What Is Big Data Analytics? Definition, Benefits, and More

To leverage big data effectively, organizations must address its challenges to enhance efficiencies, boost profits, and enable innovative business models!

Before discussing the data, it is essential to know that it changes every 60 seconds. So the data that you were hung onto may no longer be relevant after some time. But the statistics and records can be compared, and reports can be compounded to find a track record, and behavior pattern that can help in important diagnosis in healthcare;

Such data is also being used by retail banks to understand how customers use their accounts and identify security risks in banking and securities;

Monetary transactions and real-time trends in the stock exchange are being used by finance industry to generate a lot of data;

It helps identify the units that get manufactured faster; big data is also being used in marketing and advertising;

It is extensively being used in higher education;

Companies like Amazon leverage big data to their advantage by constantly monitoring competitor prices, market trends, and customer demand, so they can adjust their prices in real-time to remain competitive.

Other industries like Transportation, Cyber security, Media and entertainment, Government, Insurance, and Retail and wholesale trade also make use of big data.

What is Big Data?

Big data has been around for some time but it is still surrounded by a lot of confusion. Irrespective of what it brings to the world, this concept is evolving since its inception. It also remains the driving force behind many digital transformations like artificial intelligence, data science and internet of things. It revolves around managing scattered data - grouping, re-grouping, and distribution to make it meaningful and relevant. Every mobile app seeks permissions on mobile devices to perform.

While big data is a comprehensive collection of data, big data analytics is the process of extracting some information out of that data. Mobile apps seek information when a text message pops up when a call rings, when we buy something when we browse a particular site, when money is transferred when a cab is booked when food is being ordered, because microphones are always on, and phone's database saves photos, recordings, videos, sensor data, and written text.

Big Data is not just a fad, but a wave that is already helping change the world in more than one way. Helping improve healthcare (sensors attached to medical devices), predicting and responding to disasters (Sensor data can be analyzed to predict where there is a calamity, and where monitoring and safeguarding refugees away from war zones can be done. Big data can also help in preventing crime as police forces increasingly adopt data-driven strategies to deploy resources more efficiently.   

Big Data Project Ideas

Big data projects are important as these are often combined with other technologies like machine learning to create market strategies based on predictions by customers.

• Traffic control using Big Data
• Search Engine
• Medical Insurance Fraud Detection
• Data Warehouse Design for an E-Commerce Site
• Text Mining Project
• Big Data Cyber security
• Crime Detection
• Disease Prediction Based on Symptoms
• Yelp Review Analysis
• Recommendation System
• Anomaly Detection in Cloud Servers
• Smart Cities Using Big Data
• Tourist Behavior Analysis
• Web Server Log Analysis
• Image Caption Generator

What is Big Data Analytics?

The process of examining big data is called as big data analytics. It is widely used across industries such as healthcare, insurance, education, retail, artificial intelligence, manufacturing, agriculture, government sector, management and supply chain management, and retail to understand what is working and what needs to be improved in the system. The big data can be structured or unstructured and can offer important insights when analytics are applied. It helps in fastening the process and making critical decisions.

What are the benefits of Big Data Analytics?

It’s not just a buzzword but a robust technology that provides insights and opportunities for over-arching problems that the global economy faces. Analyzing large amounts of data quickly can greatly benefit organizations by enabling more efficient use of data to address key questions.

Big data analytics methods are being used with emerging technologies, like AI, and ML, to discover and scale more complex insights. Such insights are also helpful in improving the way a society functions.

Also, big data analytics process and study is important as it allows organizations to leverage vast and diverse data from various sources to identify opportunities and risks, facilitating swift decision-making and enhancing profitability.

It is cost-effective, improves operational efficiency, enhances product development through a better understanding of customer needs, and gains market insights by tracking purchasing behavior and market trends.

How does it work?

Big data analytics involves collecting, processing, cleaning, and analyzing large datasets to help organizations make use of their big data. (1) It starts with collecting data from various sources, (2) then organizing and processing it to ensure accuracy. (3) Data cleaning is essential to improve data quality by removing duplicates and irrelevant data. (4) Fourthly, data analysis techniques like data mining, predictive analytics, and deep learning are used to extract valuable insights from the data. Analyzing data also involves data mining (sorting data), predictive analysis (making predictions on historical data), and deep learning (imitating humans by using artificial intelligence)

Big Data Analytics Tools and Technology

Big Data is a vast platform that can be tweaked as and when required. Major players of the platform are Hadoop, NoSQL database, MapReduce, YARN, Spark, and Tableau.

Conclusive: What did you learn from the conversation?

Big data is a large amount of data that can be structured, unstructured, or semi-structured. Sometimes collecting and processing data can be difficult. If collected, it can be difficult to maintain. If maintained, it can be difficult to secure. If that is also set, it can be difficult to find the right tools and platforms to develop according to specific needs. The right solution will be flexible to assimilate future infrastructure changes.

Alternatively, big data analysis can benefit every function in a company. It can be gathered willingly through personal devices and applications, product purchases, questionnaires, and electronic check-ins, as well as publicly published remarks on social networks and websites. Big data analytics companies widely use it to improve science and research; improve governance; understand and target customers; smart cities; improve healthcare and public health; financial trading; and optimize machine and device performance!