What is Big Data? we explain what the term Big Data means, how it works, and how the Internet of Things (IoT) is transforming it.
Search engine and social media companies such as Google, Facebook, YouTube, and similar companies shape social and technological trends. These companies are data-driven, use large data sets and Big Data, and perform advanced analytics to drive their business. So our question is, how is the Internet of Things transforming Big Data? What role does the IoT have in Big Data?
What is Big Data?
Have you ever wondered how much data we generate from our daily use of smartphones in texts, emails, videos, phone calls, photos, searches, and music? Approximately 40 exabytes of data gets generated by a single smartphone user every month. Imagine this multiplied by 5 billion smartphone users globally. That is a BIG amount of data and too much for traditional computer systems to handle.
This massive amount of data is what we call Big Data. Big Data means a large, fast, and complex set of data. Such a data set is challenging to process using traditional methods. This data can amount to petabytes of unstructured and structured data generated from Social platforms and IoT Devices.
How does Big Data work?
The concept of classifying Big Data is possible with the five V's. Volume, Velocity, Variety, Veracity, and Value.
Volume refers to the amount of data collected from sources by organizations in various forms, such as videos, images, and audio. Today, data management has improved, and storing all this data has become much cheaper than in the past using data lakes and the cloud.
Velocity refers to the speed at which data streams into businesses. RFID tags, sensors, and intelligent meters mean processing of these large amounts of data has to be done in near real time.
Variety means data comes in all forms, from structured, numeric databases to unstructured data in the form of documents and media. These amounts of data are subject to management to enable proper research data analysis later.
Veracity refers to the accuracy and trustworthiness of data collected. You want data consistently analyzed for accuracy, without any bias as much as possible. The veracity of data also refers to incomplete data or the presence of errors, outliers, and missing values.
Value is what we get back from all the processes related to Big Data. By itself and regardless of its volume, data usually isn't beneficial. For data to be valuable, it needs to be converted into insights that are helpful to people and sectors in society, such as health care.
Big Data storage and processing.
How is Big Data stored and processed? Systems such as Cassandra, Hadoop, and Spark are open-source frameworks used to efficiently store and process large datasets ranging from gigabytes to petabytes of data. Let's take Hadoop, for example. Huge files distributed into a file system are broken down into smaller chunks and stored in various machines. When broken, copies are created and then stored in different nodes. This way, Big Data is stored in a distributed manner, so even if one machine fails, the data is stored in another.
Big Data is processed using the MapReduce technique. Tasks broken into small tasks end within various machines that take up each task to process and deliver fast results. This system is known as parallel processing. Now that data has been stored and processed, analysis is next for numerous applications. Game developers, for example, can analyze user data to see at which points gamers pause, restart or quit a game. This insight can help them re-work the game's storyline and improve the user experience, reducing the customer churn rate. Using this method for other areas such as business intelligence and science is also practice.
The Relation between Big Data & IoT
Estimates suggest that by 2025, there will be 175 zettabytes of data in the global datasphere. This number will only get more extensive as the number of connected devices increases every year. New technologies are allowing more devices to send data over the internet.
The Role of Big Data in IoT is the ability to process large amounts of data on a real-time basis. This valuable data is then structured and stored using multiple storage technologies. Businesses then use this information to offer a better service, a new service, or higher customer satisfaction.
The simplest way Big Data is processed is by splitting it into different categories depending on their relations. This data is then stored in databases and utilized intelligently by businesses.
Benefits of IoT & Big Data for Companies in Different Sectors
Helps to increase the Return On Investment for the Business
IoT and Big Data analytics transform how businesses add value by extracting the maximum information from devices and products to get better business insights from data processing. For example, this could be fault reporting, enabling the business to target product issues earlier.
Advantages in Manufacturing Companies
Manufacturing companies install IoT sensors to collect critical operational data from their machines, helping their business to get an in-depth performance report. Data collected helps to prevent machines from having downtime. This information helps the company make processes more efficient. For example, a company knows that equipment requires servicing due to increased vibrations reported by IoT Sensors before the machine would have irreparable damage.
Data Collection Businesses
Companies rely on data collected from the real world to transfer each individual's right content and adverts. Big Data collected from personal physical devices is the key to understanding each person's interests and what content to display. For example, an individual searching for marine products from his mobile phone will receive content and adverts related to marine systems or products.