Big Data is a field that makes use of various mathematical and statistical methods to extract useful information from a large amount of data. The collected data is large and diverse, and can be either structured or unstructured. It is beyond human ability to calculate and process using common software solutions.
Processing such a huge amount of data requires expert algorithms with high-end computing devices that can complete the necessary processes in real time. There are various apps, like Facebook, Snapchat, Google, YouTube, etc.
Where people feed a lot of data. This data consists of patterns, which are analysed using various statistical methods to generate valuable information about their surfing habits .Let us try to understand how an e-commerce company, like Amazon or Flipkart, can use the 5 V’s of big data.
1-Volume:- While using popular apps, the users throughout the world generate a huge amount of data. This data consists of their choices, which are related to the different types of products, price preferences, brand preferences, etc. All this information is collected in the backend database of the application.
2-Velocity:- As the users surf these apps, the data is being generated at a very high speed, which is called the velocity of data.
3-Variety:- Variety refers to the different types of data that users generate. The collected data can either be in structured or unstructured form. Examples include structured database files and unstructured image files
4-Veracity:- Extracting useful information from the data requires implementation of effective and accurate methods of collecting data. This process of extracting only useful data and filtering out the unnecessary data is called veracity. For example, extracting information about products that are ordered by a specific age group
5-Value:- The data is first collected and then processed to generate useful information. This generated information should help the company in developing new strategies related to pricing, marketing, and generate some value to the company.
For example, if people of a particular region show interest in a particular product, the company can plan to open a new showroom in that city or state.
Example Of Big Data
Big Data is used in healthcare. We use wearables that can track our health records, like heart rate, body temperature, blood glucose level, etc. Apple has come up with Apple Health Kit, Care Kit and Research Kit, which help phone users to store and access real-time health records on their iPhones.
You have studied about various data collection methods and sources from where data can be collected. Sometimes, the collected data can be in huge quantities. When it is not possible to handle collected data by traditional data management techniques, then it is considered as Big data
A very common example of big data is data generated through social media platforms because these platforms are used by millions of users. They share a variety of information in the form of text, images, audio, and video, and create huge amount of data every minute.
This data is so large and contains different types of information. Processing this data with a single system is extremely difficult. Some specialise tools, skills, and systems are required to handle this data. To understand big data in more detail, let us understand some important characteristics of big data
The 5 V’s of Big Data
There are five main characteristics of big data: volume, variety, velocity, veracity, and value. These are known as the 5 V’s of big data. The concept was an inception of Douglas Laney from Gartner Inc. in 2001. shows these characteristics. Let us now discuss them in detail.
Volume
This term refers to the size of data. The data size is measured in terms of bytes. Normally, if the data size is greater than a terabyte, the data is considered as big data.
Variety
Big data has variety because it is collected from various sources and the users also share or post different types of data. As a result, the collected data is diverse, which means that it may include text information, images, audio files, video files, and sensor data. Variety of data
Velocity
This characteristic shows that the data is being generated every second. In other words, you can say that data is in motion and increasing continuously.
Veracity
Extracting useful information from the data requires implementation of effective and accurate methods of collecting data. This process of extracting only useful data and filtering out the unnecessary data is called veracity. For example, extracting information about products that are ordered by a specific age group.
Value
The data is first collected and then processed to generate useful information. This generated information should help the company in developing new strategies related to pricing, marketing, and generate some value to the company. For example, if people of a particular region show interest in a particular product, the company can plan to open a new showroom in that city or state.
Applications Of Big Data
Big data is a powerful tool and applied in various fields, like banking, education, agriculture, data mining, cloud computing, healthcare, etc.
Healthcare
A huge amount of data is generated in this sector due to the availability of electronic health records. It needs to be handled by big data technologies and it is impacting this domain with various applications, which are:-
1-Personalised Medicine:- The big data techniques are used to give the best medicine and treatment to a particular patient based on his and other patients’ previous data. It is analysed how patients with similar symptoms responded to a particular treatment, and after analysis, the best treatment is offered.
2-Forecasting Health Risks:- The possible health risks for a person can be forecasted based on their current symptoms, eating habits, and lifestyle.
3-Wearable Devices for Personal Fitness:- There are many wearable devices for tracking and checking personal fitness, which include smart watches, wrist bands, etc
4-Pandemic (Outbreak Handling):- Big data also helps in handling pandemic situations by assessing resource requirements, drug discovery, food delivery, etc
Retail
The online retail market covers millions of customers; hence, a huge amount of data is generated. This big data has impacted the retail market sector in a very positive manner. It includes applications in many areas of the retail sector. Some of them are:-
1-Customer Satisfaction:- Analysing customer reviews to get more satisfied customers is an important application of big data.
2-Customer Demand:- By analysing product sales, customer demand can also be understood. That helps both customers and sellers in delivering and getting good products on time.
3-Product recommendation:– By analysing the buying patterns of customers, the retail market recommends products to the targeted customers so as to get a good sale.
Science and Research
Big data helps scientists do research in various fields. Some of the major applications are discussed as follows:-
1-Environmental Monitoring:- Big data is used to analyse sensor data to monitor the environment. It includes forest cutting monitoring, pollution control, tree plantation requirements, etc.
2-Defense Innovation:- Historical data can be analysed to design innovative defense instruments and solutions.
3-Smart City:- Traffic management, resource management, waste management, and many other smart city innovations are designed by analysing historical and sensory data.
4-Climatic Studies:- Climatic observations are stored as big data and analysed to forecast climatic observations.
Sports
Big data is impacting the sports industry in the following areas:-
1-Training:- By analysing historical data, sportsmen can be trained in a better manner.
2-Assessing Sports Popularity:- The viewer review and feedback data are used for assessing sports popularity.
3-Modifying Instruments:- Sports instruments are equipped with sensors that generate huge amount of data.
Social Media
Social media platforms have a huge amount of data that is being generated by users. This data is being analysed for the following applications:
1-Friend Suggestion:- Social media platforms give friend suggestions based on your and your friends’ contact lists.
2-Advertisements:- Relevant advertisements are shown on the basis of individual user’s choice.
Interpreting Data
In the last section, you understood what data is, its types, and the sources from where you get data. The collected data may be used to perform the following:
Step-1:- Identifying or classifying an object or tash
Step-2:- Finding something odd (finding something that is not common)
Step-3:- Predicting or forecasting some information
Step-4:- Grouping similar objects
Step-5:- Taking decision To understand the above-mentioned tasks, answers to some questions need to be found