Glossary of terms
Big Data is the approach and method of processing large amounts of structured and unstructured data. Throughout history, people have generated huge amounts of information. This includes data about our phone calls, movements, supermarket purchases, doctor visits, search queries, social media behavior (likes, shares, reposts), and so on.
Analyzing all this data, one can get a lot of useful information about the behavior of each person. Data analytics works as follows: a person provides the computer with certain input data, but the result of this algorithm is not determined by the person. A person chooses the way machine learning will be performed, but the machine learns on its own and analyzes the data set on its own to come up with certain results.
One of the most obvious features of Big Data is a large amount of data that is constantly growing. This refers to the terabytes, petabytes, exabytes, and even zettabytes of information that are generated daily by various sources, including the Internet, social media, sensors, mobile devices, etc.
Big Data includes different types of data: structured, semi-structured, and unstructured. It can be numbers, text, images, audio and video files, geolocation data, etc. Processing such a wide variety of data requires special methods and tools.
The speed at which data is collected, processed and analyzed also plays an important role in Big Data. High rates of data processing allow companies to respond to changes in real-time and make appropriate decisions faster.
An important characteristic of Big Data is data reliability, which reflects the accuracy, consistency, and relevance of information. Incorrect, inconsistent, or outdated information can lead to erroneous conclusions and strategic decisions.
The ultimate goal of big data analysis is to identify valuable information that can help companies optimize their processes, provide competitive advantages, and accelerate innovation. The value of Big Data lies in the ability to identify connections, trends, and patterns that were previously hidden or invisible.
Big Data technologies can be useful in solving the following tasks:
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