Data Program Manager, computer science assignment help

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Computer Science

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Literature Review and Proposal

Project Topic: Data Program Manager

Literature Review is a research paper about your topic. Most Action Research (AR) topics are very specific, you will most likely need to generalize your topics. For example, if your AR project involves collecting business requirements for a new system, you may not find academic research about collecting business requirements for a new system. You will be able to find research about business requirements and process change, 5-7 pages, Title page, Table of contents and reference page not included in 5-7 pages. Need minimum of eight (8) professional references

  • Proposal – this is your plan - review the template, which should provide you with some common ideasregarding how to document your proposal
  • Briefly summarize (a paragraph or two for) each of the proposed (AR) iteration (at least 4 iterations)
  • Include a visual representation – (example provided in template)

* Introduction, Conclusion and Sub Headings are mandatory

* No Plagiarism

* APA Format

* Follow Sample paper

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Running head: Literature Review 1 Sample Literature Review 2 Table of Contents Hadoop ……...…………………………………………………………………………………….3 Benefits of Hadoop …………………………………………………………………….…………3 Cost Effective ……………………………………………………………………………..3 Resilient to failure………………………………………………………………..………..3 Adaptability ………………………………………………………………………...…….4 Scalability………………………………………………………………………...……….4 Hadoop Programmer………………………………………………………………….……..…….4 Map Reduce……………………………………………………………………………….5 Distributed File system of Hadoop………………………………….................................5 Proposal…………………………………………………………………………………………...6 Iteration one………………………………………………………………………….……6 Iteration two…………………………………………………………………………….....7 Iteration Three……………………………………………………………………………..7 Iteration Four……………………………………………………………………………...7 References………………………………………………………………………………….…...…9 Literature Review 3 Hadoop In this today's world each association is stressed over exponential increment of huge information. Starting now everybody is living in the information age where the information is not measured and put away electronically on typical storage gadgets. To conquer this circumstance the new pattern innovation said huge information is presented. This primary point of this enormous information innovation is to assemble the substantial information from the noncomparative source which is hard to oversee by the essential customary system database(Harris, 2013). This innovations are profoundly costly progressively application where medium scales businesses couldn't purchase this advancements for taking care of their expansive information. Hadoop is the most chipset advancements of enormous information that permits building up the bound together storing ability and information preparing nature over different information servers. Hadoop Advantages Cost Effective Hadoop is commonsense in sorting the data in more accommodating way that can deal with the expense of data per terabyte than various innovations (Nemschoff, 2013). On other part Hadoop conveys the registering and storerooms for least cost per terabyte. Resilient to failure Hadoop is tolerant of adaptation to internal failure it is one of the primary favorable position of utilizing Hadoop as a part of constant. This innovation does information replication on a group if single hubs experience the disappointments whiling handling the information on Literature Review 4 large clusters (Nemschoff, 2013). This is one of the proficient advances that empower to recover the information in the event of plate and rack disappointments. Adaptability Adaptability is one of the significant focal points of Hadoop execution. This improves the adaptability to store the information in vast resources and permits the business dares to produce the high esteem (Nemschoff, 2013). Prior to this innovation the information is put away and prepared in typical information bases in customary system. On other part this stores a wide range of information including organized and unstructured and removes a productive business needs and experiences. Scalability As far as scalability, utilizing Hadoop one can store the substantial information in a bunch. This storage stage permits putting away and appropriating the information over the bunch and made to run parallel on various servers (Nemschoff, 2013). The principle point of improving the high adaptability is to over the issues with customary storage process over monstrous volume of information. Hadoop Programmer This innovation offered five employment positions, for example, Hadoop engineer, testing, admin, and Data analyst. The decision of developer of Hadoop is exceptionally testing to build up the front end of the innovation(Harris, 2013). Utilizing this languages software engineer will compose the code for guide decreasing and document disseminating calculations. Literature Review 5 The Project code developers are need to learn quickly Hadoop Architecture which is having Processing layer or calculation layer i.e., Map Reduce. And Storage layer i.e., Hadoop appropriated record framework. Map Reduce To Prepare the Big data by transferring application by Project developer by using developing language is called Map Reduce. This model is a productive and powerful approach that improves the helpful projects that is composed in various programming languages to run Map Reduce programs (Bonanci, 2015). This system puts the substantial information investigation into the machines at client transfer with dependable and adaptation to non-critical failure way. Distributed File system of Hadoop In this circumstance it is critical to parcel information sets crosswise over various physical machines. The document framework which deals with the storing limit of the information over the system machines is called as HDFS (Bonanci, 2015). This procedure is not performed with the normal and conventional plate record frameworks. In this viewpoint large information sets implied for the gigabytes and petabytes of the information both in basic, unauxiliary information. Essentially HDFS is a dispersed record framework that stands for Hadoop that intended for expansive information sets of putting away and getting to information over the product group equipment (Turner, 2011). Literature Review 6 Proposal To have Hadoop coding Position part in an organization one should to have the enough delicate abilities, and specialized aptitudes that identified with Hadoop innovation and other related spaces. At first one should to learn fundamental ideas how Hadoop space functions continuously applications. To be an expert in this innovation one need an awesome practice in composing codes in Java, Hive and Pig to build up the guide lessen and Hadoop dispersed document framework (DeZyre, 2016). To practice this idea progressively there are numerous edge works that present continuously. Subsequent to having the affirmation one ready to set up the potential resume for Hadoop coding position discover bosses and take interviews. This activity is consolidated with 4 iterations that decipher how to be a Hadoop engineer in required associations. Research on Hadoop programming aptitudes and necessities,and Attending the Hadoop code preparing Meeting experts to build the aptitudes in Hadoop coding. Applying and going to meetings of Hadoop engineer positions. Iteration 1: Research on Hadoop programming abilities and necessities In the activity, Iteration one is about leading exploration on Hadoop creating part, abilities and prerequisites. What are the aptitudes required to end up the Hadoop engineer and says the Hadoop programmer duties. It subtle elements how this data is assembled and looked into utilizing essential reports, assets and determined the points of interest that refined this errand effectively. Literature Review 7 Second Iteration: Attending the coding preparation for Hadoop. The second Iteration is about going to the instructional meetings to be a Hadoop designer. This Iteration explains elements the situation of picking the precise mentor for Hadoop creating. How one enhanced the proficiency in taking in the new innovation by utilizing different assets like web, Hadoop creating books, online journals, and articles. In this cycle it specify the essentials and vital abilities to wind up the of Hadoop engineer. Third Iteration: Meeting experts to build the aptitudes in Hadoop creating In this iteration it explains points of interest of experts what experts proposed and what abilities one gained from this gatherings. It is vital to take the assistance of experts to set up the potential resume and increment the delicate aptitudes and Hadoop Developing. Iteration Four: Applying and going to meetings of Hadoop designer positions The Fourth Iteration of Hadoop designer activity examination is applying and going to meet for Hadoop engineer positions. The reflection stage in this cycle troubleshoot the errors that done in this iteration and clears the effective way to future competitors. This stage shows how one finds an appropriate business through expert guidance and goes to the meetings. Literature Review 8 Hadoop Developer’s Action Research Diagram Iteration 1 Research on Hadoop programming abilities and necessities Iteration 2 attending the coding preparation for Hadoop Iteration Three : Meeting experts to build the aptitudes in Hadoop Iteration Four: Applying and going to meetings of Hadoop designer positions Plan Act Observe Reflect Plan Act Observe Reflect Plan Act Observe Reflect Plan Act Observe Reflect Literature Review 9 References Bonanci, M. (2015). The history of Hadoop. Retrieved from: https://medium.com/@markobonaci/the-history-of-hadoop-68984a11704#.5ln6wlewh DeZyre.(2016). 5 Job Roles Available for Hadoopers. Retrieved from: https://www.dezyre.com/article/5-job-roles-available-for-hadoopers/71 Harris, D. (2013). The history of Hadoop: from 4 nodes to the future of data. Retrieved from: https://gigaom.com/2013/03/04/the-history-of-hadoop-from-4-nodes-to-the-future-ofdata/ Nicolas. (2014). What is Hadoop and how does it work?. Retrieved from: http://dataconomy.com/hadoop-what-how-introduction/ Nemschoff, M.(2013). Big data: 5 major advantages of Hadoop. Retrieved from http://www.itproportal.com/2013/12/20/big-data-5-major-advantages-of-hadoop/ Turner, J. (2011). Hadoop: What it is, how it works, and what it can do. Retrieved from: https://www.oreilly.com/ideas/what-is-hadoop
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Attached.

Running head: LITERATURE REVIEW

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Literature Review
Student’s Name
Course Number
Institutional affiliation
Date

LITERATURE REVIEW

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Table of Contents
Data Program Manager ................................................................................................................... 3
Importance of a Data Program Manager ......................................................................................... 3
Cross-functional team experience management ......................................................................... 3
Marketing Skills .......................................................................................................................... 4
Advisory Skills............................................................................................................................ 4
Technology skills plus aptitude .................................................................................................. 5
Challenges affecting Data Program Manager ................................................................................. 5
1.No program order ..................................................................................................................... 5
2.Hazy desires ............................................................................................................................. 5
3.Poor interchanges amongst IT and the business ...................................................................... 5
4.No client input.......................................................................................................................... 6
Proposal........................................................................................................................................... 6
Iteration 1: Budgeting ................................................................................................................. 7
Second Iteration: Scoping ........................................................................................................... 7
Third Iteration: Time-lining ........................................................................................................ 7
Fourth Iteration: Team formulation ............................................................................................ 8
Data Program Manager Action Research Diagram ........................................................................ 8
References ....................................................................................................................................... 9

LITERATURE REVIEW

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Literature Review

Data Program Manager

Introduction and Th...


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