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Begin by exporting the data from Flexport. Access the Flexport platform, navigate to the data or reports section, and select the data you wish to export. Use the export function to download the data in a common, compatible format such as CSV or JSON.
Once you have exported the data, review and clean it to ensure it meets the format and quality standards required by Starburst Galaxy. This may involve removing unnecessary columns, correcting data types, and ensuring there are no missing values or inconsistencies.
Set up a direct connection to Starburst Galaxy. This involves accessing your Starburst Galaxy environment and ensuring you have the necessary permissions and credentials to upload data. Familiarize yourself with the data loading options and requirements of Starburst Galaxy.
If necessary, convert the data into a format that is compatible with Starburst Galaxy. This might mean transforming CSV files into Parquet or ORC files, or ensuring JSON structure aligns with Starburst"s requirements. Use local tools or scripts to perform this conversion.
Manually upload the data to Starburst Galaxy. Use the platform"s interface to initiate the upload process, selecting the prepared files from your local system. Follow the prompts to specify details such as the target schema, table names, and any relevant data loading options.
After uploading, verify that the data has been correctly imported into Starburst Galaxy. Run queries to check for completeness, accuracy, and any discrepancies in the data. Compare a sample of records from Flexport with those in Starburst Galaxy to ensure data integrity.
Finally, optimize the data within Starburst Galaxy by indexing or partitioning tables as necessary to improve query performance. Document the entire process of data migration, including any challenges and solutions encountered, to streamline future migrations and facilitate knowledge sharing among team members.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Flexport is a full-service worldwide carriage forwarder and logistics platform using modern software to fix the user experience in worldwide trade and this platform is your supply chain source of truth. It makes managing global logistics as simple, maleable, and programmable as modern business demands. Flexport is completely full-service global freight forwarder and logistics platform using modern software to fix the user experience in global trade. Flexport is a certified freight forwarder that uses people and software to manage the complexity of international trade.
Flexport's API provides access to a wide range of data related to global logistics and supply chain management. The following are the categories of data that can be accessed through Flexport's API:
1. Shipment data: This includes information about the shipment, such as the origin and destination, carrier, mode of transportation, and estimated time of arrival.
2. Customs data: This includes information about customs clearance, such as the customs broker, customs clearance status, and any duties or taxes owed.
3. Inventory data: This includes information about the inventory, such as the quantity, location, and status of goods.
4. Purchase order data: This includes information about purchase orders, such as the supplier, order status, and delivery date.
5. Financial data: This includes information about invoices, payments, and other financial transactions related to the shipment.
6. Analytics data: This includes data related to shipment performance, such as transit times, delivery accuracy, and cost analysis.
Overall, Flexport's API provides a comprehensive set of data that can be used to optimize logistics and supply chain operations.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
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