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Data engineering
Best practices Data engineer Education ELT Spark
+3
  1. Workflow
    Database Jam Session
    Database Credentials MySQL
    +8
    This workflow jams together data from not one, not two, but six databases! They are: MySQL, MongoDB, MS SQL Server, MariaDB, Orac…
    knime > Examples > 01_Data_Access > 02_Databases > 08_Database_Jam_Session
    3
  2. Workflow
    Interactive Workflow Metadata exploration
    KNIMEServer Web application Workflow summary
    +2
    This workflow shows a simple guided analytics application for exploring the metadata of a workflow. The example uses the Analyze …
    knime > Examples > 09_Enterprise > 03_Metadata_Mapping > Interactive_Workflow_Metadata_Exploration
    2
  3. Workflow
    Try & Catch for Google Books API
    Onboarding Data engineering
    Use this workflow to wrap your GET request to Google Books API into a Try & Catch
    lada > Public > Examples > Try & Catch for Google Books API
    1
  4. 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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > 00.1_Extensions_setup
    0
  5. 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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > 00.2_Setup_PostgreSQL_Database
    0
  6. Workflow
    01.2_Extract_S3_data&Blend
    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. …
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_1_ETL_Processing_I > 01.2_Extract_S3_data&Blend
    0
  7. Workflow
    02.1_Data_Anonymization
    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. …
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_2_ETL_Processing_II > 02.1_Data_Anonymization
    0
  8. Workflow
    02.1_Data_Anonymization
    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. …
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > solutions > Session_2_ETL_Processing_II > 02.1_Data_Anonymization
    0
  9. 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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.0_Setup_Local_Big_Data_Environment
    0
  10. Workflow
    03.1_In-database&Spark_processing
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.1_In-database&Spark_processing
    0
  11. Workflow
    03.1_In-database&Spark_processing
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > solutions > Session_3_ELT_on_Big_Data > 03.1_In-database&Spark_processing
    0
  12. Workflow
    03.2_Missing_value_imputation_on_Spark
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.2_Missing_value_imputation_on_Spark
    0
  13. Workflow
    03.2_Missing_value_imputation_on_Spark
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > solutions > Session_3_ELT_on_Big_Data > 03.2_Missing_value_imputation_on_Spark
    0
  14. Workflow
    03.3_Aggregation_on_Spark
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.3_Aggregation_on_Spark
    0
  15. Workflow
    03.3_Aggregation_on_Spark
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > solutions > Session_3_ELT_on_Big_Data > 03.3_Aggregation_on_Spark
    0
  16. Workflow
    03.4_Writing_from_Spark
    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…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_3_ELT_on_Big_Data > 03.4_Writing_from_Spark
    0
  17. Workflow
    04.0_Reset_DB&Big_Data_Environment
    Education Data engineering Data engineer
    +3
    This workflow resets the database by overwriting the customers and statistics tables and sets up a local big data environment and…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_4_Orchestration > 04.0_Reset_DB&Big_Data_Environment
    0
  18. Workflow
    04.0_Reset_DB&Big_Data_Environment
    Education Data engineering Data engineer
    +3
    This workflow resets the database by overwriting the customers and statistics tables and sets up a local big data environment and…
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > solutions > Session_4_Orchestration > 04.0_Reset_DB&Big_Data_Environment
    0
  19. Workflow
    04.1_ETL_Customers
    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. …
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > exercises > Session_4_Orchestration > 04.1_ETL_Customers
    0
  20. Workflow
    04.1_ETL_Customers
    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. …
    knime > Education > Courses > L4-DE Best Practices for Data Engineering > solutions > Session_4_Orchestration > 04.1_ETL_Customers
    0