Formation Platforma analityczna KNIME - szkolenie kompleksowe

Code formation

knimecompr

Durée

35 heures (généralement 5 jours pauses comprises)

Pré requis

Analytical thinking approach.

Basics of statistics and mathematical analysis.

Aperçu

KNIME is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface and use of JDBC allows assembly of nodes blending different data sources, including preprocessing (ETL: Extraction, Transformation, Loading), for modeling, data analysis and visualization without, or with only minimal, programming. To some extent as advanced analytics tool KNIME can be considered as a SAS alternative.

Since 2006, KNIME has been used in pharmaceutical research, it also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.

Certification

KNIME

KNIME

NobleProg and KNIME design, build and deliver end-to-end advanced analytics solutions that are customized to each customer's business needs.

By combining KNIME's leading open solution for data driven innovation with NobleProg's domain and technical expertise in analytics, we help our customers reduce costs and gain data-driven insights for better business outcomes.

Plan du cours

  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

Nos Clients témoignent

★★★★★
★★★★★

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