quickly. The problem with traditional data sets is that sometimes a significant amount of time must be spent in processing the data and analyzing it.
What are the three distinct characteristics that distinguish big data from traditional data sets? First, big data tends to be more expansive. When you compare the storage space of traditional data sets to those of big data, you will see how much more information is stored and can be processed. However, traditional data sets can be difficult to access and analyze because of the enormous amount of information they contain. Furthermore, traditional data sets are not well-suited for streaming data, which allows users to access and process information in real time.
Second, what are the three distinct characteristics that distinguish big data from traditional data sets? Big data’s biggest advantage over traditional data sets is the speed at which the information can be processed. Traditional data sets may take days or even weeks to process data and then provide visual information. With big data, the same information can be visualized and presented within seconds. Lastly, traditional data sets cannot accommodate the massive amounts of data collected by big data technologies.
These three distinctive characteristics reflect the differences between big data and traditional data sets. The use of streaming technologies in computing has made big data sets the modern trend. Streaming provides users instant access to large amounts of data. Additionally, the ability to process this data in real time provides users a new perspective on how business can be conducted.