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Data Warehouse Lab Work 7

Created2022-05-23|Updated2022-05-23|Lab Work
|Word Count:21|Reading Time:1mins|Post Views:

Preparation for Final Project I

Exercises before working on the final project for the Data Warehouse course.

Module

Download Module 7

Dataset

Download Dataset

Author: Azhar Rizki Zulma
Link: https://blog.zulma.id/posts/Data-Warehouse-Lab-Work-7/
Copyright Notice: All articles on this blog are licensed under CC BY-NC-SA 4.0 unless otherwise stated.
TrisaktiSubjectData Warehouse
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Data Warehouse Lab Work 6
Merge DataMerge Data or Data Merging is the process of combining two or more sets of data into a single data set. This process is necessary when you want to analyze or process large amounts of raw data that are stored separately in various types of files, worksheets, or data tables. Before analysis, the data needs to be merged to facilitate and expedite the analysis or data processing. ModuleDownload Module 6 DatasetDownload Dataset
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Information Technology Project Management Lab Work 9
Resource GraphResource Graph is a feature in Microsoft Project that functions to visualize the daily resource usage in a bar chart. It can also indicate resource overloads. In addition to viewing resource usage, its other function is to analyze the resources used in project management. Resource Graph is a facility provided to display reports in a graphical form, similar to other worksheets in Microsoft Project.Resource Graph has several display branches, including those provided by Microsoft ...
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Final Project Practicum IIIn this practicum, students are required to perform data cleansing on the given dataset as the first step of the Final Project Practicum. Below is the module along with the dataset. ModuleDownload Module 10 DatasetDownload Dataset
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Output DataOutput Data is the action of storing data from transformation results or data created automatically in Pentaho. In Pentaho Spoon, Output Data can be done in many ways and in any format, but the most commonly used ones are as follows: Database (Directly inputted into the Database) CSV TXT XML JSON Microsoft Excel In this practical, you will learn how to output data in Text and CSV formats because these two formats are the most common for data storage. Database storage will be cove...
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Final Project Practicum IData CleansingData Cleansing is a process of detecting and correcting (or removing) corrupt or inaccurate data sets, tables, and databases. Inaccurate data includes empty data that has no value or contains NULL/NaN values. The goal of data cleansing is to ensure that when the data is processed later, there will be no errors resulting from incomplete or missing data. In this practicum, students are required to perform data cleansing on the given dataset as the first st...
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Final Project Practicum IVIn this practicum, students are required to perform Extract, Transform & Load (ETL) on the provided dataset as part of the final stages of the Practicum Final Project. In the initial process of data analysis, data scientists must follow several basic steps to ensure the accuracy of the output. One of the methods is Extract, Transform, and Load, commonly referred to as ETL. Since its emergence in the 1970s, ETL has drawn the attention of companies for storing thei...
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Contents
  1. 1. Preparation for Final Project I
  2. 2. Module
  3. 3. Dataset
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