With the ever-growing and increase of producing large volumes of data every year i.e big data Hadoop framework was introduced. As big data is a combination of large volumes of datasets, it cannot be processed using the traditional computational methods. It requires huge computational power, ever-growing techniques, algorithms and frameworks to process the large volume of datasets.

In order to process such data using complex frameworks and algorithms, the Hadoop framework was introduced. It measures and processes the output with very much accuracy.

What is Hadoop big data analytics?

Big data Hadoop is an open source framework that stores and process the big data in distributed systems across different clusters of computers by using single computational or programming model. By using the Hadoop technology, one can process the data using a single server with thousands of machines by performing local storage and computation.

The Hadoop technology requires the MapReduce algorithm, big data and Hadoop Distributed File system. In order to become a Hadoop developer, you need to know the core Java concepts, database concepts and any of the Linux operating systems.

What is Big Data with respect to Hadoop technology?

Big data is nothing but a collection of large datasets which can be processed using the computational tools, frameworks and techniques. So here we use the Hadoop framework to analyze the big data results. In general, it is the data produced by the applications or devices which needs to be processed effectively by connecting all the distributed clusters around the server.

Below are the notable fields where big data falls:

Clients that fall under big data:

  • Social Media Data: The social networks such as Facebook and Twitter holds the information and you can see it is viewed and accessed all over the world. It is a distributed file system with one server and different clusters components running in various places. The results for each and every component s are added together to generate the accurate result.
  • Stock Exchange BIg data: The stock exchange holds the information of buy and sells shares of different companies. Anyone can access them anywhere and do the trade as the result all are combined, data is analysed and process from the server end.
  • Power Grid Big Data: The power stations holds the information of power consumed by the particular node in the base station and all the nodes belonging to that station will be notified to generate unique results so that one can estimate the power consumed with respect to the power station.
  • Transport Data: It contains information on the distance, availability of the vehicle in that particular junction etc.
  • Search Engine Data: Hadoop technology also uses in search engine data analytics so as to retrieve or get data from the databases.

The big data as the huge volume of velocity and varieties of data. It is classified into 3 types.

Big data can be of the following type.

  • Structured data which is nothing but the relational database. Here all are linked and connected one after the other as our relationships.
  • Semi-Structured data: XML data can be stated as semi-structured data because here is the data is organized in the form of specific elements.
  • Unstructured Data: Word documents, text files, PDF and media files comes under it.

To be more specific and usable it had help many industries to get the data and take immediate response.

The advent of big data Hadoop in our real life brings many fruitful and meaningful challenges to face the world with more curiosity. With the data kept in the social networks, the marketing agencies benefit a lot because they can easily promote their brand or product as to reach it the outer world. It also helps in healthcare as it can give better treatment services based on the previous records. It helps in the electric department to collect the data regarding the amount of power consumed and to check whether there is any need to produce more electricity.

In each and every discipline big data Hadoop helps to generate accurate results with the best output. It helps in the IT industry when there is a need to process the bulk amount of information from different resources. It produces unique results and also makes your work easier too.

With the big data Hadoop, one can take efficient decision making, cost reductions and also helps in reduced risks in businesses. The big data requires the frameworks and infrastructure to protect the privacy and security in order to manage and process the large volumes of data at the instance.

Different vendors use different technologies to handle the big data. Big data opt the operational and analytical big data technologies. In operational big data, MongoDB and NoSQL systems are designed to compute the operational capabilities in real time with interactive workloads where data is captured and stored. The big data analytics includes the Massive Parallel Processing(MPP) and MapReduce database systems to provide the complex analysis of the data.

big data analytics

The traditional approach of storing and processing of big data is useful when the processes data is limited. When the processed data is huge volume this method does not works well. In such advent situation, Google provided an solved this problem using the MapReduce algorithm. This algorithm divides the task into several parts connected across the network and results are collected to the final dataset i.e central server as shown in the above image

 

Conclusion:

The big data technology helps any fields to create the best output by reducing cost, computational power and also eliminates the risk for the businesses. By using proper techniques, frameworks and models one can definitely drive a good approach for their business success.