1. Financial data analytics using AWS Athena


    Sure, I'd be happy to help you get started with setting up an AWS Athena resource for financial data analytics.

    To achieve that, we're going to create an AWS Athena Database and a Data Catalog. In Athena, a database is a set of tables, and a Data Catalog is a collection of databases.

    Once the infrastructure is set, you can proceed with creating tables and performing queries for your financial data analysis.

    Here's a simple Pulumi program that creates an Athena database and data catalog.

    Remember to replace "my_data_catalog" and "my_finance_db" with your desired names for the data catalog and database, respectively.

    import pulumi from pulumi_aws import athena # Create an AWS Athena DataCatalog data_catalog = athena.DataCatalog("my_data_catalog", description="My Athena Data Catalog", parameters={ "example-key": "example-value", }, type="HIVE" ) # Create an AWS Athena Database database = athena.Database("my_finance_db", bucket="my-athena-bucket", # replace with your S3 bucket name name="finance_data", catalog_name=data_catalog.name, ) # Outputs pulumi.export("Data Catalog ID", data_catalog.id) pulumi.export("Database ID", database.id)

    This Python program with Pulumi sets an AWS Athena database for financial data analysis. It will create an Athena Data Catalog and an Athena Database, where you can create tables and perform SQL queries on your financial data.

    Here are the relevant Pulumi resources this program uses:

    • athena.DataCatalog is used to create a new Data Catalog, which is a collection of databases in Athena.

    • athena.Database is used to create a new Athena Database within the previously created Data Catalog. This is where your tables will be created.

    Before you can start querying data using Athena, you would need to create tables suitable for financial data analytics. The creation of tables depends on the structure of your financial data.

    Prerequisite: The S3 bucket referred in the bucket argument. You should first create an S3 bucket with your financial data or specify an existing one.

    Note: The creation of tables and execution of queries against these tables is not covered by this Pulumi program. It's a separate responsibility typically handled on the application-layer rather than infrastructure-layer.