Data Warehouse Lab Work 10
Final Project Practicum II
In 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.
Module
Dataset
All articles on this blog are licensed under CC BY-NC-SA 4.0 unless otherwise stated.
Related Articles
2022-03-21
Data Warehouse Lab Work 1
Message Box & Data Transformation in SpoonData warehouse is a type of data management system designed to enable and support business intelligence (BI) activities, especially analytics. A data warehouse is solely intended for querying and analysis and often contains a large amount of historical data. Data in the data warehouse typically comes from various sources such as application log files and transactional applications. The data warehouse centralizes and consolidates a large amount of...
2022-03-28
Data Warehouse Lab Work 2
Data InputData input is an action of entering data into a system, where the data can then be stored, manipulated, or processed. Inputting data in Spoon can be done in various formats, and the tools provided in Spoon are quite comprehensive and diverse. Among the data storage formats that can be input are: SQL CSV TXT XML JSON Microsoft Excel Input can be done in an unlimited manner with the data storage formats mentioned above. Besides these formats, there are many other ways, but the most...
2022-04-04
Data Warehouse Lab Work 3
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...
2022-04-11
Data Warehouse Lab Work 4
Structured TransformationStructured transformation is the systematic and structured conversion of the original data measurement scale into another form, making it easier to analyze variability in the data. The expected output is also in the form of cleaner and more structured data. In today’s practical session, we will perform a simple data transformation by combining header data with content data separately and changing the data format from CSV to Microsoft Excel format. You can download...
2022-04-18
Data Warehouse Lab Work 5
Connected to MySQLMySQL is a multi-threaded, multi-user SQL database management system (DBMS) software with around 6 million installations worldwide. Pentaho Spoon itself supports importing and exporting data through DBMS, and one of the supported DBMS is MySQL. In this lab, you are required to connect MySQL with Pentaho Spoon. Below are the datasets stored in SQL format, and you can also download the work module. ModuleDownload Module 5 DatasetDownload Dataset
2022-05-19
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
Comments
