What is Big Data in simple words
Posted: Wed Jan 22, 2025 6:34 am
Big Data is a huge array of diverse information, as well as a set of methods and tools for their processing and analysis. Big data includes both ordered information and information that does not have a specific structure, unsystematic.
The size of "big data" is so large that neither a person nor a regular computer can process it. This process requires enormous computing power and special software that are only available in data centers. Based on the analysis of big data, forecasts are made, processes are optimized, and models are built.
Principles of Big Data
This technology is used to analyze all factors and make the right decision. In general, big data works like this: organizations generate disparate information and pass it through an algorithm that structures it and turns it into a form understandable to humans. Then the obtained data is analyzed. With the help of artificial intelligence, they look for relationships and patterns in them that can predict the future, and already based on this, specialists think through strategies, find solutions to the problem and ways to bahamas whatsapp number database improve certain processes.
Let's look at each stage in a little more detail.
What is Big Data.
Collection sources
There are a great many places where big data comes from, but they can all be divided into three groups:
Social. This includes all information generated by users on the Internet (photos, texts, videos, messages, reviews, ratings, clicks on links), as well as statistical data of states and cities, birth and death rates, medical records and information about people's movements.
Machine. This is mainly the Internet of Things and the physical devices connected to it: smartphones, wearable gadgets, smart home appliances, industrial equipment, weather satellites, etc.
Transactional. Data that arises from purchases, money transfers, ATM transactions, product deliveries, etc.
Storage
As we have already said, "big data" is too voluminous to fit on a simple computer. We are talking about millions of gigabytes (petabytes) of information. They are stored in special data centers with the most powerful servers. In addition to physical ones, cloud storage is also used. Often, data from one source is "merged" into a "data lake", from where neural networks then extract the necessary information.
Processing
Working with big data is based on three principles: horizontal scalability, fault tolerance, and data locality. This means that the system that will process the information must be easily expandable, contain many machines, and continue to work even if some of them fail. The third principle is that the data, if possible, should be processed on the same devices on which it is stored. Otherwise, the costs of transmitting information may exceed the costs of processing it.
Software for performing such a complex task is developed based on various methods. A classic example is MapReduce, a parallel computing model that involves distributing the processing process between machines participating in a computer cluster. Two of the most popular tools for working with Big Data are developed based on this algorithm: the Hadoop and Apache Spark frameworks.
The size of "big data" is so large that neither a person nor a regular computer can process it. This process requires enormous computing power and special software that are only available in data centers. Based on the analysis of big data, forecasts are made, processes are optimized, and models are built.
Principles of Big Data
This technology is used to analyze all factors and make the right decision. In general, big data works like this: organizations generate disparate information and pass it through an algorithm that structures it and turns it into a form understandable to humans. Then the obtained data is analyzed. With the help of artificial intelligence, they look for relationships and patterns in them that can predict the future, and already based on this, specialists think through strategies, find solutions to the problem and ways to bahamas whatsapp number database improve certain processes.
Let's look at each stage in a little more detail.
What is Big Data.
Collection sources
There are a great many places where big data comes from, but they can all be divided into three groups:
Social. This includes all information generated by users on the Internet (photos, texts, videos, messages, reviews, ratings, clicks on links), as well as statistical data of states and cities, birth and death rates, medical records and information about people's movements.
Machine. This is mainly the Internet of Things and the physical devices connected to it: smartphones, wearable gadgets, smart home appliances, industrial equipment, weather satellites, etc.
Transactional. Data that arises from purchases, money transfers, ATM transactions, product deliveries, etc.
Storage
As we have already said, "big data" is too voluminous to fit on a simple computer. We are talking about millions of gigabytes (petabytes) of information. They are stored in special data centers with the most powerful servers. In addition to physical ones, cloud storage is also used. Often, data from one source is "merged" into a "data lake", from where neural networks then extract the necessary information.
Processing
Working with big data is based on three principles: horizontal scalability, fault tolerance, and data locality. This means that the system that will process the information must be easily expandable, contain many machines, and continue to work even if some of them fail. The third principle is that the data, if possible, should be processed on the same devices on which it is stored. Otherwise, the costs of transmitting information may exceed the costs of processing it.
Software for performing such a complex task is developed based on various methods. A classic example is MapReduce, a parallel computing model that involves distributing the processing process between machines participating in a computer cluster. Two of the most popular tools for working with Big Data are developed based on this algorithm: the Hadoop and Apache Spark frameworks.