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Title:BIG DATA TEHNOLOGIJE ZA ANALIZO VELIKE KOLIČINE POSLOVNIH PODATKOV
Authors:ID Medved, Jana (Author)
ID Bobek, Samo (Mentor) More about this mentor... New window
Files:.pdf MAG_Medved_Jana_2014.pdf (1,50 MB)
MD5: F7F9013ED36B880D5D92C48ED409B9F0
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:EPF - Faculty of Business and Economics
Abstract:S tem, ko naš svet postaja vedno bolj povezan in naše aktivnosti vse bolj digitalizirane, postajajo podatki bogatejši, raznoliki in na voljo kadarkoli. Organizacije izkoriščajo te ogromne količine podatkov za natančnejše prilagoditve sistemov, podporo odločanju in razvoj proizvodov in storitev. V magistrskem delu smo predstavili karakteristike Big Data, njegove prednosti in izzive s katerimi se soočajo organizacije pri analiziranju ogromnih količin podatkov, osredotočili pa smo se na tehnologije Big Data analitike in v povezavi s tem na vizualizacijo Big Data - kot primer je predstavljena rešitev SAS Visual Analytics. Organizacije uporabljajo Big Data tehnologije, da dobijo odgovore na pomembna vprašanja z analizo podatkov takoj, torej v realnem času ter ne rabijo čakati na rezultate dneve, tedne ali celo mesece. Največja prednost Big Data tehnologij je tako pospešitev časa prejema rezultatov analize ter posledično hitrejše sprejemanje odločitev. Kot tehnologije Big Data analitike smo predstavili delovanje Hadoopa ter značilnosti NoSQL podatkovnih baz in masivnih paralelnih analitičnih podatkovnih baz. Prav tako smo predstavili visoko zmogljivo analitiko, ki s hitrostjo spreminja način obdelave in izkoriščanje vrednosti Big Data v organizacijah ter v povezavi z njo analitiko v pomnilniku (angl. in-memory analytics), ki omogoča organizacijam hitrejše odločanje, natančnejše rezultate in vzpostavitev zanesljive ter prilagodljive analitične infrastrukture. Z Big Data se povečuje tudi potreba po bolj napredni podatkovni vizualizaciji. Predstavitev informacij na razumljiv način, je glavni izziv analiziranja podatkov, če želimo, da rezultati privedejo do konkretnih ukrepov. Rezultati analiz in vizualizacija podatkov sta učinkovita kombinacija za predstavitev in deljenje informacij v podjetju. Rešitev, ki podpira vizualizacijo podatkov, izbranih za analizo, je lahko zelo koristna, sploh kadar lahko pomaga uporabniku izbrati najprimernejšo vizualizacijo za določen nabor podatkov. Takšna rešitev je SAS Visual Analytics, zmogljivo orodje raziskovanja podatkov za razkritje trendov in skritih priložnosti. Združuje analitiko, in-memory arhitekturo, raziskovanje podatkov, podporo Hadoopa in različne možnosti uporabe informacij.
Keywords:Big Data, vizualizacija, poslovna analitika, visoko zmogljiva analitika, SAS Visual Analytics
Place of publishing:Maribor
Publisher:[J. Medved]
Year of publishing:2014
PID:20.500.12556/DKUM-45019 New window
UDC:004
COBISS.SI-ID:11807004 New window
NUK URN:URN:SI:UM:DK:ILCGGHBO
Publication date in DKUM:13.10.2014
Views:4042
Downloads:682
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:EPF
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Secondary language

Language:English
Title:BIG DATA TECHNOLOGIES FOR ANALYSING MASSIVE VOLUMES OF BUSINESS DATA
Abstract:With our world becoming more interconnected and our activities more digital, data is more abundant, diverse, and available in real time. Organizations are taking advantage of these massive amounts of data for more precise adjustments of business systems, decision support and development of products and services. In this master’s thesis, we introduced characteristic of Big Data and opportunities and challenges that companies are facing with when analyzing Big Data. Our focus was on technologies of Big Data analytics and Big Data visualization – as an example, we represented solution SAS Visual Analytics. Organizations are using Big Data technologies to get answers on important questions with data analysis in real-time, and don’t have to wait for results days, weeks or even months. The most important benefit of Big Data technologies is accelerating the time-to-answer period and consequently faster decision-making. As Big Data technologies we presented how Hadoop works, characteristics of NoSQL and massively parallel analytical databases, high performance analytics and in connection with it in-memory analytics. High performance analytics is with its speed changing the way of processing and delivering value from Big Data. In-memory analytics enables faster decision-making, accurately results and establishment of reliable and scalable analytics infrastructure. With Big Data, there is also bigger need for more advanced data visualization. Understandably presenting information is key challenge of data visualization, if we want that analyzing data leads to concrete action. Results of an analysis and visualization of data can be a powerful combination for presenting and sharing of information in organization. A solution that supports visualization of the data selected for analysis can be very helpful, especially when it helps the user pick the best visualization for specific set of data. Solution with those characteristics is SAS Visual Analytics, powerful tool for exploring data to uncover trends and hidden opportunities. It combines analytics, in-memory architecture, data exploration, Hadoop support and different possibilities of using information, including on iPad.
Keywords:Big Data, Visualization, Business Analytics, High Performance Analytics, SAS Visual Analytics


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