Big Data : First of all let me tell you that if you want to get complete information about Big Data then you are absolutely right place and reading the right article. Here you will be given complete information about Big Data in detail, I claim that after reading this article, you will not need to read any other article. Now you have to spend some time and read the whole article.
Big data refers to data that is so large or so complex that conventional ordinary data processing applications are not sufficient to work with them. Big data is data sets that are so large or it can be complex that traditional data processing applications are inconsiderable. Now Big Data will be discussed in further detail.
What is Big Data?
Big data is also a form of data but as its name suggests, it is of large size. Big data is used to describe a collection of data that is vast in volume and is growing rapidly over time. This type of data is so large and complex that no traditional data management tool has been able to store or process it efficiently.
Before understanding big data, you have to understand data, data means information, if we talk in general terms, it can be in any form, like you read a newspaper, then you get different types of information in it. which is written on a paper. This is also a type of Data.
But if we talk about the digital form of these information then they are generated and processed by computer/laptop, i.e. any activity done digitally forms a data, like you send email, take photo, make video. it's all a data.
Big data refers to a very large form of data, which is created by increasing the size of various smaller data. It resides in different formats, which cannot be handled by traditional tools and applications, and the size of this data keeps on increasing continuously. That is, Big Data is a huge form of data itself.
Big Data is a technology to collect, maintain and process whatever data we want through digital medium whether it is Facebook or whatsApp or other means. In which data is analyzed and used in business process engineering, analysis of medicines in the medical field and human resource management and selection of talents.
It is very easy to understand, for example, you are asked how long you use mobile throughout the day, your answer will be that you use at least four to five hours, in this four-five hours of use, what you Even if the data is saved through Facebook or Twitter or other means, that data is saved in the server of Facebook or other software companies, millions of people like you do the same thing, we can call this data as Big Data, this data is processed by software companies using big data technology and used in user behaviour analysis and product marketing. Taking this article forward, we are going to discuss about how many types of Big Data are there.
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Types of Big Data
There are three types of Big Data which are given below-
1. Structured Big Data
2. Unstructured Big Data
3. Semi-structured Big Data
1. Structured Big Data : Any data that can be accessed, processed and stored in a fixed format is called "structured" data. Day by day, technology in computer science has achieved more and more success in developing techniques for working with this kind of data (where the format is already well known) and is gaining value outside of it. However, nowadays, we are seeing issues when the size of such data becomes very high, with typical sizes being in the range of several Gigabytes.
An example of structured data is given below to make you understand that an “Employee” table is structured in the database-
2. Unstructured Big Data : Unknown structure of any data is known as unstructured data. Apart from being huge in size, unstructured data presents many challenges in terms of its processing, from which it derives its value.
Combination of simple text files, videos, images, are heterogeneous data source it is a typical example of unstructured data. Any organizations have a wealth of data available to them but unfortunately they don't know how to get value out of it. This data is in its unstructured format. The result returned by “Google Search” is the best example of unstructured data.
3. Semi-structured Big Data : Both forms of data can be a Semi-structured data A semi-structured data can also be seen in a structured form but it is not completely defined. In other words it can be said that it is not really defined with examples. A table definition in relational DBMS. An example of semi-structured data might be data displayed in an XML file.
What is the use of Big Data?
Data Analyst performs a thorough investigation of Big Data through customized software tools, for which a process of Data Mining and Data Analysis is used, after which the necessary information’s from the Big Data is extracted.
That information can be anything, which includes data of companies, personal data of people, data of social sites i.e. data of every digital activity used by people every day.
Then all this information is used by big companies to develop their marketing strategies, understand customer behaviour and increase customer satisfaction, so that their products can be reached to the interested customers and increase their sales.
Let me tell you the use of it in very simple words, it will happen with you often. For example, some day you searched "watch" on the internet, then whenever you open any site after that, the ads of "watch" often appear in front of you. It has been filtered from Big Data that you are searching watch, you need watch, so watch ads are often shown in front of you.
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Characters of Big Data
There are mainly three characteristics of Big Data, Volume, Variety, Velocity, on the basis of which they can be understood, let us know how the main features of Big Data work :-
Volume in Big Data
The name big data itself refers to the size that is very large. In Big Data the size of the data plays a very important role in determining the value of the data. Furthermore, whether or not a particular data can actually be considered big data depends on the amount of data. Therefore, volume is a feature of Big Data that needs to be considered when dealing with Big Data.
Volume is the most important feature of Big Data, because of the volume it is named Big Data, when the data is analyzed then its size is the most important, through this we can know how much size the data is , just normal. The size of Big Data is at the level of Terabytes and Petabytes.
Variety in Big Data
It would not be wrong to say that Big Data without Variety is disabled, Variety is a very special part of Big Data, which shows what format the data belongs to. If we talk about the nature of the data, then most of the data that is in our database is structured data like save tabular form data in our database which we also call RDBMS database.
There are some other types of data which we call semi-structured data. In the end, importance is given to unstructured data, which is a very difficult task to convert into structured form. All that data which is saved through images, audio or social media comes in the category of data unstructured. The main function of Big Data is to convert unstructured data into useful formats.
Diversity is the next aspect of Big Data. It refers to both structured and unstructured data for the heterogeneous sources and nature of data. In the earlier days, spreadsheets and databases were the only sources of data that most applications considered. Nowadays, data is also being considered in analysis applications in the form of data, email, photo, video, surveillance equipment, PDF, audio etc. This diversity of unstructured data presents some issues for the analysis of data, storage, and mining.
Velocity in Big Data
We all know that the speed of internet has increased very fast so the speed of data creation has also increased, due to which velocity is an important feature of Big Data, in which its frequency and speed is analyzed at the time of creation of data.
The speed of data generation is known by the term velocity. Velocity is used to measure how fast data is generated and processed to meet demands, determining the actual capacity in the data.
Big Data Velocity basically refers to the type of data that data flows through business processes, application logs, networks and social media sites, sensors, mobile devices etc. The flow of data should be massive and continuous.
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How is Big Data Generated?
Basically Big Data consists of two types of generation: 1. Machine Generated and 2. Human Generated Data.
1. Machine Generated: - This data is the data generated by computers and other machines, in which there is no human intervention or such as computer logs, application logs, etc.
2. Human Generated: - This data is generated by humans. We all use social sites like Facebook, Instagram, YouTube, Twitter, Gmail etc. These include all types of data like photos, videos, emails, all this is called Human Generated Data.
Types of Big Data Analytics
Descriptive Analytics: - This is the first stage of data processing, in which the previous historical data is extracted from the raw data and the data is prepared for the next process. That is, through this, the performance report of a business can be extracted from last year to year and accordingly further strategy can be made.
Diagnostic Analytics: - The way the further strategy is prepared by examining the past data in Descriptive Analytics, similarly the answers to the questions are found in Diagnostic Analytics. For example, if there is a significant increase or decrease in business at any one time of the year, the reasons for this are found, then in Diagnostic Analytics, answers to such questions are found and appropriate action is taken on it.
Predictive Analytics: - In this, on the basis of Descriptive and Diagnostic Analytics data, the business opportunity is estimated which completely depends on the quality of the data and accordingly the business strategy is made like if take the example of retail. Based on the data, the sales of a product can be estimated and appropriate work can be done accordingly.
Prescriptive Analytics: - By this, historical data is used to overcome the future difficulties in a business, and it helps in making strategies for the preparations to deal with them, for which Machine Learning and Artificial Intelligence are used.
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Big Data Analysis Technology
When it comes to data analysis, many technologies have been developed for this in Big Data, using which data analysis and visualization is done, let us know which technologies are used in these :-
1. Machine learning : Machine learning is an important contributor to big data analysis, which converts data into full form using computer algorithms, which is used in email filtering, speech recognition, and medical fields. The important task of machine learning is to convert data into computer algorithms to usable form.
2. Cloud computing Technologies : Cloud computing feature is one of the #top 5 technology, using cloud computing in Big Data, data is shown on the internet in a useful format in which the data resides on a centralized server in one place, and we can use it anywhere in the world. The best example of this can be YouTube, Facebook and other social networking websites, which work in cloud computing technology.
3. Big data charts technologies : If you want to understand the nature of any data, then it is easiest and useful to understand it through pictures, in view of this, there are many visualization tools in Big Data too, using which we can present the data in chart form. By using chart we can present the data in different forms.
What are the benefits of Big Data Technology?
When any technology comes, we do not get its benefits immediately, we understand about it gradually, like take the Internet itself, nowadays there is no one who is not using the Internet, by using it We are saving our time as well as money, let us know what are the benefits of Big Data Technology.
Decrease in the cost of the product : When you buy any goods online through internet, then you have to fill a form called product report, which tells your opinion about the product, all these details are saved in centralized server, which is called Big Opinion about the product is formed using data technology, if the product is not correct, it is removed and new product is developed according to the user requirements, all this process is very much with the advent of big data technology. It is done in less time, which reduces the cost of the product.
Increase in sales of goods and customer satisfaction : Friends, whenever you buy any goods, if that goods is good, then you tell friends about it, due to which the demand for that goods suddenly increases, do you know that Big Data is behind it, when Even if you buy goods online, then register your opinion about it, millions of people like you give their opinion about it, which is made using data technology to make this product better, due to which the customer is satisfied, There is also an unexpected increase in the sale of goods.
Retail : Market trends can be understood, that is, what product the customer wants at what time in the market, and what type of product the customer is interested in, the information of all these points can be extracted from Big Data and business sales can be increased.
Health: Big data analysis has an important role in the field of health, in which information of millions of patients can be collected and analyzed by various hospitals, and information about the steps taken in the treatment can also be taken so that the patients coming forward are treated properly. possible and better care can be taken.
Bank: The bank has direct access to the financial data of the customer, such as how much is the customer's salary, how much is the savings or how much is being spent by the customer, so with the help of big data processing, all the rest of the customer. Activities can also be monitored. That is, the Customer Behavior can be understood and accordingly loans and credits are offered to the customer where there is more possibility of sale and also Big Data Analysis can be taken advantage of in fraud control.
Politics: It also has a big role in politics, so that past voting data can be understood, and new voter trends can be detected, in which individual voters can be attracted by advertising and other means according to their choice. Which increases the chances of profit somewhere.
Disadvantages of Big Data Technology
When any technology comes, then along with its advantage, it brings disadvantage as we use computer, it has many advantages and disadvantages too, let us know, what are the disadvantages of Big Data Technology :-
Data maintenance is more expensive : As soon as you take the name of Big Data, you must have understood that the amount of data is very high, which cannot be stored in a normal server, for this high end data server is needed which costs a lot, there is also a reason, That the data that is saved has to be maintained, due to which there is a huge cost in its maintenance.
Data not in correct format : Nowadays, whatever data is being saved in the server, most of the social media files which contain videos, image files or other types of unstructured files, which are expensive to convert into structured form, are also time consuming, and not necessary. , that this data can be useful in business analysis.
Examples Of Big Data
It would be appropriate to tell about Big Data through some examples so that you can understand very easily.
Social media : Statistics from just one social media such as Facebook show that 500+ terabytes of new data are added to the database every day. This data is mainly generated in the context of photo and video uploads, message exchanges, comments etc.
Jet engine : The data shows that a single jet engine can generate 10+ terabytes of data in a flight time of 30 minutes. There are several thousand flights per day, due to which the estimate of data generation reaches petabytes.
New York Stock Exchange : The data shows that The New York Stock Exchange generates approx one terabyte of new trading data per day.
Architecture of Big data
To analyze the data in Big Data, Big Data is mainly divided into 4 layers, their main function is to analyze the data and divide it into different components, let us know what is the function of these layers.
1. Sources layer : Finding out about the sources of data and also deciding what is the format of the data is the main function of the big data sources layer, such as deciding whether a data is structured, semi-structured, or unstructured is the responsibility of this layer. The main task is to find out Velocity, Volume is also the work of sources layer.
2. Data massaging and store layer : Preserving the data and converting it into the correct format so that it can be analyzed is the main function of the data massaging and store layer. For example, suppose an image file is coming and it has to be stored in Hadoop Distributed File System (HDFS), then it is the task of this layer to convert the data according to that file system.
3. Analysis layer : The function of Analysis layer in Big Data is to use the information gathered from sources layer and store layer to create algorithms and present the information to be used by using existing tools, this information can be used in creating advertising and business intelligent concepts.
4. Consumption layer : The main function of the Consumption layer is to inspect the information provided by the Analysis layer and convert it into Business Intelligence report, which is used by the companies to design the product and present it in the market as compared to their competitors.
Big Data technology in the future
In Medical field : Now-a-days the record of every patient has become online in which the record of his medicines and the complete details about the disease are kept secure on the central server, using Big Data technology the complete history of that patient can be easily analyzed and who is the patient. The decision of whether to give medicine can also be taken immediately, which will be the biggest contribution of Big Data technology in future.
In Marketing filed : Nowadays companies spend the most money in the marketing of any product, whether it is online advertising or TV advertising, which costs a lot, by using big data technology, companies can reduce this expenditure somewhat in the future. For example, if you buy any product, then you have to register your opinion about it on the company's website or online website, the details of which are with the company, companies will use Big Data technology for the same in future. By using the details, they will make such products, for which they will have to spend less money in marketing.
How does Big Data work?
Just as thousands of GB of data per second are collected in Big Data, all types of data are there in them like text, audio, video, images and social sites, out of which some data remains structured, like companies etc., and mostly Quantity is of Unstructured or Raw data, which comes from social sites and other sources.
So to handle such a huge amount of data, customized data processing software tools, etc. and hardware devices are used, by which their work information is extracted from the raw data.
Last Word
Friends, I have tried my best to reach you a better article about Big Data. By the way, Big Data is such a big ocean that as much as is written about it, still it seems less. But for the sake of information, all those points have been discussed which is necessary. If you are satisfied with the given information then like and share it.
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