What is Big Data, and what does it do?
The term “Big Data” refers to a large volume of data, whether structured or unstructured, which is stored, processed, studied, and analyzed to then be transformed into strategic actions from a business perspective.
Given its complexity, variability, and speed of growth, data storage, and processing are done thanks to technologies and software applications capable of executing these at high speeds. It would be impossible to do so using conventional tools like databases or statistics.
The volumes of data are generated from different sources of modern technology, ranging from writing a comment on social media to clicking on a web link or filling in a registration form, or from tuning in to a radio frequency to turning on GPS in vehicles and on phones. Access to all this data generated is valuable information for companies to identify patterns and thus develop proposals, products, and solutions based on them.
What are the main characteristics of Big Data?
To better understand the term, an analysis of the “5 Vs of Big Data” is usually carried out:
- Speed: refers to the rate at which data is generated, as well as how quickly it is stored and processed, which happens in almost real-time.
- Volume: this entails tens of terabytes or even petabytes of data generated and stored every second, and which must be processed in large quantities.
- Type: indicates the different types, forms, and sources of data that exist, whether structured — which may be organized through a relational database — or unstructured and semi-structured — which require additional processing with qualified tools to understand its meaning.
- Veracity: refers to how reliable the data and information collected are to determine their quality. Big Data must focus on obtaining accurate data to implement actions and solutions that reduce the margin of unpredictability.
- Value: in such a vast universe of information that must be processed, it’s necessary to discover value and pay special attention to the data that’s really important for decision-making and future strategic actions.
How does Big Data work?
The process of obtaining, analyzing, and understanding data responds to an automated process through analytical and artificial intelligence tools that record, process, and store all the information generated in real-time.
This management requires a stable, secure infrastructure that supports large volumes of data quickly and efficiently. This requires using thousands of servers and is based on three main steps:
- Integrating strategies and technologies in an efficient system to receive, process, and format data for subsequent management.
- Managing data storage, either in the cloud or in a company’s IT infrastructure, and preferably in real-time to have access to it at any time.
- Analyzing it after receiving and storing the data and making decisions based on that analysis to obtain a competitive advantage.
What does Big Data have to do with sustainability?
Data tracking and processing also plays a key role in sustainability issues. Through partnerships between public and private companies, so-called sustainable data gathers, compares, and draws relationships between information from physical events – such as fires, rain, or earthquakes – and data from social components – such as home light intensity, phone calls, actions on social media, etc.
Extracting the data takes place through satellite photos and public databases. These aim to understand human behavior in natural and humanitarian situations in order to implement political improvements in cities.
Examples of Big Data
Big Data’s impact has enabled its implementation in different fields and for multiple types of businesses and companies: marketing and sales, health, sports, politics, telecommunications, and more, all with the aim of developing actions based on analyzing that information. A few examples:
- India Night Lights: data collection to identify energy consumption in India and then measure the evolution of access to electricity in rural areas of the country.
- Slam Tracker: this predictive analysis tool makes it possible to get information from the data generated by sensors in athletes’ sports equipment in order to identify patterns and improve their performance by monitoring physical preparation, nutrition, and sleep.
- Life Under Your Feet: a study of climate change based on a tool that collects data from satellites on the variations in humidity and temperature worldwide. This project aims to improve decision-making regarding the construction of infrastructure for agricultural systems.