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Data Extraction from Oracle to AWS Datalake

Planning and Preparation

Identify the specific data to be extracted from Oracle database

Determine the format and structure of the data in the AWS Datalake

Assess any data transformations or mappings required during the extraction process

Define the frequency and schedule for data extraction

Identify the appropriate tools or technologies for data extraction from Oracle to AWS Datalake

Ensure necessary permissions and access are granted for Oracle and AWS environments

Oracle Database Configuration

Verify that the Oracle database has the required permissions and privileges for data extraction

Ensure that the necessary Oracle database drivers are installed and up to date

Confirm that the Oracle database is accessible and functioning properly

Validate the connectivity between the Oracle database and the AWS Datalake environment

AWS Datalake Configuration

Set up the AWS Datalake environment with the appropriate storage resources and configurations

Create the necessary IAM roles and policies to access the AWS Datalake

Establish connectivity between the Oracle database and AWS Datalake environment

Configure data ingestion or storage services in AWS Datalake to receive the extracted data

Data Extraction

Develop and test the data extraction scripts or queries for Oracle database

Implement any required data transformations or mappings during the extraction process

Execute the data extraction process and monitor for any errors or issues

Validate the extracted data against the expected results or requirements

Establish mechanisms for error logging and handling during the extraction process

Data Transfer and Loading

Determine the most suitable method for transferring the extracted data to AWS Datalake (e.g., AWS Data Pipeline, AWS Glue, custom scripts)

Configure the chosen data transfer mechanism to load the extracted data into AWS Datalake

Monitor the data transfer and loading process for any errors or performance issues

Validate the loaded data in AWS Datalake to ensure its integrity and accuracy

Data Quality and Validation

Implement data quality checks and validation processes on the extracted and loaded data

Create and execute data validation scripts or queries to ensure data consistency and accuracy

Monitor and address any data quality issues or discrepancies in the extracted data

Establish periodic data quality audits to maintain the integrity of the extracted data

Monitoring and Maintenance

Set up monitoring and alerting mechanisms to track the data extraction process and its performance

Establish regular maintenance tasks for data extraction scripts, ETL processes, and related configurations

Monitor and optimize the performance of the data extraction process to ensure efficiency

Keep the documentation and metadata related to the data extraction process up to date

Implement proper security measures and access controls to protect the extracted data

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