What is Big Data: Definition, Characteristics, and Benefits

what is big data definition characteristics and benefits.

Lately the term 'Big Data' has become the center of attention, but not many people know what Big Data is. In the age of the internet, companies, and organizations all over the world have been collecting so much data. IBM states that businesses worldwide generate nearly 2.5 trillion bytes of data every day! Nearly 90% of global data has been produced in the last 2 years alone.

Forbes also reports that every minute, users watch 4.15 million YouTube videos, send 456,000 tweets on Twitter, post 46,740 photos on Instagram and there are 510,000 comments posted and 293,000 status updates on Facebook! Just imagine the huge amount of data generated by activities. like that. This constant creation of data using social media, business applications, telecommunications, and various other domains is leading to the formation of Big Data and it is impacting all of our lives.

What is Big Data?

Big Data is a high-volume, high-speed and diverse information asset that demands innovative, cost-effective forms of information processing for enhanced insight and decision making. Big Data refers to complex and large data sets that must be processed and analyzed to reveal valuable information that can benefit businesses and organizations. This data set is so large that ordinary data processing software cannot manage it.

History of Big Data

Although the concept of big data itself is relatively new, the history of big data begins in the 1960s and 70s when the world of data was just getting started with the first data centers and the development of relational databases. Around 2005, people began to realize how much data users generate through Facebook, YouTube, and other online services. Hadoop (an open-source framework created specifically for storing and analyzing big data sets) was developed in the same year. NoSQL also started to gain popularity during this time.

The development of open-source frameworks, such as Hadoop (and more recently, Spark) is critical to the growth of big data because they make big data easier to work with and cheaper to store. In the years since the volume of big data has skyrocketed. Users still generate huge amounts of data, but it's not just humans doing it.

With the advent of the Internet of Things (IoT), more objects and devices are connected to the internet, collecting data on customer usage patterns and product performance. The advent of machine learning is still generating more data. While big data has come a long way, its usefulness is just beginning. Cloud computing has expanded the possibilities of big data even further. The cloud offers truly elastic scalability, where developers can easily spin up ad hoc clusters to test subsets of data.

Big Data Characteristics

1) Variation

Big Data model refers to structured, unstructured, and semi-structured data collected from various sources. While in the past, data could only be collected from spreadsheets and databases, today data comes in many forms such as emails, PDFs, photos, videos, audios, audios, SM posts, and many others.

2) Speed

Velocity basically refers to the speed at which data is being generated in real-time. In a broader outlook, it consists of the rate of change, correlating incoming data sets at varying rates, and bursting activity.

3) Volume

We already know that Big Data represents a huge 'volume' of data that is generated daily from various sources such as social media platforms, business processes, machines, networks, human interactions, etc. A large amount of data is stored in the data warehouse.

What is Big Data Technology?

Suppose our PC can only manage a small amount of data. Just imagine all the possible information to be entered into a single spreadsheet. Database software is capable of handling higher volumes of information. These tools can feed that information onto a single hard drive data which would otherwise require a shelf filled with boxes full of notebooks and folders. But these tools are not enough to handle all the volumes of information we call big data.

Examples of Big Data Usage

Internet of Things

The internet that we know today is the internet of people. This is where people interact with each other, with machines that facilitate that communication. We look at sites that people design. We read the words that people type.

The Internet of Things is a device that communicates directly with each other without human involvement. An example is a device that monitors the weather. Smart thermostats access that information and make adjustments to the temperature in our homes. Big data and the Internet of Things are interdependent. These devices can take action on their own thanks to all the data available to them. The more devices that function this way, the more data it generates.

Machine Learning

Machine Learning refers to the ability of computers to learn from data. Machine Learning is also behind content recommendations on YouTube. This prediction is caused by an algorithm. Google search algorithm? The algorithm that determines what we see on Facebook's news feed? It's all machine learning at work.

Artificial Intelligence

Artificial Intelligence is the next step after machine learning. Here, not only does the computer learn from the data, but uses that information to make its own decisions and shape its own behavior. Microsoft and Google have both demonstrated efforts to create humanoid robots. Facebook uses artificial intelligence to help prevent suicide. The technology is evolving at a rate where there are few instances where computer thinking has outperformed humans.

What is Big Data Analytics?

Big data sources don't tell us anything about them themselves. One has to understand all that information. This is what big data analytics is all about: looking at the enormous volume of information and seeing what we can learn. Today, more and more organizations are embarking on new big data projects, and companies are racing to offer their specialized forms of big data analytics in various fields. Through these actions, big data has an effect on our lives.

Big Data Benefits

Big Data in Healthcare

The healthcare industry is not the fastest in adopting new technologies. Some providers are still migrating from paper to digital storage tools. Nonetheless, there are areas where big data makes a difference. One of them is the integration area. Insurers and providers work to combine data from multiple sources, such as claims, X-rays, doctor's notes, and prescriptions.

Many believe that if healthcare data were more integrated, it could provide better care at lower costs. When Amazon, Berkshire Hathaway and JP Morgan announced earlier this year that they were working together on healthcare, they cited technology as their area of ​​focus, as covered by The Guardian.

Big Data in Finance

The financial industry understands the idea of ​​making decisions based on computer analysis. Such as Automated trading systems that use machines to sell stocks without human intervention, based on what is happening in the market. This is called high frequency trading. Now, scientists are using big data to predict which stocks will succeed and when future falls are likely. Banks also see big data as a way to increase their revenue.

Big Data In Ecommerce And Marketing

We certainly produce a lot of information when shopping. Online, we have to create an account before we shop, allowing sites not only to track what we buy but every item we see. Stores base their layout around consumer interests and behavior. Online sellers decide what to see based on demographic information and other metrics.

There is a great demand for the kind of insight that comes from monitoring interests and behavior online. Facebook and Google are tech giants that are profitable because of their ability to sell ads that are better able to target specific consumer groups than other advertising methods and platforms. They can do this thanks to all the information we provide when we use their services.

Is Big Data Dangerous?

Big data comes with a promise, but it also comes with risks. First is the erosion of privacy. More people know more about each of us than at any point in human history. Not only is it easy to find where we live, but where we go, who we love, how we live, and what we think.

This makes individuals and society more open to manipulation. We can be tricked into giving up our passwords or credit card numbers. More data offers more ways for advertisers and media companies to shape our desires and values. There is more data about us than ever before, and that data is stored in many different places. It creates more attack targets. It's not enough to get there, to protect our own machines. Data breaches are now a common occurrence, with what happens to our data beyond our control.

Even companies that might do a decent job of protecting our data from outside attacks often do dubious things with the data themselves. Finding ways to keep our data secure, our privacy respected, and our values ​​maintained will be an ongoing challenge as the trend towards big data continues. Yet no matter how we feel about it, for better or for worse, we all live in the world of big data.


So What Is Big Data? Big Data refers to a large amount of data that flows from various data sources and has different formats. Even before that, there was big data stored in the database, but due to the varied nature of this Data, traditional relational database systems were not able to handle this Data. Big Data is more than just a collection of datasets with different formats, it is an important asset that can be used to derive quantifiable benefits.

Hopefully, this article about What is Big Data: Definition, Characteristics, and Benefits, gives you a little insight. Also, read an article about What is BIOS and how does it work that you may need to know. Thank you.

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