Travaux pratiques (TP) - Intelligence artificielle et données
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Travaux pratiques (TP) de intelligence artificielle et données partagés par des étudiants et des enseignants. Thèmes couverts : machine learning, apprentissage automatique, big data, data science, fouille de données.
This document details the methodology for implementing an ETL solution using SQL Server Integration Services (SSIS). It describes how to extract customer and sales order data from the InternetSales database, transform it via calculations and transformations, and load it into a staging environment. Profiling source data, analyzing its structure, and ensuring transformations are tailored to the operational needs are outlined. The process includes using SSIS tools, debugging strategies, and testing the data flow to confirm successful data migration.
This document provides a step-by-step guide to developing an Extract, Transform, Load (ETL) solution using SQL Server Integration Services (SSIS). It involves extracting customer and sales order data from a source database, performing data profiling, applying transformations, and loading it into a staging database. Key exercises include configuring data flow tasks, creating connections, performing data mappings, and using industry-standard best practices for data profiling and validation. The lab concludes with successfully transferring and profiling data to ensure data quality and complete...
This lab focuses on creating an ETL (Extract, Transform, Load) solution using SQL Server Integration Services (SSIS). The procedure involves extracting sales order data and customer data from the InternetSales database, transforming the data with calculated fields and transformations, and loading it into a staging database for pre-processing. Tasks include profiling source data for statistics, implementing connections and flows in SSIS, mapping input and output fields across data flows, and validating the workflow through debugging and profiling operations. Outputs include CSV files, data p...
The document describes a practical case study centered on designing and implementing a data warehouse for a fictitious global sports goods company, Orion. It covers the company’s organizational, product, and customer informational landscape and establishes questions that the Business Intelligence system aims to answer, focusing on performance metrics and decision support. The solution involves leveraging an operational database and preparing a star schema warehouse with dimensions and fact tables, which will be populated using ETL processes created within Talend Open Studio. Practical instr...
This document provides an introductory tutorial on importing and reading tabular data formats (CSV, Excel) in R, detailing commands like `download.file`, `read.csv`, and the use of the external `readxl` library for Excel files. It explains how to access rows, columns, and subsets of data using dataframes, demonstrates built-in datasets in R, and explores additional capabilities like inspecting structure (`str`) and accessing complex calculations for data manipulation. Methods for installing and utilizing libraries are also covered comprehensively.