Platforma analityczna KNIME - szkolenie kompleksowe Treningskurs

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Kurskode

knimecompr

Varighet

35 timer (vanligvis 5 dag inkludert pauser)

Krav

Analytical thinking approach.

Basics of statistics and mathematical analysis.

Oversikt

Det er Konstanz Information Miner, et plattform utviklet for integrering, interaktiv analyse og rapportering av data, tilgjengelig på grunnlag av fri og åpen programvare. KNIME gjør det mulig å integrere en rekke ródiverse komponenterói fra feltet maskin læring (eng. maskin læring) og dataforskning (eng. Data mining) takket være modulære konsepter for strømforsyning data. Grafisk brukergrensesnitt og bruk JDBC  gjør det mulig å enkelt og raskt montere noderów (eng. nodes) for å koble sammen rógenne kilderódeler av data med hensyn til forhåndsbehandlingsprosessen - ETL  og modellering, analyse og visualisering av data uten behov for å bruke programmering (eller i minimal grad). KNIME I en viss grad, som et avansert analytisk verktøy, kan betraktes som et alternativ SAS.

Siden 2006 har KNIME blitt brukt i farmasøytisk forskning, så vel som i andre områder som kundeinformasjonsanalyse (CRM), business intelligence (BI) og finansiell dataanalyse.

Machine Translated

Kursplan

  1. Introduction to data processing and data analysis
  2. Fundamental information of KNIME platform
  • Installation and configuration
  • Overview of the interface
  1. Discussion of tool integration
  2. Building workflows
  3. Methodology of creating business models and data modeling
  • Documentation
  • import and export workflows
  1. Basic nodes
  2. Design ETL processes
  3. Data mining
  4. Data Import 
  • from files
  • from relational databases using SQL
  • creating SQL queries
  1. Advanced nodes
  2. Data analysis:
  • data preparation
  • data check-up
  • statistical data examination
  • data modeling
  1. Introduction to Flow Variables and Loops
  2. Advanced process automation
  3. Visualization Features
  4. Open source data sources
  5. Data mining basics
  • selected types of Data Mining tasks and processes
  1. Getting more knowlegde from data
  • Web Mining
  • SNA
  • Text Mining
  • Data visualization on graphs
  1. Install Extensions and Integrations
  • R
  • Java
  • Python
  • Gephi
  • Neo4j
  1. Reporting
  • Overview
  • BIRT Integration
  • KNIME WebPortal
  1. Conclusion and Q&A session

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