Difference between Big Data and Hadoop
In this modern era, a tremendous amount of data is being generated and processed every second. With this data, diverse platforms have been created in this landscape, which includes Big data, Data analytics, Data science and many more. Data is the biggest asset of any business organisation in today s world. According to Forbes- ” The total data market is expected to nearly triple in size, growing from US$69.6 billion in revenue in 2015 to US$ 211.3 billion in 2020.
With an introduction of new technologies and application in the digital economy, many organisation have opened up in Big data landscape. Data science, Data analytics, Data mining, Data engineering etc, all fall under the same category and work together in the same platform. Most of the people quite often interchange these terms but there are very large differences among them. A similar type of ambiguity exists with the term Big Data and Data Analytics.
Hadoop is an open-source software application which allows users to stores data and runs the application on any hardware. Hadoop provides huge storage for storing data and enormous processing power that can perform a limitless task without facing any difficulty. Hadoop is written in the JAVA programming language and currently, it is the best project accomplished by APACHE. Hadoop was developed by Google on the MapReduce system.
Hadoop follows the concept of horizontal scaling instead of vertical scaling. In horizontal scaling, you can quickly add new nodes to the HDFS cluster and run it as per your requirement. Hadoop can store all kind of data whether it is structured, unstructured or semi-structured. Hadoop also allows you to follow Write Once Read Many concepts. You can just write any kind of data once and you can read the same data as many times you want. Hadoop follows multiple advantages like Reliability, Scalability, Flexibility and Cost-effective.
Hadoop works as a single unit which means that if one of the machines fails to operate, another machine will take responsibility and work in the most reliable and effective fashion. Hadoop infrastructure has been in-built on fault tolerance platform which proves that Hadoop is highly reliable. Not only this, Hadoop can small cluster, for example, laptops and PC, all the data nodes can have normal configurations. Hadoop is open-source software which has no cost of licensing or in common layman terms, it is absolutely free of cost.
Hadoop has an in-built capacity of expanding and integrating it with cloud-based services without causing any interruption. So, if you are thinking about installing Hadoop on a cloud then you don’t need to worry about the scalability factor because you can expand your set up within a few minutes whenever you want. Hadoop can deal with all types of data. You can store any type of data whether it is structured, semi-structured or semi-structured.
Applications of Hadoop
Hadoop helps business organisations to make decisions based on various analysis of data sets and multiple variables, rather than concentrating on a small sampling. This feature of Hadoop gives users more comprehensive views of their customers, risk analysis, marketing, operations etc. To display the same results without using big data and other analysis, the organisation need to focus and conduct multiple and limited data analysis. That ‘s why business organisations use Hadoop for obtaining the best analysis.
Here is some application of Hadoop:
- Optimising Machine Performance– Hadoop is used by many giant companies in the mechanical field especially to develop self-driving car by automation. Automation and Hadoop together help to run the car without a human driver. Just by providing some informations based on GPS, traffic, sensors, you can easily tell your car what to do and what not to do.
- Healthcare– Hadoop is used in the medical field to improve public health. Hadoop monitors the daily activities of an individual by tracking their heartbeats, pulse count, blood pressure level by different sensors by utilising a huge amount of public data stored in the system. This deduces which medicine and prescriptions can be provided to an individual which can improve the health of the country.
- Understanding and optimising the functions of business organisation– Business organisation uses Hadoop to compile the performance and growth of the company in different ways. Retailers can customise their stock performance by various predictions using social media, google searches, market researches etc. This help organisations to make the best decisions to improve their profits and maximise their returns. Many organisations use Hadoop to improve workspace by monitoring their employee behaviour. It tracks daily activities of every employee to monitor the interactions and behaviour of every employee.
- Business Forecasting and Financial Trading– Hadoop has complex algorithms that scan the market with defined conditions and criteria and conditions to find out trading opportunities. Hadoop uses algorithms to make important decisions on stock predictions.
- Science and Research- Hadoop plays an important role in science and research field. Hadoop helps to take many important decisions after successfully compiling a huge amount of stored data. This helps to draw conclusions with fewer efforts as compared to the earlier time.
Big Data is a field that deals with systematically extracting the information from the large and complex, structured and unstructured data which are difficult to solve using normal data processing software. Big data is generally associated with three main V’s- volume, variety and velocity. When there are large structured and unstructured data, we are primarily concerned with observing and tracking those data. In the current scenario, Big data uses predictive analytics, user behaviour analytics and other typical analytics methods to extract information from data. This analysis of data can find a new development in medicine, science, technology and so on.
It is not easy to process bid data using the traditional methods of data analytics. Therefore, specialised modelling techniques are being used to process these unstructured data and extract useful information required by the organisations. Big data help to solve these unsolved and unpredicted problems, revelling the unknown information and strategy behind customer needs and requirements.
Application of Big Data:
- Manufacturing– According to recent global studies conducted by TCS, improvement in supply planning and product quality provides the real benefits of big data in the manufacturing sector. Big data provides a platform for transparency in the manufacturing industry which shows the availability and growth in performances. Thus, big data acts as an input of predictive tools and preventive strategies in Health Management.
- International development- Various researches on Information and Communication technologies suggests that big data can make an important contribution to international development. Recent advancements of big data offer different opportunities in the field of health care, cyber, security, crimes, economic productivity, natural disaster etc. Additionally, user-generated data offers new discoveries which are lacking behind due to some reasons. However, there are still some problems which are yet to be covered by big data such as privacy issues, imperfect methodology and interoperability issues.
- Medicine and health research– Big data in health research is continuously striving to increase its results in the field of biomedical research, as data-driven analytics is moving forward than hypothesis-driven research. This trend generated by big data can be tested in clinical researches and traditional follow-up biological researches.
- Information Technology– Big data has help business operations as a tool to help the business employee to wok more rapidly and efficiently, collecting and distributing the resources in IT. By applying the principles of big data and machine learning and deep learning, IT departments can easily trace potential issues and move to provide a more accurate solution before the problem arise.
- Insurance– Health insurance providers are collecting data on different useful topics on social Determinants of health such as food and TV consumption, clothing size, purchasing habits where they can predict the cost and revenue, in order to spot health issues of their clients. It is difficult to say whether this information is being used for pricing purpose or not!
Difference between Big Data and Hadoop
There are lots of difference between Big data and Hadoop. Hadoop is a software which is programmed in such a way that it accomplished its goals and objective underlined by the users. Big Data uses various platforms like Business Intelligence, Machine Learning and Artificial Intelligence for optimising the data and display better results according to the user-defined instructions.
Big data is simply a huge collection of data that business organisations use to achieve their goals and operations. Big data can include various types of data stored in different kinds of formats. For example, business organisations put lots of efforts to collect every single piece of information contained in the form of data on purchases in currency formats, on customer identifications like name, address, contact number or social security number or sales inventory numbers.
Hadoop is one of the software designed to handle Big data. Hadoop is specially used to interpret the results of big data searches through special algorithms and optimisations. Hadoop is open-source software designed under Apache and it is maintained for the global community of users. Hadoop has various components such as MapReduce and HDFS to optimise its functioning and reduce the load.