At present, companies are using big data and analysis to stay ahead in the competition. The market is data-driven and crucial for the growth of the business. Data emerges from various sources and in different formats. The internet has given rise to popularity on social media platforms and most of the data today comes from such social media and this data is mostly in the unstructured format. In traditional times, the data was not in an unstructured format and was manageable with the conventional tools, but presently the amount of data is generated cannot be managed using those tools and systems. The advancement of technology has introduced Hadoop as a framework to manage massive amounts of data with minimum efforts and time. It also leads to the creation of ample job opportunities for individuals. For building a study future, Big data Hadoop training can help individuals to get hands-on training with practical experience.

What is big data?

The companies on an everyday basis get enormous amounts of data from multiple sources. It becomes very difficult to differentiate which data is useful and which is of no use. It is a collection of data that is very complex to process with traditional tools.

Types of big data

 Structured: Structured data is in the defined format and it can be easily accessed by using database management systems.

 Unstructured: Unstructured data emerges in various formats such as in the forms of images, texts, documents or video. It is hard to categorize. With the growth in social media, unstructured data constitute the majority of the data that appears. and become hard to manage.  

 Semi-structured: This type of data is in a semi-organized format. It cannot be organized in a fixed format.  

Why Hadoop is required?

Hadoop is an open-source framework that is used to process and manage enormous amounts of data. Hadoop mainly stores data and running applications and in the cluster of computers. Hadoop is a powerful tool that has emerged for processing data and also to solve complex problems. It utilized simple programming models for the operationality. It mainly uses the Mapreduce model for the processing of big data. It is a flexible and highly fault-tolerant platform that eliminates the loss of data in case of failure of the system. It works in a manner that it splits the files into the large blocks and apportion across the nodes.  

Hadoop constitutes 4 modules which are

•  Hadoop Common: These modules contain the libraries and other utilities that are needed by other Hadoop modules. It caters to the need of developers by enabling them with the tools to read files in the Hadoop system. 
• Hadoop Yarn: Using Hadoop yarn modules, the developers are enabled to manage the resources for managing the data resources in the system. 
• Hadoop Distributed File System: It is responsible for the storage of massive amounts of data in easy structures that can be accessed through the networks. 
•  Hadoop MapReduce: This module caters to the processing of large datasets and maintains in a structured format and manages the analysis of data stored.  

Most noteworthy features of Hadoop

• Open source: It is an open-source framework and highly recommends to the developers. It is very widely used for management and storage of data: Hadoop is popular as it is readily available;e to implement in the systems.

• Easy on pockets: As it is an open-source framework that comes with no licensing fees and provides for an affordable tool for storage of data.

• Fault-tolerant: It is a powerful and feature-packed framework and eliminates the risk of data being lost. In this framework, every node has 3 duplicate nodes and when there is a system failure, data is automatically saved on the different nodes and save it from loss.

• Highly Scalable: Hadoop proves to be high in scalability as it manages to store and process large amounts of data at high speed and that too at very inexpensive servers.

• Vastly Flexible: This framework is flexible as it allows the users to store data in various formats such as structured, unstructured for later use. The data saved need not be pre-processed.

• Speedy: Hadoop is a robust framework that locates the data stored in any location in a quick time and process pools of data in a reduced time.

Why Hadoop training is gaining popularity?

• Big Data Management: The growth of data is rising exponentially and so is the demand for an effective tool for its management. The uproar of data has surged to enhance the demand for Hadoop developers in the market. Hadoop is capable to manage high volumes of data in minimum time without costing a lot. It is an open-source framework and easily available to the users without paying any licensing fees.

• High in demand: To meet the needs of big data management and analysis companies are hiring Big data Hadoop developers and administrators to take leverage the technologies meeting their business goals Hadoop has surfaced as a popular tool and creating colossal employment opportunities for the candidates.

• Lucrative career: As the demand is high for the Hadoop developers, companies are paying high salaries to the candidates who have practical knowledge and experience. It is one of the most engrossing things about building a career in this domain. The skills gap and demand enable the professional to garb handsome salary packages.

How Hadoop training can help you?

For gaining proficiency, training is the best path for the candidates to learn and grow skills. KVCH is an acknowledge Big Data Hadoop training provider with more than 28 years of experience in rendering training services. The students get hands-on training under the guidance of industry experts with many years of experience in the relevant field. It provides authentic industry experience by practicing ion real-time projects. Training helps individuals to grow skills and prepare to step on the road for the future.

Career outlook for Big data Hadoop professionals:

•  Hadoop Developer
•  Hadoop Admin
•  Data Analyst
•  Big Data Architect
•  Software Engineer
•  Senior Software Engineer
•  Data Engineer
•  Data Scientist