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Data engineering
Data engineer
Best practices Education ELT Spark Big data Orchestration Workflow dependencies Workflow service
  1. Go to item
    Workflow
    00.1_Extensions_setup
    Education Data engineering Data engineer
    +1
    Open this workflow and install suggested extensions. Restart KNIME Analytics Platform. After the extensions are installed, you ca…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > 00.1_Extensions_setup
    0
    chemgirl36
  2. Go to item
    Workflow
    00.2_Setup_PostgreSQL_Database
    Education Data engineering Data engineer
    +1
    This workflow writes tables "customers", "contracts", "statistics" to PostgreSQL database. These tables in the database will be u…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > 00.2_Setup_PostgreSQL_Database
    0
    chemgirl36
  3. Go to item
    Workflow
    URL File Testflow
    Education Data engineering Data engineer
    +3
    A company validates that the file containing the URL for the US Customers data Web service is correct. The file is available in t…
    lada > Public > Testing Framework > testflows > report > 02_URL_File_Testflow
    0
    lada
  4. Go to item
    Workflow
    02.1_Data_Anonymization_solution
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > solutions > Session_2_ETL_Processing_II > 02.1_Data_Anonymization
    0
    chemgirl36
  5. Go to item
    Workflow
    04.2_ELT_Usage
    Education Data engineering Data engineer
    +3
    The company tracks the usage of the website and stores the information about each session. - Various data are collected, e.g., se…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > exercises > Session_4_Orchestration > 04.2_ELT_Usage
    0
    chemgirl36
  6. Go to item
    Workflow
    03.2_Missing_value_imputation_on_Spark_exercise
    Education Data engineering Data engineer
    +3
    The company tracks the usage of the website and stores the information about each session. - Various data are collected, e.g., se…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.2_Missing_value_imputation_on_Spark
    0
    chemgirl36
  7. Go to item
    Workflow
    03.1_In-database&Spark_processing_solution
    Education Data engineering Data engineer
    +3
    The company tracks the usage of the website and stores the information about each session. - Various data are collected, e.g., se…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > solutions > Session_3_ELT_on_Big_Data > 03.1_In-database&Spark_processing
    0
    chemgirl36
  8. Go to item
    Workflow
    01.1_Extract_WebService_data_solution
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > solutions > Session_1_ETL_Processing_I > 01.1_Extract_WebService_data
    0
    chemgirl36
  9. Go to item
    Workflow
    03.0_Setup_Local_Big_Data_Environment
    Education Data engineering Data engineer
    +3
    This workflow sets up a local big data environment for the next exercise. It creates a local big data environment and loads the u…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > solutions > Session_3_ELT_on_Big_Data > 03.0_Setup_Local_Big_Data_Environment
    0
    chemgirl36
  10. Go to item
    Workflow
    03.4_Writing_from_Spark_exercise
    Education Data engineering Data engineer
    +3
    The company tracks the usage of the website and stores the information about each session. - Various data are collected, e.g., se…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.4_Writing_from_Spark
    0
    chemgirl36
  11. Go to item
    Workflow
    Best Practices for ETL on Customer Data
    Best practices Data engineer Data engineering
    +4
    This workflow demonstrates how to apply best practices to a simple ETL (Extract, Transform, Load) process on customer data. The c…
    lada > Public > Examples > Best_Practices_for_ETL_on_Customer_Data
    0
    lada
  12. Go to item
    Workflow
    03.1_In-database&Spark_processing_exercise
    Education Data engineering Data engineer
    +3
    The company tracks the usage of the website and stores the information about each session. - Various data are collected, e.g., se…
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.1_In-database&Spark_processing
    0
    chemgirl36
  13. Go to item
    Workflow
    01.2_Extract_S3_data&Blend_solution
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > solutions > Session_1_ETL_Processing_I > 01.2_Extract_S3_data&Blend
    0
    chemgirl36
  14. Go to item
    Workflow
    01.2_Extract_S3_data&Blend_exercise
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > exercises > Session_1_ETL_Processing_I > 01.2_Extract_S3_data&Blend
    0
    chemgirl36
  15. Go to item
    Workflow
    04.1_ETL_Customers_solution
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > solutions > Session_4_Orchestration > 04.1_ETL_Customers
    0
    chemgirl36
  16. Go to item
    Workflow
    03.4_Writing_from_Spark_exercise
    Education Data engineering Data engineer
    +3
    The company tracks the usage of the website and stores the information about each session. - Various data are collected, e.g., se…
    hayasaka > KNIME Fall Summit Training 2022 > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.4_Writing_from_Spark
    0
    hayasaka
  17. Go to item
    Workflow
    01.1_Extract_WebService_data_exercise
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    chemgirl36 > Public Space > L4-DE Best Practices for Data Engineering > exercises > Session_1_ETL_Processing_I > 01.1_Extract_WebService_data
    0
    chemgirl36
  18. Go to item
    Workflow
    04.1_ETL_Customers_solution
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    hayasaka > KNIME Fall Summit Training 2022 > L4-DE Best Practices for Data Engineering > solutions > Session_4_Orchestration > 04.1_ETL_Customers
    0
    hayasaka
  19. Go to item
    Workflow
    02.1_Data_Anonymization_solution
    Best practices Data engineer Data engineering
    +1
    The company has two branches: one in the United States and another one in Europe. New US customer data comes from a web service. …
    hayasaka > KNIME Fall Summit Training 2022 > L4-DE Best Practices for Data Engineering > solutions > Session_2_ETL_Processing_II > 02.1_Data_Anonymization
    0
    hayasaka
  20. Go to item
    Workflow
    04.3 Orchestration_solution
    Best practices Data engineer Data engineering
    +4
    Once the workflow the ETL on Customers data is executed successfully, i.e., customer data are accessed and anonymized, and the da…
    hayasaka > KNIME Fall Summit Training 2022 > L4-DE Best Practices for Data Engineering > solutions > Session_4_Orchestration > 04.3_Orchestration
    0
    hayasaka

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