The Importance Of Hadoop Within The Context Of The Assignment

The paper is divided into three sections, the first of which will establish a timeline of events. This project background will serve as a case study for the analysis in the following section that will be structured such that each of the previously mentioned facets will be independently analyzed and contrasted with project management principles. Finally the paper will conclude with a summary of the analysis and recommendations based on

In the current business environment, the demand for project managers is ever growing. In short, project management is a provisional project constrained by time, cost and scope (A guide to the project management body of knowledge, 2013). Between the immense organization, optimization, and communication assets skilled project management brings to a project, it is easy to see why project management is a booming field of study. Furthermore, project management can be both financially and personally rewarding when long term milestones and goals come to fruition.

In this paper the word ‘project” is defined, discussed and elaborated on. The phases of a project lifecycle and its purpose are to be discussed, and how it is important for organizations to use project management to accomplish tasks will in conclusion be discussed thoroughly. The indisputable word ‘Project” may be defined in numerous unusual ways, some can all have the same meaning and others can mislead a reader. The definition that accurately explains what a project is, comes from the Houghton Mifflin Company (2009) website stating; “something that is contemplated, devised, or planned; plan; scheme.” A definition that can mislead a reader is this definition from the same website just two paragraphs

Larson, E.W. and Gray, C.F. (2012, p. 214). Project Management: The Managerial Process, 5th Ed. McGraw-Hill Learning Solutions. Boston, MA.

Hadoop is one of the open source frameworks, is used as extension to big data analytics framework which are used by a large group of vendors. This type of framework makes work easy for the companies how they?re going to store and can use the data within the digital products as well as physical products (James, M. et al. 2011). We can analyze data using Hadoop, which is emerging as solution to

Project management is fundamentally part of every facet of life rather we have the education to realize that we are implementing it in our world or not. For everyone to understand the fundamental project team concepts and principals to have a solid understanding, it will be explained here. We will describe the five parts of the project life cycle, describe the three most important criteria for team success, describe the fundamentals of team structure, and finally list and describe the stages of a team’s life cycle.

Every organization has many projects, and you rely heavily on technology to solve your business needs. You have probably heard to focus on a project that gives you the big bang for your buck. For Hadoop, Identify identify a small project with an immediate need for Hadoop. Too many times I have witnessed projects fail in companies due to the level of complexity, lack of resources, and high expenses. By sSelecting a small project to get started which allows the IT and business staffs to become familiar with the interworking of this emerging technology. The beauty of Hadoop is that it allows you to start small and add nodes as you go.

Big Data is creating great opportunities for businesses, companies and many large scale and small scale industries. Hadoop, as an open-source cloud computing and big data framework, is increasingly used in the IT world. The rapid growth of Hadoop and Cloud Computing clearly indicates its importance as a Big Data enabling technology. Due to the loopholes of security mechanism, the security issues introduced through adaptation of this technology are also increasing. Hadoop services do not authenticate users or other services. As a result, Hadoop is subject to security risks. Big Data is already a prime target for vulnerable attacks due to the valuable information it holds. In this paper,

Hadoop is an open-source framework which is used for processing and analyzing big data. It consists of a Hadoop Distributed File system and MapReduce. (‘Data Lake’, 2015)

Abstract - Hadoop Distributed File System, a Java based file system provides reliable and scalable storage for data. It is the key component to understand how a Hadoop cluster can be scaled over hundreds or thousands of nodes. The large amounts of data in Hadoop cluster is broken down to smaller blocks and distributed across small inexpensive servers using HDFS. Now, MapReduce functions are executed on these smaller blocks of data thus providing the scalability needed for big data processing. In this paper I will discuss in detail on Hadoop, the architecture of HDFS, how it functions and the advantages.

Abstract—Hadoop framework is a solution for big data problem. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. Big data is only not about storing the data, it is also about execution and analyzing of data.

With the rise of Hadoop in the workplace, along with it comes a rise of vendors offering various platforms to store, access, and analyze vast amounts of data. These platforms vary in their functionality, cost, and ease of use, among other factors. Three of the more popular vendors are Amazon Web Services, Map-R, and Cloudera. While each of these is based on Apache Hadoop’s open source offerings, it is the applications and reach that differentiates them. Although price will always be a factor as well, this comparison seeks only to explore the vendors themselves, not the price of admission.

The Basic idea in Hadoop is all about parallelization. Parallelization can be easily accomplished, if a processing (a work) can be easily split into n units. Hence the core focus of MapReduce programming framework have been to solve the partition problem.

Hortonworks is a business computer software company based in Palo Alto, California. The company focuses on the development and support of Apache Hadoop, a framework that allows for the distributed processing of large data sets across clusters of computers. Architected, developed, and built completely in the open, Hortonworks Data Platform (HDP) provides Hadoop designed to meet the needs of enterprise data processing.HDP is a platform for multi-workload data processing across an array of processing methods from batch through interactive to real-time - all supported with solutions for governance, integration, security and operations.

This chapter introduces an industrial and technical review for Hadoop framework with other technologies used with Hadoop system to process bigdata. Hadoop project originally was built and supervised by Apache community. In addition to Apache many other companies whose businesses run on Hadoop are adding more interesting features to Hadoop, some of them announced their own Hadoop distributions replying on the original core distribution distributed by Apache.