What is Big Data: Definition, Characteristics and Benefits

The term “big data” has recently come into the spotlight, 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 a lot of data. IBM It states that companies around the world generate approximately 2.5 trillion bytes of data every day! Nearly 90% of global data was generated in two years just past.

Forbes also reported that users watch every minute 4.15 million YouTube videos send 456000 tweets On Twitter, posting 46,740 photos on Instagram and there 510,000 comments publish and 293,000 cases Updated on Facebook! Just imagine the huge amount of data generated by such an activity. This continuous creation of data using social media, business applications, telecommunications, and various other areas is creating Big Data and affecting our entire lives.

What is big data?

Big data is a large-volume, high-speed, diversified information asset that requires innovative and cost-effective forms of information processing to improve visibility 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 normal data processing programs cannot manage it.

History of big data

Although the concept of big data itself is relatively new, the history of big data began in the 1960s and 1970s when the data scientist was just getting started with the first data centers and the development of relational databases. Around 2005, people began to realize the amount of data that users generate through Facebook, YouTube, and other online services. Hadoop (an open source framework created specifically for storing and analyzing huge 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 dealing with big data easier and cheaper to store. In the years since, the amount of big data has skyrocketed. Users are still generating massive amounts of data, but it’s not just about humans.

With the advent of the Internet of Things (IoT), more objects and devices are connected to the Internet, collecting data about customer usage patterns and product performance. The advent of machine learning is still generating more data. Although big data has come a long way, its usefulness is only just getting started. Cloud computing has expanded the possibilities of big data even further. The cloud offers truly flexible scalability, where developers can easily create custom batches to test subsets of data.

Big data features

1) difference

The 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 the data comes in various forms like emails, PDFs, images, videos, audios, audios, SM posts and many more.

2) speed

Speed ​​basically refers to the speed at which data is generated in real time. From a broader perspective, it consists of rate of change, association of incoming data sets with varying rates, and explosive activity.

3) Size

We already know that Big Data refers to 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?

Let’s say our computer can only manage a little bit of data. Just imagine all the possible information to be entered into one spreadsheet. Database software is capable of handling larger amounts of information. These tools can feed this information onto a single hard drive that would otherwise require a shelf full of boxes full of notebooks and folders. But these tools are not enough to handle all the volumes of information we call big data.

Example Use of big data

The Internet of things

The Internet 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 websites that people design. We read the words people write.

The Internet of Things is devices that communicate directly with each other without human intervention. 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 interconnected. These devices can take action on their own thanks to all the data available to them. The more devices that operate in this way, the more data they generate.

Read also: Learn what is Internet of Things (IoT) technology

machine learning

Machine learning refers to the ability of computers to learn from data. Machine learning is also behind YouTube’s content recommendations. This prediction is caused by an algorithm. Google search algorithm? The algorithm that determines what we see in the Facebook news feed? All of this is machine learning in action.

Artificial intelligence

Artificial intelligence is the next step after machine learning. Here, the computer not only learns from the data but uses that information to make its own decisions and shape its behaviour. Both Microsoft and Google have demonstrated efforts to create humanoid robots. Facebook uses artificial intelligence to help prevent suicide. Technology is developing at a rate where there are only a few instances where computer thinking has outdone humans.

What is Big Data Analytics?

Big data sources don’t tell us anything about it. One has to understand all that information. That’s what big data analytics is all about: looking at massive amounts 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 affects our lives.

The benefits of big data

Big data in healthcare

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

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

Big data in finance

The financial industry understands the idea of ​​making decisions based on computer analysis. Like automated trading systems that use machines to sell stocks without human intervention, based on what’s 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 dips are likely. Banks also see big data as a way to increase their revenue.

Big data in e-commerce and marketing

We certainly produce a lot of information when shopping. Online, we have to create an account before shopping, which allows sites to not only keep track of what we buy, but every item we see. Stores in their design are based on consumer interests and behavior. Online sellers decide what to see based on demographic information and other metrics.

There is a huge demand for the kind of insight that comes from monitoring interest and behavior online. Both Facebook and Google are profitable tech giants due to their ability to sell ads that are better able to target specific groups of consumers 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 promises, but it also comes with risks. The first is the erosion of privacy. More people know about each of us than ever before in human history. Not only is it easy to find where we live, but where we are going, 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 provides more ways for advertisers and media companies to shape our desires and values. There is more data about us than ever before, and this data is stored in many different places. Creates more attack targets. There is absolutely no way to protect our devices. 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 questionable things with the data itself. Finding ways to keep our data secure, respect our privacy, and uphold our values ​​will be an ongoing challenge as the trend toward big data continues. However, no matter how we feel about it, through thick and thin, we all live in a world of big data.

conclusion

So what is big data? Big data refers to a large amount of data that flows from different data sources and has different formats. Even before there was big data stored in databases, but due to the diverse nature of this data, traditional relational database systems were unable to handle this data. Big data is more than just a collection of data sets of different formats, it is an important asset that can be used to derive quantifiable benefits.


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