Big data is defined as a technique which is used to control and manage a large amount of data set. Many organization contains very large data but they are not able to handle some challenges such as analysis, data curation, sharing, and data visualization and information privacy (Chen, & Zhang, 2014). To avoid such kind of problems, information and communication technology has established a new method that is big data. The main goal of this report is to appreciate the fundamental idea of big data with their advantages and disadvantages. Today most organization analyse the data with the help of big data technology because it has the ability to control and monitor huge data. The word big data refer to the usage of prognostic analytics and this technology is more efficient for the visualization of data. With the help of this technology consumers can handle data or information in a computer system and it is observed that the rate of big data has increased by 40% in the last five years.
The fundamental concept of big data technique is completely based on the data analytics approach. Many organizations understand that if they detect the data which streams into their commercial then they can apply this process for analysis. Big data is an advanced technology that comprises data and it also used to store the consumer’s data. The term big data was identified by Roger Douglas in the year 2005 and the application of this technology is something that has been in reality for a long duration. The colossus is in one of the first data processing technique that was introduced by the British in the year 1943 (Chen, Chiang, & Storey, 2012). This machine was used for searching for the data pattern and record user’s data at the rate of five thousand characters per second. From this investigation in the year 1952 the United States created a national security agency that uses a machine learning program to handle a large amount of data. The first data centre was developed in the year 1965 for storing billions of tax and fingerprint sets.
During the generation of big data yahoo developed an open source Hadoop for indexing the complete World Wide Web. At that time the use of social media was increasing very fast and a large amount of data were detected on daily basis (Chen, Mao, & Liu, 2014). Many government communities and business established big data projects like in the year 2009 the biggest biometric database created and governments analysed and stored fingerprint and iris scans of all consumers. In the last few years, many organizations have introduced a new approach to big data, for example, HCL, Google and many more. In the year 2017, the rate of this technique has grown by 30% due to this increment information and technology developed many processes to handle human data. 80% of the available data has been developed in the last 2 years and the use of big data process is growing very quickly because many consumers use social media for communication.
Big data technology helps business communities to harness their data or information and use this technique to produce a new opportunity for analysis. This technology is making a new generation of decision support data management and many industries are identifying the potential value of this data and putting into a technique. Information and technology developed many approaches for maintaining data for example simulation, machine education, and regression analysis but these are not much efficient. For which big data technology has been created that has the ability to analyze both structured and unstructured data and a recent study indicated that in the year 2015 big data provided almost 4 million jobs globally (Fan, & Bifet, 2013).
It is also making a huge demand for consumers and organization’s that can store and analyse big data technology. Recent investigation shows that in the year 2018 the United States faces a shortage of 140,000 to 190,000 individuals with deep analytics (Gandomi, & Haider, 2015). Big data technology represent a blog of records where data of every user can be analysed and it is a correct statistically that provide a clear understanding of pictures, documents and data. It has a volume which needs a parallel processing and a special model to store human data and it is not possible to access one computer. The main reason for making big data technology was to store and analysis the huge amount of data and it has the capability to recognize the customer data. This technology has numbers of resources, for example, every mouse clicks on a web link that can be stored in web log files and analysed to understand the behaviour of consumers. This technology involves data sets that store, manage and capture data. This technology is very popular and it can identify the most efficient platform to improve the business. Machine learning and digital footprint both are very common big data technologies that use for analysing consumers data. It is high velocity, high variety and high volume that need latest forms of processing to increase decision making and process optimization and a new veracity has been added by some communities to describe the concept of big data technology.
There are many characteristics of big data technique which are described below:
The amount of data which is produced is most significant in this context and the main role of this step is that it identifies the value and potential of the data. It is also called the size of the data and organization can analysis a huge quantity of data at a time.
The next step of big data technology is that variety that defines the category of data where information divided into subparts. This provides a platform to help the consumers that are very closely analysing the data and are linked with it.
The term velocity is defined as the speed of generation of data or in another word it identifies how debauched the data is shaped and handled to meet the requirement of the consumers (Gantz, & Reinsel, 2012).
This is in one of the serious factors that can be an issue for those organizations use big data for analysis purpose. It is defined as the inconsistency that can be indicated through the data or information at eras thus hindering the procedure of existence bright to control and achieve the data more effectively.
The value of the statistics being apprehended can vary from person to person and it is observed that the precision of study completely depended upon the veracity of the source facts.
The management of facts is very complex and crucial especially for a huge quantity of data and information comes from numbers of resources. These consumers’ data require be connecting and correlating in order to grasp the data which is hypothetical to be taken through these numbers sets. This condition is called the complexity of the information set.
There are main 5C systems used in the cyber-physical systems which are described below:
There are numbers of technologies involve in big data, for example, crowdsourcing, integration, machine learning, data fusion, A/B testing, signal processing, visualization and time series algorithm. The massively parallel processing is an advanced technology that has the capability to handle and store a petabyte of data (Hashem, et al., 2017). DARPA technology data analysis approach pursues the essential construction of enormous data circles and in the year 2008 ayas has launched this technology and now most of the organizations are using this for analysis of data.
Cloud computing is a modern technology which is used to store and monitor the consumer’s data and it is also used as a backup plan by which the problem of cyber-attacks. This kind of technique generally used in big data to improve the scalability, for example, organisations can add more than 15 computers in several clicks (Kitchin, 2014).
Hadoop is an approach which is used to distribute a large amount of data from one location to another. The main role of this process is that it breaks a huge chunk into very small pieces on different computer networks. HDFS is the part of Hadoop system that has the ability to simulate multiples files at a time and it can be used to address the large data files.
Apache Spark is a type of technique which is used for parallel data processing that makes a real-time analytics. The main advantage of this process is that organizations can easily find the nature and behaviours of consumers by which they can improve their productivity and performance. There are many advantages to this technology first of all; it gives a comprehensive outline to manage big data technology with a variety of database. It also enables Hadoop clusters to simulate 100 times faster in memory and 10 times faster when it runs on disk. It can be written in any language like java, python, and scale and it can be used to balance the consumer’s data. Therefore, many organizations use this technology for analysis and manage the user’s data and it is observed that in the last two years the use of apache spark has increased by 30%.
Big data technology has enhanced the demand for information security specialists in many organizations such as IBM, EMC, HP, AG, Oracle Corporation, and dell. All these business communities have spent around $15 billion on software to manage and control the human data or information (Labrinidis, & Jagadish, 2012). In the year 2011, this organization’s spent around %100 billion and they were increased their share of more than 10%. It is investigated that 1/3rd of the data is deposited in the procedure of alphanumeric transcript which is a very most common method to manage huge data. There are lot of applications of big data technology which are described below:
This is one of the best applications of a big data process that allows a way to access and control the consumer’s data in terms of cost, innovation and productivity. The recent event shows that this technology does not come without their flaws and data analysis need numbers of the central government to work in collaboration and produce new process. In the year 2012, the United States developed big data investigation and development to address the issues faced by the government during the data managing process. Initially, they composed big data into 6 departments and produce around 84 big data programmes (LaValle, et al., 2011).
The actual use of info technology indicates that big data process can make a significant contribution to managing the consumer’s data. It also provides the gainful chances to enhance executive approach in many growth sectors, for example, employment, economic productivity, resource management, and health care (Lazer, Kennedy, King, & Vespignani, 2014). The main challenge faced by the big data is security because hackers use malicious software to access consumer’s computer networks.
According to a recent investigation big data process provides a way to improve the performance and efficiency in manufacturing. It delivers an infrastructure for transparency in the field of manufacture industries which is the capability to avoid the problem of uncertainty and inconsistency in the performance (McAfee, et al., 2012).
Modern PHM process implemented data analytics code which can perform more effectively when large data or information involves in machine learning. To control and manage the machine life cycle a new approach is needed for which information and communication technology developed big data technique that controls data more effectively (Madden, 2012). In private sectors this technology plays a significant role, for example, Wal-Mart organization handles around 1 million consumers every hour which is done by using big data technology. Numbers of retail banks use big data technology because they communicate with many users in a day for which they analysis data by using this technology.
There are many drawbacks of this technology which are described below:
There are many challenges faced by these technologies which are described below:
The most common challenge occurs in big data process is storing and analysis data or information. It is estimated by the digital universe that the quantity of data stored in the information technology system is doubling every 2 years (Provost, & Fawcett, 2013). In which the rate of unstructured data is very high that means it does not reside in the computer database. It is very difficult to store and control audio, video, and other unstructured information and this problem are increasing very fast because many organization dealing with huge unstructured data.
Many organizations use this technology to achieve their business goals but they also used to store their big data which is also a crucial problem. This technology was developed to control and manage big data not to store human data for which information and communication technology developed cloud computing to store business data (Raghupathi, & Raghupathi, 2014). Every business industries want to improve their decision-making process for which they adopt third-party servers due to which the problem of insight occurs.
Data integration is also a very common issue faced by big data technology and it is observed that big data comes from various places such as social media, emails, and enterprise and employees documents. To combine all these data and produce a new report that can increase the difficulty in big data for which vendors provided many software’s and tools but many organizations say that they have not resolved the issue of data integration yet.
Security of information is one of the crucial problems for every technology and big data is very less secure. In the last few years the issue of security is growing very fast because hackers use malicious software to hack human data (Swan, 2013). They produce traffic and unwanted signals and transfer to the organization computer network by which they easily enter into computer devices and block user’s personal information (Wu, Zhu, Wu, & Ding, 2014). There are various kinds of security threats occur in big data, for example, denial of service attack, malware, and ransomware and wanna cry attack and data breach. In the last two years around 40% of organizations were suffered from the issue of ransom ware and DOS attack.
It is recommended that the issue of security can be resolved by making security strategies and policies and information and technology developed advanced analysis approach like apache spark that can be adopted. Generally, hackers share fraud emails and unauthentic signals to employees accounts that are developed by malicious software and by which they encrypt their private details (Zikopoulos, & Eaton, 2011). To avoid such kinds of problems organization can adopt a firewall, encryption, and antivirus and cryptography technology. Encryption is a very popular technology that converts data into the form of code which cannot be easily read by hackers and transferred from one place to another. By using this technology people can address the problem of a data breach in big data.
Conclusion:
Big data is a very popular innovation in the field of information technology which is used by many organizations to control and monitor their large data. By using this approach people can analyse and handle huge data like audio, video, pictures and other unstructured data. This report is completely based on the summary of big data and with the help of this report readers can enhance their knowledge in the area of technology. There are main five characteristics of big data such as volume, variety, veracity, velocity and variability all these are described in this report. This research report explained the fundamental concept of big data technology with their advantages and disadvantages and also evaluated the challenges faced by this technique. People should ensure that they use only authentic servers and they can adopt security plans to avoid security-related issues such as firewall, encryption and biometric recognition.
References:
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