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Begin by exporting the required data from Kyriba. Access Kyriba’s reporting or data extraction tools to generate the dataset you need. Choose a suitable format for export, such as CSV or Excel, which can be easily handled manually. Ensure that the data is complete and accurate before proceeding to the next step.
Once you have exported the data from Kyriba, review and clean the data to ensure it aligns with the schema and requirements of Starburst Galaxy. This may involve removing unnecessary columns, renaming fields, or converting data types to match the destination database’s structure.
Choose a secure method to transfer the data files from your local system to the Starburst Galaxy environment. This could involve using secure file transfer protocols such as SFTP or SCP. Make sure you have the appropriate access and credentials to perform the transfer securely.
After preparing the data and setting up the transfer method, upload the data files to the storage location accessible by Starburst Galaxy. This could be a cloud storage service integrated with Starburst Galaxy, such as AWS S3, Azure Blob Storage, or Google Cloud Storage. Ensure that the data is uploaded to the correct bucket or container.
Log into the Starburst Galaxy platform using your credentials. Navigate to the data management or ingestion section where you can manage and access the uploaded data files. Verify that the files have been correctly uploaded and are ready for further processing.
With the data now available in storage, create external tables in Starburst Galaxy to access the data. Use SQL commands or the platform’s interface to define tables that map to the structure of your data files in the storage location. Specify the correct file format and location path for each external table.
Execute SQL queries or use Starburst Galaxy’s data loading functionalities to ingest the data from the external tables into permanent tables within the database. This step finalizes the transfer process, making your data from Kyriba fully available and operational within Starburst Galaxy for analysis and querying.
By following these steps, you can manually transfer data from Kyriba to Starburst Galaxy without the need for third-party connectors or integrations.
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.
Kyriba is a global leader in cloud treasury and finance solutions, providing mission-critical capabilities for cash and risk management, payments, and working capital solutions. More than 2,500 clients worldwide rely on Kyriba to view, protect and grow their liquidity. Kyriba has connectivity in its DNA and is driven by research and innovation to uncover new ways to use APIs, artificial intelligence, and predictive analytics to support our customers. It unifies cloud offerings with a truly global community of customers, partners, and talented employees reaching over 100 countries worldwide.
Kyriba's API provides access to a wide range of financial data, including:
1. Cash Management Data: This includes information on cash balances, bank accounts, and transactions.
2. Payment Data: This includes details on payments made and received, including payment method, amount, and date.
3. FX Data: This includes exchange rates and currency conversion information.
4. Risk Management Data: This includes data on financial risks such as market risk, credit risk, and liquidity risk.
5. Treasury Management Data: This includes information on treasury operations such as cash forecasting, cash positioning, and cash pooling.
6. Compliance Data: This includes data on regulatory compliance, such as anti-money laundering (AML) and know your customer (KYC) requirements.
7. Reporting Data: This includes data on financial reporting, such as balance sheets, income statements, and cash flow statements.
Overall, Kyriba's API provides a comprehensive set of financial data that can be used to manage cash, payments, risk, compliance, and reporting.
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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