Financial data analytics using AWS Forecast

The following is a Pulumi program written in TypeScript. This program accomplishes the goal by setting up an example AWS Forecast dataset and a CloudWatch dashboard to monitor the forecast system.

Please update the program to use real forecasting data and AWS resources as per your use-case.

Here's the description for your program:

In this program you're setting up an AWS Forecast Dataset using the aws-native.Forecast::Dataset resource. You're also creating a Cloudwatch Dashboard using the aws.cloudwatch.Dashboard resource, which will aid in the real-time monitoring of your forecast data. This is a minimal solution for setting up financial data analytics on AWS using Pulumi. You will need to enhance and customize this according to your specific needs.

import * as pulumi from "@pulumi/pulumi";
import * as awsnative from "@pulumi/aws-native";
import * as aws from "@pulumi/aws";

// Create a Forecast dataset
const dataset = new awsnative.forecast.Dataset("financialForecastDataset", {
    datasetType: "TARGET_TIME_SERIES",
    domain: "CUSTOM",
    datasetName: "FinancialData",
    dataFrequency: "D",
    schema: {
        attributes: [ 
            { attributeName: "item_id", attributeType: "string" },
            { attributeName: "timestamp", attributeType: "timestamp" },
            { attributeName: "demand", attributeType: "float" }
        ]
    },
    encryptionConfig: {
        roleArn: "arn:aws:iam::123456789012:role/forecast", // update this with actual arn
        kmsKeyArn: "arn:aws:kms:us-east-1:123456789012:key/abcd1234-a123-456a-a12b-a123b4cd56ef" // update with actual kms key arn
    },
});

// Create Cloudwatch dashboard to monitor the forecast
const dashboard = new aws.cloudwatch.Dashboard("financialForecastDashboard", {
    dashboardName: "FinancialForecastDashboard",
    dashboardBody: `{
        "widgets": [
            {
                "type": "text",
                "x": 0,
                "y": 0,
                "width": 4,
                "height": 4,
                "properties": {
                    "markdown": "## AWS Forecast - Financial Data Analytics Dashboard"
                }
            }
        ]
    }`
});

// export the names
export const datasetName = dataset.name;
export const dashboardName = dashboard.dashboardName;

Please note to replace the "roleArn" and "kmsKeyArn" with actual ARNs for a KMS key and IAM role in your AWS account. These are required for data encryption configuration specified by "encryptionConfig" in the dataset.

Keep in mind this is a foundational setup. You need to update dataset schema, attributes and configure more specific widgets on the CloudWatch Dashboard based on what specifically you want to monitor from AWS Forecast which might depend on your business needs.

This is a starting point and there are various other components (like Predictor, Predicted vs Actual visualization, training dataset import, exporting forecasts etc.) which need to be added to make this a complete data analytics setup.