This release contains total reserves (includes gold, current US$). The data is available from year 1960. Total reserves comprise holdings of monetary gold, special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities. The gold component of these reserves is valued at year-end London prices. Data are in current U.S. dollars. This product works with GS Financial Cloud.
Total reserves comprise holdings of monetary gold, special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities. The gold component of these reserves is valued at year-end (December 31) London prices. Data are in current U.S. dollars. This release contains total reserves (includes gold, current US$) for all countries in the world.
The original publisher of this data is The World Bank. This content is published as World Bank Open Data and provides free and open access to global development data. This work is licensed under a Creative Commons Attribution 4.0 (CC-BY 4.0). This data is anonymized/aggregated.
Total reserves (includes gold, current US$) (total-reserves.csv)
CloudFormation template that setups up automatic revision updates plus AWS analytics services such as AWS Glue and Amazon Athena (cloudformation.yaml)
AWS Lambda code for revision updates (post-processing-code.zip)
Please note, in the post processing code, we use a Lambda layer that extends the AWS Python SDK (boto3) that is built into the Lambda Python runtime by adding the AWS Data Exchange and AWS Marketplace Catalog API SDKs as of November 13, 2019. Once the public SDKs are updated to include AWS Data Exchange APIs, we will update the code to remove this Lambda layer.
Deploy CloudFormation template to set up automatic revision updates and AWS Analytics services
Assuming you have subscribed to this product listing, below are the detailed steps to deploy CloudFormation template:
(Please note that you will need IAM permissions for CloudFormation, AWS Data Exchange, IAM, Lambda, Glue, Athena and QuickSight, in order to deploy the CloudFormation template.)
Under the product listing, scroll down to Data sets section and click on the Data set name
Under the Revisions section, click on the most recent revision
Under Assets, checkmark total-reserves/automation/post-processing-code.zip and click Export to S3
Choose the S3 Bucket where you would like to store the dataset. Make sure you only choose the S3 bucket. The asset comes with a pre-defined directory structure
Under Assets, checkmark total-reserves/automation/cloudformation.yaml and click either Export to S3 or Export to computer
If you exported the cloudformation.yaml to S3, go to the S3 UI on the AWS console and navigate to the location where the cloudformation.yaml is stored. In S3, click on the cloudformation.yaml and copy the url from the Object URL
Now, from your AWS Management Console, log onto Amazon CloudFormation UI and click Create Stack
Under Choose a template either provide the template via uploading from local computer or specify the S3 object url and click Next
Provide a friendly stack name in the Stack name text box
In the SourceS3Bucket field, input the S3 bucket name that you chose earlier to store the total-reserves/automation/post-processing-code.zip file
Leave rest of the fields as is
Click Next
In the Options screen, click Next
Tick mark the I acknowledge that AWS CloudFormation might create IAM resources. box
Click Create
At a high level, CloudFormation will setup following resources automatically.
Lambda function to setup automatic AWS Data Exchange revision updates for this dataset
CloudWatch Event rule that will automatically trigger the Lambda function every time a new revision update is published
Another Lambda function to setup AWS Glue and Amazon Athena
Necessary IAM roles and permissions
If you are interested in looking at the AWS Lambda code or the CloudFormation template, feel free to inspect files inside total-reserves/automation/post-processing-code.zip and total-reserves/automation/cloudformation.yaml
Analytics & Visualizations
Apart from the source data, what we are also providing in this product listing is an easy way to interact and extract value out of the dataset. Native AWS Analytics services such as AWS Glue, Amazon Athena and Amazon QuickSight provide different ways to interact and visualize the data. The included AWS CloudFormation template sets up AWS Glue and Amazon Athena automatically in your AWS account.
Using AWS Glue and Amazon Athena to run interactive queries against the dataset
Once the CloudFormation template is successfully deployed, the data is immediately searchable, queryable, and available on Athena. You can go to the Athena UI from the AWS Management Console and run SQL queries on the dataset.
Here are some sample Athena SQL queries you can try on the dataset.
# list total reserves for all countries for year 2017
SELECT "country_name", "2017" FROM "total_reserves"."data";
# list yearly total reserves for "china"
SELECT * FROM "total_reserves"."data" WHERE "country_name" = 'china';
# compare total reserves for "china between year "2000" and "2017"
SELECT "country_name", "2000", "2017" FROM "total_reserves"."data" WHERE "country_name" = 'china';
# compare total reserves between "brazil" and "china"
SELECT * FROM "total_reserves"."data" WHERE "country_name" IN ('brazil', 'china');
Setup Amazon QuickSight to create visualizations on the dataset
Below are the detailed steps to analyze dataset using Amazon QuickSight
From your AWS Management Console, log onto Amazon QuickSight
Click Manage data
Click New data set
If you ran the provided CloudFormation template, you should already have your database and table with schema created in AWS Glue and Athena
Click on Athena to connect to your data source
Provide a name for your QuickSight Data source name and click Create data source
In the Database: contain sets of table dropdown, choose database as total_reserves and under Tables: contain the data you can visualize, choose table as data
At this point, you can Edit/Preview data if you like
You can then click on Select
In the Finish data set creation screen, you can select Visualize to finish the creation of data set process
Visualize the data set by selecting the Horizontal bar chart from the Visual types
Drag country_name field to the Y axis in Field wells and for e.g. drag 2017 field in the Value block to chart the data
You are now ready to start analyzing and visualizing the dataset.
Contact Information
If you have questions about the source data, please contact data@worldbank.org. If you have any questions about the CloudFormation stack, Lambda code or any of the AWS services being used, please contact data@rearc.io.
About Rearc
Rearc is a cloud, software and services company. We believe that empowering engineers drives innovation. Cloud-native architectures, modern software and data practices, and the ability to safely experiment can enable engineers to realize their full potential. We have partnered with several enterprises and startups to help them achieve agility. Our approach is simple — empower engineers with the best tools possible to make an impact within their industry.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
This listing is free. You get one pricing dimension, Product Access (Units), which grants subscribers access to the dataset. There are no tiers, usage charges, or size options to compare. Access is granted at no cost through your subscription. The vendor publishes this publicly available dataset on AWS Data Exchange so you can consume it in a consistent format without the work of sourcing and processing it yourself.
Top-of-mind questions for buyers
What does the Product Access (Units) dimension grant me?
It grants your subscription access to the Total Reserves dataset. There is a single unit that unlocks the data. It does not meter usage, count records, or scale by data volume. Once subscribed, you can consume the published dataset through AWS Data Exchange.
Does my cost change as I query or download more data?
No. This listing is free and has one access dimension with no usage-based charges. Downloading more records, querying more often, or adding users does not create software fees. Note that AWS storage or transfer charges for your own environment may apply separately.
How is the dataset delivered and kept current?
The vendor publishes this publicly available dataset on AWS Data Exchange. You consume it in a consistent format without sourcing or processing it yourself. The vendor owns the life cycle for the dataset, so updates are handled on their side.
www.rearc.io
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