Computers use various quantities, symbols, or characters to perform several operations. Now, all of these are stored, as well as transmitted through electric signals, and are recorded in a suitable media. These transmissions and also the recordings are called data. A brief understanding of the very basic idea of data was required to finally arrive at what is called, big data – our epicenter of discussion today.
What is Big Data?
We now know what data is. However, a humongous version of it, with lots of complexities, so much so that it becomes difficult to process everything refers to something that is called Big Data. It is nothing but a huge volume of data that gets generated in a business daily. Both structured and unstructured data flood businesses and people seldom know what to do with it. But what matters is which organization is using it efficiently for its betterment in terms of improving its strategic moves. It is not the quantity of data that is important, but rather what one is doing with all that data, is something that should be noted.
The overall collection of big data is unimaginable in volume but it is a fact that it is essentially ever-growing in nature. It deals with such large sizes of data and so many complexities that it is not compatible with the older and traditional version of data management tools, which also cannot store or process data with huge size.
Nonetheless, the entire process of computers dealing with big data for analytics has been there for quite some time now, but it was majorly during the early 2000s when big data was coined its mainstream definition.
The Three Vs
The phrase Big Data refers to three Vs:
- Volume – The size of data plays an important role in considering a particular data as big data. Also, volume is important to determine the value of that data. Big data is all about the collection of enormous sizes of data by organizations from various sources. When we talk about the characteristics of big data, volume is of prime importance.
- Variety – The variety of data being generated every day has been through a significant change. When computing was still not so widespread, databases and spreadsheets were used by most applications, which were considered to be the only good source of data But nowadays, data taking the form of photos, emails, videos, audios, or even PDFs is nothing new. Referred to as variety in big data, analysis applications are talking about these forms of data, rich in heterogeneous sources.
- Velocity – Imagine the probable amount of data generated in a single day. Velocity in big data talks about the speed of generation of data. Careful handling of this data at the right intervals of time is important. Big data is dealt with or is taken care of by sensors, smart meters, or RFID tags.
After coming across the three main characteristics of big data, now is the time to site examples of big data that we see around us on a day-to-day basis.
Big Data Examples That’s Not Very New:
NYSE or the New York Stock Exchange roughly generates around one terabyte of new data concerning trading, every day. This is hence, one of the most famous examples of big data that exists before us.
Facebook, every day. The data generated by Facebook is indeed big data and variety is another trait when it comes to this particular example. This is because the generation of most of the data in social networking sites is in the form of exchanges of messages, video and photograph uploads, etc.
Flying an airplane requires a lot of exchanges of big data. The communication in the form of radio signals gives rise to more than 10 terabytes of flying data in just 30 minutes of flying time. Now if we think about the bigger picture. Thousands of flights to and fro throughout the world on a single day. Generation of data, thus, reaches up to many petabytes.
An increasing number of people are resorting to crypto-trade when it comes to trading shares in the new world. Cryptocurrencies are running on or are based on a chain of pockets of digital memories called a blockchain. Now, the blockchain acts as a ledger to crypto transactions. Therefore, there is the generation of a huge amount of big data each day by crypto-trade. Its halt would rise to the collapse of the entire chain.
How Is Big Data Advantageous?
Indeed, big data always refers to a huge size of data that needs catering. Hence, an efficient dealing and proper analysis will enable several positive outcomes. Some of them are as follows:
- Savings – some big data tools offer a lot of savings if a particular company has to save or store big data in its system. Some of these tools also identify efficient ways of doing business which will, in turn, benefit the company at large.
- Fast action, reduced time – The tools often offer high speeds to sort out big data and take respective actions immediately helping in quick analysis and decision making based on previous learnings.
- A better understanding of the market condition – big data analysis gives you a better understanding of market conditions. For an instance, by understanding customers’ preferences, you can figure out what product is in demand and accordingly come up with better business offers and plans.
- Online reputation – sentiments of human beings can also be judged with the help of big data tools. You can get something of feedback by understanding the reputation of your company and can also plan to improve the presence of your business accordingly.
Now, big data companies make use of these advantages and create their databases, which we might say helps us in making a better sense of the world. Three of the big data companies that will surely attract your attention are as follows:
CLOUDERA
The company is a cloud platform, built by people from organizations like Google, Yahoo, Facebook, etc., and is a leading name in big data analysis. It provides a technology that helps to sort out big data, keeping everything in one place. Thus, making way for clearer insights.
Google is one of the most successful big data companies that existed. Starting from the search engine to its other products and services, Google has effectively used big data and brought in innovation.
IBM
Solutions regarding big data analysis are supplied by IBM. This helps companies wrangle up data quite effectively. It makes sure that a company can refer to its stored data simply and make everything accessible with better insights. IBM is presently one of the largest tech companies that are dealing with big data effectively.
Starting from the very nascent stage of computers to where we stand today. We have come past a lot of innovations. Dealing with big data is surely one of them. It can be structured, unstructured, or semi-structured. Still, a lot of companies and organizations are trying to channelize these packets of data. They want to create something useful, operational, and efficient. Though big data often comes to use by big companies, it is a fact that we hold the power to alter statistics in terms of how all these data are being generated as well as consumed.
