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First, ensure you have an AWS account and the necessary permissions to create and manage resources like DynamoDB tables. You can do this by logging into the AWS Management Console and setting up IAM roles with appropriate policies to access DynamoDB.
Navigate to the DynamoDB service in the AWS Management Console. Create a new table by specifying a table name and a primary key (partition key). For exchange rates, you might choose a combination like `currency_code` as the partition key and `date` as the sort key, depending on your data needs.
Use a programming language such as Python to write a script that fetches data from the exchange rates API. You can use libraries like `requests` to send HTTP GET requests to the API endpoint and retrieve the JSON data. Ensure that you handle any authentication required by the API.
Once you have the API response, parse the JSON data to extract the relevant exchange rate information. You might need to transform this data into a format suitable for DynamoDB, matching the table's schema. For example, ensure each entry has the necessary attributes like `currency_code`, `date`, and `exchange_rate`.
Install and configure the AWS SDK for your programming language (e.g., Boto3 for Python). Set up your AWS credentials in your development environment by configuring the AWS CLI or directly in the SDK. This will allow your script to interact with DynamoDB.
Use the AWS SDK to write the parsed and transformed data to your DynamoDB table. You can use the `put_item` method to insert each record. Ensure you handle exceptions and errors, such as conditional checks or throughput limits, to maintain data integrity and performance.
To regularly update your DynamoDB table with the latest exchange rates, automate the script using a scheduler. If you're using AWS, you can deploy your script as an AWS Lambda function and use Amazon CloudWatch Events to trigger it at regular intervals. Alternatively, use a cron job if you're running the script on a local server.
By following these steps, you can efficiently transfer data from an exchange rates API to DynamoDB without relying on 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.
Used by tens of thousands of developers, Exchange Rates API provides accurate and reliable currency data instantly through its free, simple-to-use API interface. With more than 10 years of exceptional API uptime and support, developers trust Exchange Rates API to provide fast and accurate conversion rates for 160 different currencies as well as essential stock market data in JSON format. They have worked hard to achieve their mission of building a remarkably hardware efficient and reliable currency converter API.
Exchange Rates API provides access to various types of data related to currency exchange rates. The API offers real-time and historical exchange rates for over 170 currencies, including cryptocurrencies. The following are the categories of data that the Exchange Rates API provides:
• Real-time exchange rates: The API provides real-time exchange rates for various currencies, which are updated every minute.
• Historical exchange rates: The API offers historical exchange rates for up to 10 years, allowing users to analyze trends and patterns in currency exchange rates.
• Currency conversion: The API allows users to convert one currency to another using the latest exchange rates.
• Time-series data: The API provides time-series data for exchange rates, allowing users to track changes in exchange rates over time.
• Currency metadata: The API provides metadata for various currencies, including their names, symbols, and ISO codes.
• Cryptocurrency data: The API provides real-time exchange rates for various cryptocurrencies, including Bitcoin, Ethereum, and Litecoin.
Overall, the Exchange Rates API provides a comprehensive set of data related to currency exchange rates, making it a valuable resource for businesses and individuals who need to track currency exchange rates.
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.
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