Analiza primerov uporabe velike količine podatkov

delo diplomskega seminarja

Marko Koželj (Author), Simona Sternad (Mentor)

Abstract

Diplomski seminar predstavlja računalništvo v oblaku in velike količine podatkov. Ta dva pojma sta novi poslovni priložnosti za podjetja. Vsekakor bodo brez teh dveh inovacij podjetja težko preživela na mednarodnih trgih. V diplomskem seminarju smo obravnavali računalništvo v oblaku. Na kratko smo povedali osnovne značilnosti, razvoj skozi leta, arhitekturo, tipe in SWOT analizo računalništva v oblaku. Kasneje smo se osredotočili na velike količine podatkov, jih definirali, pojasnili zgodovinski razvoj in ugotavljali ali smo pripravljeni na njih. Razložili smo tudi karakteristike, arhitekturo in ugotavljali praktičnost in uporabnost, ter njihovo varnost. Preučili smo podjetja Google, IBM in Microsoft in ugotovili kakšne rešitve imajo za velike količine podatkov in na kakšni platformi delujejo. Na koncu pa smo še ugotavljali razlike med samo arhitekturo teh rešitev. V glavnem je bila primerjava med rešitvama Dremel in Hadoop. Razložili pa smo tudi zakaj velike količine podatkov pomagajo tem podjetjem.

Keywords

računalništvo;računalništvo v oblaku;podatki;SWOT analiza;arhitektura;zgodovinski razvoj;

Data

Language:	Slovenian
Year of publishing:	2013
Typology:	2.11 - Undergraduate Thesis
Organization:	UM EPF - Faculty of Economics and Business
Publisher:	[M. Koželj]
UDC:	004.2
COBISS:	11525660
Views:	1373
Downloads:	111
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Case analysis of big data
Secondary abstract:	The thesis presents cloud computing and big data. Those two concepts are new business opportunities for companies. In any case without those two innovations, companies will hardly survive in the international market. In thesis we dealt with cloud computing. We have represented basics, development through the years, arhitecture, types and swot analysis of cloud computing. Later, we focused on how big data is defined, developed and if we are ready for it. We explained their characteristics, arhitecture and observed practicality and usability, as well as their safety. We have studied the companies Google, IBM and Microsoft and we figured out what solutions they have for big data and on what plaftorms they run. On the end we observed the differences in arhitecture of those solutions. In general the comparison was between Dremel and Hadoop. We also explained why big data helps to those companies.
Secondary keywords:	Cloud computing;big data;Dremel;BigQuery;Hadoop;MapReduce;HDInsight;IBM Big Data Platform;
URN:	URN:SI:UM:
Type (COBISS):	Final seminar paper
Thesis comment:	Univ. v Mariboru, Ekonomsko-poslovna fak.
Pages:	50 str.
ID:	8727168