Big Data is huge amounts of data that come from various sources, such as social networks, websites, and mobile applications. “Big” refers to any unstructured data that is generated daily in the amount of 150 gigabytes. How much is that? A file with the full text of the novel “War and Peace” weighs about 6 megabytes. 150 gigabytes is “War and Peace”, which has been reprinted 25,000 times. It is impossible to process this much data manually.
Therefore, tools and technologies have emerged that have expanded the capabilities of Big Data processing and analysis. For example, Apache Spark and NoSQL databases, streaming data processing systems. Big Data is widely used in various industries: finance, healthcare, retail, telecommunications. Companies use big data to make more informed decisions, optimize processes and create new products and services.
According to a study by VK Cloud and Arenadata conducted among Russian companies, 62% of respondents implemented big data solutions in 2022.
For comparison, in 2015, only every tenth Russian student data company worked with Big Data .
Machine learning comes to the rescue in processing large amounts of data – a technology that allows algorithms to improve based on their experience, make predictions and “make decisions”.
The field that combines statistics, data analysis, machine learning and other methods of working with big data is called Data Science. This is one of the most promising areas in IT.
Signs of Big Data
How do we know that we have big data and not regular data? By the presence of three signs:
volume - it can be hundreds of gigabytes per day.
speed - the amount of data increases exponentially.
diversity - data is unstructured and comes in different formats: text, images, audio or numbers.
Flocktory_How to Use Big Data and Machine Learning to Increase Profits
Sometimes other characteristics of big data are also identified:
variability - the flow of information can be non-uniform, with dips and bursts of activity.
value - the information to be processed may be difficult to analyze, but important to achieving business goals.
visualization - the analyzed data can be presented visually.
reliability - the data is accurate and the method used to obtain it is correct.