Understanding what is Big Data with examples

Big Data has gained popularity in recent times. It is referred to a sizeable volume of data that cannot be stored or handled using normal data storage or processing tools. Due to the enormous volume of data generated by both human and machine activity, the data are so complicated and vast that neither people nor a relational database can analyze them. However, when properly analyzed using contemporary analytical tools, these vast amounts of data offer firms significant insights that aid them in improving their operations by taking wise decisions.

It’s in the name: Big Data

This particular write-up helps you understand what big data with examples from various fields is. It is impossible to analyze all the generated data using identical tools for each type. Once the type of data has been determined, the data storage techniques may be appropriately assessed. Blobs, queues, files, tables, discs, and application data may all be stored in one place using a cloud service like Microsoft Azure. There are, however, specialized services that deal with particular data subcategories even within the Cloud. Examples of Azure Cloud Services that assist in handling and managing sparsely varying types of data are Azure SQL and Azure Cosmos DB. Cloud can be said to be an integral part of big data operations.                 

Big Data Types

Every day human interactions produce an enormous amount of data each second as Internet usage is thriving day by day. Digital data includes selfies, tweets, emails, purchases, blog articles, and many other types of data. These stored information’s (big data) can be divided into the following types:

Structured Data

Structured data are organized data sets that are easier to evaluate and sort since it has predetermined similar characteristics and is represented in the structured or tabular schema. Each field is independent and accessible separately or in conjunction with information from other fields because it is predefined. Structured data is very prominent because it enables faster data insertion and retrieval from various database locations.

Unstructured data

Unstructured data refers to information that lacks predetermined conceptual definitions and is difficult for conventional databases or data models to interpret or analyze. The major portion of data is made up of unstructured data, such as dates, facts, and numbers. Examples of this type of big data include satellite imaging, mobile activity, audio and video files, and NoSQL databases. The amount of unstructured data is expanding due to the images we post on Facebook, Instagram, and other platforms as well as the videos we view on those same platforms.

Semi-structured Data

A combination of unstructured and structured data is semi-structured data. Semi-structured data is characterized by traits of both structured data and unstructured data (information that lacks a clear organization). For instance, semi-structured data is frequently seen in JSON and XML.

Big Data examples

One of the most significant developments of the digital era is the technology known as Big Data. Powerful analytics tools are revealing patterns and connections hidden in enormous data sets, that influence planning and decision-making in almost every business. Big Data usage has increased so much in the past decade that it now affects almost every element of our lifestyles, purchasing patterns, and everyday consumer decisions. Here are a few examples of Big Data applications in day-to-day activities.

Transportation

The GPS we use to locate places while traveling is powered by big data. Satellites are the main input source of GPS. Example: For transatlantic trips, an aeroplane can produce 1,000 terabytes or more worth of data. Data collected is handled by data analytics tools, which analyze passenger data, fuel efficiency, cargo weights, and weather patterns to maximize safety and energy efficiency.

Advertising and Marketing 

Till now, companies have used traditional ways such as TV, radio, and other methods to study consumer preferences and mindsets for advertisements. To be aware of what people search for, advertising companies own a report of the respective Big data resource. Using accurate measures like click-through rates, views, and technology-based marketing initiatives enhances marketing efficiency. 

Financial and Banking Services

Bank uses big data to spot unusual behavior and anomalies that could indicate fraudulent transactions. Banks utilize big data analytics tools to track and create a report on operational procedures, KPIs, and personnel activities.

Entertainment and the Media

Big Data is used in the entertainment industry to analyze consumer feedback, forecast audience interests and preferences, manage programming schedules, and target advertising efforts. The two specific examples are Spotify and Amazon Prime, both use big data analytics to provide subscribers with customized programming recommendations and other similar functions.

Meteorology

Globally distributed weather sensors and satellites gather a large amount of data to monitor the environment. Big Data in meteorology are used to investigate the trends in disasters, make weather predictions, recognize the effects of global warming, determine the locations on the planet where drinking water will be available, and provide early warning during emergencies like storms and tsunamis.

Healthcare

Big Data is positively changing the healthcare sector. Patients’ electronic health records are updated in real-time using data collected by wearable technology and sensors. Big Data in the health sector used in the following aspects:

• Predicting the onset of epidemics,
• Digital health records,
• Real-time notification,
• Increasing patient involvement
• Plan strategically
• Research speed up
• Telemedicine
• Improved medical image analysis

Cyber security

While big data can put firms at greater risk of cyber attacks, machine learning and analytics can use the same data stores to deter and combat online crime. Analysis of historical data can produce intelligence to develop more effective threat controls. Machine learning can alert suspicious patterns and sequences breaching norms. This enables companies to take measures against threats like ransom ware assaults, harmful insider programs, and unauthorized access attempts. Also, post-attack analysis can reveal the techniques employed after a corporation has experienced an intrusion or data theft. 

Final Thought

Data is one of the most valuable assets for businesses today, and firms everywhere are realizing this. In reality, advances in the field of big data will have the power to drastically alter the world for the better. These write as so far explained what is big data with examples. You may get a better understanding of big data services by visiting our website. You can consider utilizing Rootfacts consulting service and enhancing your company’s performance.