Let us begin by defining the term- Data. If you do a quick Google search then you will find that “Data” is defined as ‘the quantities, characters, or symbols on which operations are performed by a computer, which may be stored and transmitted in the form of electrical signals and recorded on magnetic, optical, or mechanical recording media’.
In simple words, we can say that all the facts and figures which can be stored in digital format can be termed as data. All the text, numbers, images, audios, videos stored in our phones and computers are some examples of data. They are all digitally stored and comprise of zeros and ones. Please remember that data is a plural term, the singular term for data is .datum’.
The concept of Big Data is nothing complex; as the name suggests, “Big Data” refers to copious amounts of data which are too large to be processed and analyzed by traditional tools. Since the amount of Big Data increases exponentially- more than 500 terabytes of data are uploaded to Facebook’s database alone, in a single day- it represents a real problem in terms of analysis. Now you may be thinking that if this big data is so problematic then why is everyone so obsessed about it? Well, the answer lies in the benefits it provides. Here are some real-world examples of the ways in which Big Data is used.- Netflix collects user behavior data from its more than 100 million customers.
This data helps Netflix in understanding what every individual customer wants to see. Based on the analysis it recommends movies and TV shows which the viewer will love to watch. As a result, the customer is happy because he is getting what he likes without even searching for it, and Netflix is happy because it has delighted its customers which will result in higher customer retention. Credit card companies collect and store the real-time data of when and where the credit cards are being swiped.
This data helps them in thwarting fraud detection. Suppose a credit card is used at location A for the first time. Then after 2 hours the same card is being used at location B which is 5000 kilometers away from location A. Now it is practically impossible for a person to travel 5000 kilometers Within two hours, and hence it becomes clear that someone is trying to fool the system. These were just the two example, big data has hundreds of different applications in hundreds of different fields. Be it banking, communication, healthcare, media, advertising, manufacturing, transportation, retail, Big data can be used everywhere and this is why more and more businesses are trying to harness its power.
Classification is essential for the study of any subject. So Big Data is widely classified into three main types, which are- Structured, Unstructured and Semi-Structured Data Structured data Structured Data is used to refer to the data which is already stored in databases, in an ordered manner. It accounts for about 20% of the total existing data and is used the most in programming and Computer-related activities. There are two sources of structured data- machines and humans. All the data received from sensors, weblogs, and financial systems are classified under machine-generated data.
These include medical devices, GPS data, data of usage statistics captured by servers and applications and the huge amount of data that usually move through trading platforms, to name a few. Human-generated structured data mainly includes all the data that humans input into computers, such as names and other personal details. When a person clicks a link on the internet or even makes a move in a game, data is created- this can be used by companies to figure out their customer behavior and make the appropriate business decisions and modifications.
Unstructured data While structured data resides in the traditional row-column databases, unstructured data is the opposite- they have no clear format in storage. The rest of the data created, about 80% of the total account for unstructured big data. Most of the data a person encounters belong to this category- and until recently, there was not much to do to it except storing it or analyzing it manually. Unstructured data is also classified based on its source, machine-generated or human-generated. Machine-generated data accounts for all the satellite images, the scientific data from various experiments and radar data captured by various facets of technology.
Human-generated unstructured data is found in abundance across the internet since it includes social media data, mobile data, and website content. This means that the pictures we upload to Facebook or Instagram handle, the videos we Watch on YouTube and even the text messages we send, it all contributes to the gigantic heap that is unstructured data. Semi-structured data. The line between unstructured data and semi-structured data has always been unclear since most of the semi-structured data appear to be unstructured at a glance. I
nformation that is not in the traditional database format as structured data, but contains some organizational properties which make it easier to process, are included in semi-structured data. For example, NoSQL documents are considered to be semi-structured, since they contain keywords that can be used to process the document easily.
Big Data analysis has been found to have definite business value, as its analysis and processing can help a company achieve cost reductions and dramatic growth. So it is imperative that you do not wait too long to exploit the potential of this excellent business opportunity. This was all about Big data and the types of Big Data.