Big-Data Tutorial
'Big-data' is similar to 'Small-data' but bigger. ? Recently getting popular expression “Midsize data”. ? …but having data bigger it requires somewhat.
Big-Data Tutorial
? Good news about big-data: ? Often because of vast amount of data
Data Science Tutorial
10 de ago. de 2017 2017 SEI Data Science in Cybersecurity Symposium. Approved for Public Release; Distribution is Unlimited. Data Science Tutorial.
Preview Big Data Analytics Tutorial (PDF Version)
sources to a data product useful for organizations forms the core of Big Data Analytics. In this tutorial we will discuss the most fundamental concepts and
Data Science do zero: Primeiras regras com o Python
Translated from original Data Science from Scratch by Joel Grus. Mas não é um tutorial compreensível sobre Python é direcionado a ... O pdf para y.
introduction to big data and hadoop
volumes of data Facebook was generating. Makes it possible for analysts with strong SQL skills to run queries. Used by many organizations.
Informatica Big Data Management - 10.2.2 - User Guide - (English)
10 de jul. de 2020 Informatica the Informatica logo
Big Data Conceitos básicos
Volume de dados de difícil tratamento. Page 5. SEFAZ/ES – do BI ao Big Data Analytics. • Início de
UNIVERSIDADE ESTADUAL DE CAMPINAS FACULDADE DE
O curso “Data Mining e Big Data: inteligência analítica na pesquisa FEQ-0267 – “A História da Big Data: Tutorial sobre Big Data /.
Big Data Analytics: Optimization and Randomization
10 de ago. de 2015 http://www.cs.uiowa.edu/˜tyng/kdd15-tutorial.pdf. Yang Lin
Marko Grobelnik
Marko.Grobelnik@ijs.si
Jozef Stefan Institute, Slovenia
Brdo, Nov 10th2015
Big Data Tutorial: http://www.slideshare.net/markogrobelnik/big-datatutorial-grobelnikfortunamladenicsydneyiswc2013
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`Volume² challenging to load and process (how to index, retrieve) `Variety²different data types and degree of structure (how to query semi- structured data) `Velocity²real-time processing influenced by rate of data arrival )URP ´8QGHUVPMQGLQJ %LJ GMPMµ N\ H%0 `1. Volume ORPV RI GMPM ´Tonnabytesµ `2. Variety(complexity, curse of dimensionality) `3. Velocity(rate of data and information flow) `4. Veracity(verifying inference-based models from comprehensive data collections) `5. Venue (location) `6. Vocabulary (semantics) `7B 8B EB " 9" 9" 9" FRPSMULQJ YROXPH RI ´NLJ GMPMµ MQG ´GMPM PLQLQJµ TXHULHV "MGGLQJ ´RHN 2B0µ PR ´NLJ GMPMµ MQG ´GMPM PLQLQJµ TXHULHV YROXPHBig-Data
Big-Data
Big-DataData-Science
Source: WikiBonUHSRUP RQ ´Big Data Vendor Revenue and Market Forecast 2012-2017µ 2013 `Where processing is hosted?ŃDistributed Servers / Cloud (e.g. Amazon EC2)
`Where data is stored?ŃDistributed Storage (e.g. Amazon S3)
`What is the programming model?ŃDistributed Processing (e.g. MapReduce)
`How data is stored & indexed?ŃHigh-performance schema-free databases (e.g.
MongoDB)
`What operations are performed on data? ŃAnalytic / Semantic Processing / Visualization `An excellent overview of the ´%LJ GMPMµ algorithms is the book ´Leskovec, Rajaraman,Ullman: Mining of Massive Datasetsµ
ŃDownloadable from: http://www.mmds.org/
ŃAssociated MOOC (from Oct 2014):
https://www.coursera.org/course/mmds `Big-Data is everywhere, we are just not used to deal with it `7OH ´%LJ-GMPMµ O\SH LV YHU\ UHŃHQPŃ"JURRPO VHHPV PR NH JRLQJ XS
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