Data Migraton Services
Planning a migration soon?
Extraction With AMSA Connect
In order to achieve big data goals, data extraction becomes the most important step as everything else is going to be derived from the data that is retrieved from the source. AMSA Connect can easily extract data that is stored in a structured format such as a relational database management system (RDBMS). If data extraction is not done properly, the data will be flawed. After all, only high-quality data leads to high quality insights. AMSA Connect can do all the assessment, mapping, planning, and deployment to get your data extracted smartly for Data Warehouse ETL. It is very effective in migrating data from any structured/semistructured sources onto a Cloud DW or Data Lake.
What to Keep in Mind When Preparing for Data Extraction During Data ETL:
Impact On the source
Retrieving information from the source may impact the source system/database. The system may slow down and frustrate other users accessing it at the time. This should be thought of when planning for data extraction. The performance of the source system shouldn’t be compromised. You should opt for a data extraction approach that has minimal impact on the source.
Volume
Data extraction involves ingesting large volumes of data which the process should be able to handle efficiently. Analyze the source volume and plan accordingly. Data extraction of large volumes calls for a multi-threaded approach and might also need virtual grouping/partitioning of data into smaller chunks or slices for faster data ingestion
Data Completeness
For continually changing data sources, the extraction approach should cater to capture the changes in data effectively, be it directly from the source or via logs, API, date stamps, triggers etc.
Let AMSA Connect Do the Heavy Lifting
AMSA Connect can do all the thinking, planning, and deployment to get your data extracted smartly for Data Warehouse ETL. It checks all the boxes above and is very effective in migrating data from any structured/semi-structured sources onto a Cloud DW or Data Lake