The Role of Hadoop that has revolutionized Big data technology

In the beginning stage of the electronic world the use of the internet is limited, hence the data to be stored are lesser and storage devices are lesser respectively. But the data or information on the internet had rapid growth. Web pages are turned from dozens to millions. Every process in various sectors is made computerized and special devices are made for storage purposes. Customers and organizations urge the App Development Company to use modern big data analysis techniques for better framework and feasibility.

Evolution

Web crawlers and Developers worked hard to create many university-led research projects and search engine startups took off (Yahoo, AltaVista etc). One such project is called Nutch by which they wanted to return web research results faster by distributing data and calculation across many several computers to perform multiple tasks at a time. Then the Nutch project is divided into two web categories as web crawler Nutch remained the same and the processing portion is developed as Hadoop. In 2008, Yahoo planned and released Hadoop as an open-source project.

Hadoop

Hadoop is an open source distributed processing framework helps in managing data processing and to store big data application running in a grouped system. Hadoop is a data management platform for Big data technologies basically used to support advanced analytic initiatives, consist of predictive analytics, data mining and machine learning applications. The preliminary role of Hadoop is to collect process and analyze both structured and unstructured data.

Functions of Hadoop

The basic function is to provide a distributed file system to big data sets. Following this process, the data sets are transformed into useful information using the Map Reduce programming model. The size of the big data is probably about hundreds of gigabytes. This large amount of data provides a distributed file system (HDFS). These data are stored in a cluster of machines and accessed.

The HDFS allows the user to access the data in the entire commodity making the process more reliable and robust. Nodes are high helps in changing task.  If there is a breakdown in one node, Hadoop would detect and change the work on another node. The framework is also highly scalable and easily accessed or configured at any time convenient time of user according to their needs. Setting up the Hadoop software doesn’t need any special change in hardware. Thus the machines need some basic hardware configuration such as RAM, disk space and operating system.

Advanced data analysis could be done from home

With a Hadoop technology, advanced data analysis in large number could be done without the aid of external outsourcing specialist service providers. Installation of Hadoop technology doesn’t need any higher configuration system to ensure user and installation seems to be easy. Outsourcing operational cost is also be avoided since the data analysis is done from home with the aid of the Hadoop framework.

Leveraging the entire data of an Organization

Hadoop are designed in such a way to handle a different variety of data such as structured, unstructured, Real-time and historical. This grabs the attention of much organization to completely rely on Hadoop for storing and analyzing the data in all means. This in turns helps in increasing the return on investment (ROI) of an organization and used to collect, process and store the data including ERP, CRM system, social media program, sensor, industrial automation system etc.

Run a commodity vs custom architecture

The task that is run through Hadoop is formerly done by some MPCC and other specialties, expensive computer system.    Hadoop and its advanced technology only aid in commodity hardware. In fact, on the basis of big data, it is supported by a large and competitive solution provider which protects the customer from vendor lock-in.

The Business case for Hadoop

A business case mainly depends on the value of information. Hadoop helps in deriving more information and analyze large information to support better decision making. It makes information more valuable by analyzing at real time. Hadoop is designed to manage both structured and unstructured data and gives new insights into new data types such as social media streams and sensor inputs. An organization much relies on Hadoop for them better understanding their customers, competitors, supply chain, risk, and opportunities.

Most of the organization thinks that big data and Hadoop are mainly helping in analyzing the data for the historical data that may not suit for the present time condition. Big data analysis not only helps in analysis data but also gives the recommendations and prediction from the past data.

Future of Hadoop

Hadoop is used in different filed for effective and desired outputs. This framework is highly helpful in future of Bioinformatics where the set of computers and pre-programmed algorithms are used to map genome. This highly helps in understanding the life science and advancement of technology for the benefit of mankind.

Studies suggest that by the end of 2019 there would be a deficit of about 3 lakh data scientist. Development in big data is mainly due to the increase in awareness of the advantage that insights taken from the unstructured data could impact business and improve the Return on investment (ROI).

Increase in the requirement for the Job for Hadoop developers in several fields like e-commerce, retail business, and educational institution to obtain an advantage with their competitors.

Organizations are striving hard for embedding of Hadoop in their system for their ease and efficiency. But still, Hadoop adoption is not easier for many organizations facing the complexity of implementation and training. Hadoop has become an emerging technology of big data to invest more heavily for the effective workflow.