Implement a backup technique for Amazon Fast Sight BI belongings

Amazon Fast Sight is a core characteristic inside Amazon Fast — an agentic, AI-powered digital workspace designed to maximise end-user productiveness— that gives AI-powered BI capabilities by way of pure language queries, interactive dashboards, and embedded analytics from trusted enterprise information sources.

Amazon Fast Sight belongings corresponding to dashboards, analyses, datasets, and information sources will be backed up utilizing the AssetsAsBundle APIs described on this put up. A backup technique helps shield towards unintentional deletions, unintended modifications, and regional disruptions. For groups that depend on Fast Sight to assist important enterprise selections, a well-designed backup plan is beneficial.

This put up is the primary in a two-part collection masking backup and restore for Amazon Fast Sight BI belongings:

• Half 1 (this put up): Covers find out how to design and implement a backup technique, together with asset choice, the APIs accessible for export, and a ready-to-use pattern automation software.
• Half 2: Covers the restore course of. You should use the backups created in Half 1 to recuperate belongings after unintentional deletion, unintended modifications, or as a part of a broader catastrophe restoration plan.

An efficient backup technique is particularly important for organizations in closely regulated industries corresponding to monetary companies, healthcare, and vitality, for a number of causes:

• Information loss prevention protects towards human errors, unintentional deletions, and occasions like ransomware.
• Assembly restoration aims helps organizations obtain their Restoration Level Aims (RPO) and Restoration Time Aims (RTO), minimizing information loss throughout incidents.
• Audit and reporting helps monitoring and reporting on belongings all through their lifecycle (creation, updates, and deletion).
• Elevated workload resiliency permits fast restoration of programs to earlier states, decreasing downtime and enhancing reliability. This aligns with the Reliability pillar of the AWS Properly-Architected Framework.
• Catastrophe restoration (DR) preparedness offers a basis for implementing a DR course of that anticipates technology-related disasters and contributes to your group’s enterprise continuity plan (BCP).

For extra details about the catastrophe restoration capabilities of Fast, and find out how to assess them towards organizational necessities, see the Amazon Fast catastrophe restoration and resiliency information.

On this put up, we cowl finest practices for implementing an efficient backup technique for BI belongings in Fast Sight. We begin by masking the choices for choosing the belongings to incorporate in your backup, then clarify the high-level APIs accessible for that goal, and finalize with pattern code that will help you get began shortly.

Backup practices for enterprise intelligence

BI programs current distinctive enterprise continuity challenges due to their function in supporting decision-making processes and key stakeholders. You need to shield them towards service disruptions by implementing an efficient backup plan. Earlier than constructing this plan, it’s necessary to know the structure and the scale to contemplate as a part of your DR plan.

The previous diagram reveals that Fast Sight depends on AWS’s international infrastructure throughout a number of AWS Areas to present excessive availability for Fast Sight belongings, together with information sources, datasets, analyses, and dashboards.

The Tremendous-fast, Parallel, In-memory Calculation Engine (SPICE) shops and encrypts imported information with excessive availability (HA) by way of redundant copies throughout a number of Availability Zones (AZs) throughout the Fast Sight Area.

With this regional design, you may preserve assets in a number of Areas and use a secondary Area within the unlikely occasion of a regional outage affecting your main BI assets.

For consumer and identification administration, Fast Sight makes use of a single Area that you simply outline in the course of the preliminary account subscription course of. The diagram reveals that this Area hosts consumer and group identification info and should be accessible for customers to entry Fast Sight.

For instance, if a consumer needs to entry a dashboard within the eu-west-1 Area however the Fast Sight major Area is us-east-1, each Areas should be accessible to complete the consumer entry circulation. Fast Sight makes use of regional structure with AZs for redundancy. Nonetheless, if your corporation wants safety towards the unlikely occasion of a regional outage, you could design your catastrophe restoration (DR) technique accordingly.

Tip: Should you’re not sure of your Fast Sight major Area, you may retrieve this info by working the next command:

aws quicksight describe-account-settings --aws-account-id XXXXXXXXXXXX --region us-east-1

Be aware: This aws quicksight describe-account-settings command specifies us-east-1 because the endpoint Area. Should you obtain a 200 standing, your identification Area is us-east-1. In any other case, you obtain an error like the next, which instructs you to level to your present identification Area (for instance, eu-west-1):

An error occurred (AccessDeniedException) when calling the DescribeAccountSettings operation: Operation is being known as from endpoint us-east-1, however your identification area is us-east-1. Please use the eu-west-1 endpoint.

Defining Fast Sight belongings to incorporate within the backup plan

With a clearer understanding of Fast Sight structure, the following step is deciding on the belongings to incorporate in your backup plan, for this you may comply with two methods:

Again up particular belongings:

This feature is appropriate if you outline a backup or DR technique targeted on defending important belongings for your corporation operations which you can conveniently restore after a catastrophe or unintentional deletion. This contains particular dashboards (and their dependent belongings) that key stakeholders use to make enterprise selections or that working groups (finance, logistics, procurement, and so forth) use to assist continued enterprise operation.

This feature is beneficial if you require a simple backup plan and when the BI belongings which might be key to enterprise continuity are a subset of all of the belongings accessible in your Fast Sight occasion.

Again up all belongings:

This technique is beneficial if you wish to outline a backup technique that covers each versioning and potential catastrophe restoration. By backing up all belongings, you may carry out in-place rollback of any asset to a earlier state if a human error causes an unintended modification or deletion. Moreover, as a result of you’ve a backup of all belongings in your account, you may choose particular belongings to revive as a part of your DR plan.

This method offers you most protection but in addition requires extra complicated orchestration and automation. This put up focuses on this technique and offers pattern code which you can adapt to attenuate time to manufacturing.

After you choose your technique, select the kind of BI belongings to export. Fast Sight affords the next asset sorts:

• Dashboards: Learn-only belongings focused at reader customers, printed from an evaluation. It’s also possible to save a dashboard to an evaluation to make edits.
• Analyses and dashboards: An evaluation is an editable model of a dashboard. Solely the authors you select can entry it.
• Information sources: A knowledge supply implements the connection to your information, which may come from analytic sources corresponding to databases or information warehouses, AWS companies corresponding to Amazon Easy Storage Service (Amazon S3), or third-party software program as a service (SaaS) information suppliers corresponding to Jira and ServiceNow.
• Datasets: An asset kind that makes use of an information supply to entry exterior information that you need to use to arrange and construction the information that powers your analyses and dashboards.
• VPC connections: A characteristic that you need to use to combine together with your VPC assets corresponding to databases and information warehouses which might be situated in that VPC or reachable from it (peered VPCs or networks linked by way of VPN or AWS Direct Join).
• Themes: A group of styling and look settings which you can apply to a number of analyses and dashboards to match an aesthetic normal that meets your product or company branding wants.

All these belongings have dependencies between one another, with analyses and dashboards on the prime of this dependency chain, as the next diagram illustrates.

While you select the asset sorts to again up, pay attention to these dependencies so you may absolutely restore belongings from the backup. For instance, if you again up a dashboard, you additionally must again up its dependencies, which could embody datasets, information sources, VPC connections, and a theme. The subsequent sections clarify how Fast Sight export APIs deal with these dependencies.

Backup course of overview

The mechanism we cowl on this put up makes use of the AssetsAsBundle APIs accessible in Fast Sight. AssetsAsBundle APIs (additionally referenced as AAB APIs) are a set of high-level APIs designed to assist programmatic export and import of Fast Sight assets. They cowl a spread of use circumstances corresponding to launch administration, backup and restore, cross-account migration, and steady integration and steady supply (CI/CD) workflows.

This set of APIs contains the next operations:

• StartAssetBundleExportJob: Creates a bundle (bundle) that accommodates the belongings exported as a part of the operation. The bundle is a zipper file with textual content recordsdata. The format will be both JSON or AWS CloudFormation relying on the worth specified within the ExportFormat parameter. Relying on the format, you may import these belongings utilizing the AAB APIs straight or use CloudFormation infrastructure as code (IaC) for provisioning. After the asynchronous operation finishes, the system uploads the bundle to a brief S3 location for downloading.
• StartAssetBundleImportJob: Takes a beforehand exported bundle and restores the belongings packed in it. You should use the import operation to outline overrides for a large set of parameters corresponding to asset names and information supply connection parameters (host, port, workgroup, and extra).
• DescribeAssetBundleImportJob and DescribeAssetBundleExportJob: Each AssetBundle operations are asynchronous. You should use these APIs to explain the operation, ballot for its standing, and act after it finishes. While you carry out an export job, you need to use DescribeAssetBundleExportJob to retrieve the DownloadUrl for the bundle, which is legitimate for five minutes. You may renew the URL with additional calls to DescribeAssetBundleExportJob.

Supported belongings and present limitations of AssetsAsBundle APIs

AssetsAsBundle APIs assist a listing of Fast Sight belongings together with analyses, dashboards, information sources, datasets, shared folders, restricted folders, refresh schedules, themes, and VPC connections. Nonetheless, some asset sorts have limitations.

Unsupported information sources: Adobe Analytics, File, GitHub, Jira, Salesforce, ServiceNow, Amazon S3 (with domestically uploaded manifest recordsdata), and Twitter.

Unsupported datasets: Datasets that include machine studying (ML) columns generated utilizing inference by way of linked SageMaker ML fashions.

You need to exclude these belongings out of your backup plan to keep away from an InvalidParameterValueException error if you situation the StartAssetBundleExportJob operation.

To work round this, you may exchange unsupported information sources and datasets by following these procedures.

For Amazon S3 information sources with native manifest recordsdata:

1. Create a brand new Amazon S3 information supply.
2. Add the manifest file to Amazon S3.
3. Reference the manifest file out of your information supply.
4. Exchange the information supply within the dependent datasets utilizing the UpdateDataSet API.

For different unsupported information sources and datasets:

Comply with this process to rework your incompatible dataset right into a appropriate one:

1. Create an evaluation linked to the information supply you wish to assist in your backup.
2. Create a desk visible that shows all dataset columns.
3. Export the information as a CSV file.
4. Create an Amazon S3 dataset utilizing a manifest uploaded to Amazon S3.
5. Replace your analyses and dashboards with the brand new dataset utilizing the exchange dataset performance.

Different belongings to contemplate as a part of your backup

Though Fast Sight assets are the important thing belongings to again up, you should embody some extra assets and configurations in your backup plan for potential restore or catastrophe restoration conditions.

You may export Fast Sight belongings together with their permissions, together with the customers and teams which have entry to them. You management this by setting the IncludePermissions flag to true.

As a result of every Fast Sight asset is owned by a consumer, you should again up customers and teams to have a full and restorable backup.

AssetsAsBundle APIs don’t cowl customers and teams, however you need to use DescribeUser, DescribeGroup, and DescribeGroupMembership to incorporate this info within the backup.

Along with customers and teams, think about backing up account settings corresponding to account customization (the DescribeAccountCustomization API), custom-made manufacturers (the DescribeBrand API), and folders (the ListFolders, DescribeFolder, and DescribeFolderPermissions APIs).

Technical implementation

On this part, we cowl find out how to create an automation that orchestrates the invocation of the Fast Sight APIs wanted to carry out an efficient backup implementation. We offer pattern code on the finish of this part that implements each customers and teams backup and Fast Sight belongings backup.

Backup orchestration circulation

The automation software helps three modes of operation: consumer backup solely, belongings backup solely, and each. This offers most flexibility if you carry out your backup plan. The next diagram reveals the circulation that the software follows relying on the chosen operation mode.

Customers and group backup

The consumer and teams backup service makes use of the Fast Sight consumer and group APIs to learn your account’s present state and retailer the retrieved consumer and group information in Amazon DynamoDB. The service makes use of date-based suffixes for DynamoDB desk names to protect historic backup information and forestall overwrites. This enables point-in-time restoration and backup historical past monitoring. This design additionally simplifies restore operations since you don’t must filter by date suffixes if you question information inside a selected backup.

Instance for a backup run on 2025-10-19:

• Customers: quicksight-users-backup-2025-10-19
• Teams: quicksight-groups-backup-2025-10-19
• Consumer-Group Memberships: quicksight-users-groups-backup-2025-10-19

Customers Desk Schema:

{
  "user_name": "string (partition key)",
  "arn": "string",
  "e mail": "string",
  "function": "string",
  "identity_type": "string",
  "lively": "boolean",
  "principal_id": "string",
  "backup_timestamp": "string (ISO 8601)",
  "custom_permissions_name": "string"
}

Teams Desk Schema:

{
  "group_name": "string (partition key)",
  "arn": "string",
  "description": "string",
  "principal_id": "string",
  "members": ["list of user names"],
  "backup_timestamp": "string (ISO 8601)"
}

Customers-Teams Membership Desk Schema:

{
  "membership_id": "string (partition key, format: username#groupname)",
  "user_name": "string",
  "group_name": "string",
  "user_arn": "string",
  "group_arn": "string",
  "backup_timestamp": "string (ISO 8601)"
}

Be aware: The consumer and group backup service implements dual-Area assist. Consumer and group operations use the identity_region configuration parameter, whereas backup asset operations use the usual aws_region. This design addresses enterprise situations the place Fast Sight identification administration is configured in a distinct Area than asset storage.

Property backup

The belongings bundle backup service coordinates the export of belongings inside a Area and uploads the generated bundle to an Amazon S3 location for later use. The automation backs up the next belongings: information sources, datasets, analyses, dashboards, and themes. By default, the backup contains all dependencies. You may disable this setting if wanted.

At a excessive degree, the service performs the next duties:

• Lists all information sources utilizing the ListDataSources API, filtering out Amazon S3 manifest-based information sources and information sources with invalid VPC connection names. Names should include solely alphanumeric characters separated by hyphens.
• Lists all datasets utilizing the ListDataSets API, filtering out FILE datasets by checking the ImportMode subject.
• Lists all analyses utilizing the ListAnalyses API.
• Lists all dashboards utilizing the ListDashboards API.
• Teams belongings by kind for separate export jobs. You may configure the variety of belongings to incorporate in every bundle, with a most of 100 (the API restrict).
• Checks the export job standing utilizing the DescribeAssetBundleExportJob API and implements exponential backoff to keep away from throttling.
• Uploads the finished asset bundle to Amazon S3 utilizing the next prefix construction.

my-QuickSight-backups/
└── QuickSight-backups/                          # Customized S3 prefix
    ├── 2024/01/15/
    │   ├── datasources/
    │   │   ├── datasources-143022.zip            # Single bundle (≤ max_assets_per_bundle)
    │   │   └── datasources_bundle_1-143045.zip   # A number of bundles when belongings exceed restrict
    │   ├── datasets/
    │   │   ├── datasets_bundle_1-143045.zip      # A number of bundles when belongings exceed restrict
    │   │   └── datasets_bundle_2-143045.zip      # Sequential numbering for a number of bundles
    │   ├── analyses/
    │   │   └── analyses-143108.zip               # Single bundle
    │   └── dashboards/
    │       ├── dashboards_bundle_1-143131.zip    # First of a number of dashboard bundles
    │       └── dashboards_bundle_2-143131.zip    # Second dashboard bundle
    └── 2024/01/16/
        ├── datasources/
        │   └── datasources-090015.zip
        ├── datasets/
        │   └── datasets-090030.zip
        └── ...

Be aware: The bundle quantity string is current solely when the variety of belongings to again up exceeds the configured worth in max_assets_per_bundle.

Finish-to-end software for backup creation

The QuickSight-backup software offers a easy method to export all of your Fast Sight belongings and their dependencies into sturdy, cheap storage corresponding to Amazon S3. The software creates new prefixes for generated bundles, so earlier backups aren’t overwritten. The software additionally exports customers and teams utilizing the identical precept: DynamoDB shops this information, and desk names include the date when the backup was generated. With this method, you need to use backups as a supply in your restoration technique and monitor the historical past of modifications to your Fast Sight belongings and related customers.

The code makes use of the Boto3 Python SDK and contains packaging assist by way of setuptools for setup and use.

Tooling utilization and configuration

Earlier than utilizing the software, ensure you meet the next conditions:

• Python 3.8 or greater.
• A Fast Sight account with Enterprise version or greater.
• AWS Command Line Interface (AWS CLI) configured with acceptable credentials.
• Required AWS permissions. See the Permissions part within the code.

Clone from supply

git clone https://github.com/aws-samples/sample-quicksight-backup-tool.git
cd quicksight-backup-tool

Create a Python venv (beneficial)

python3 -m venv ./.venv
supply .venv/bin/activate

Set up the bundle

Create a configuration file

To get began, seek advice from the config-basic.yaml file within the repo or create one from scratch. This configuration file defines key parameters for the software, together with the next:

• AWS account.
• Area.
• Backup places (DynamoDB tables and Amazon S3 bucket prefixes).

Utilizing the software

After set up, you may run the software as follows:

quicksight-backup --config config.yaml --mode full

You solely want to supply the --config parameter. You may omit the remainder. The --mode parameter controls the backup kind (full, users-only, or assets-only), the place full is the default mode. The next record describes the arguments the software helps.

Optionally available arguments

• --mode, -m: Backup mode (full, users-only, assets-only); default is full.
• --output-dir, -o: Output listing for studies and manifests.
• --verbose, -v: Allow verbose (DEBUG) logging.
• --log-file: Path to log file.
• --dry-run: Validate configuration with out working the backup.
• --no-progress: Disable progress indicators.
• --generate-manifest: Generate a backup manifest file.
• --generate-report: Generate a human-readable backup report.
• --version: Present model info.

For extra info, see the software README file.

Device code

You will discover the code for this software within the aws-samples repository. This software helps you get began shortly. Use it as a foundational reference to refine and adapt in your particular backup necessities.

Earlier than you implement a backup answer in your manufacturing setting, affirm that you simply:

• Evaluate and adapt the code to align together with your particular infrastructure necessities, safety insurance policies, and compliance requirements.
• Conduct thorough testing in a non-production setting to validate performance and efficiency.
• Implement acceptable safety controls together with encryption, entry administration, and audit logging required by your group.
• Validate restoration procedures to substantiate your backup technique meets your outlined Restoration Time Aims (RTO) and Restoration Level Aims (RPO).
• Contemplate price optimization methods and monitoring to maintain the answer inside your operational funds.
• Keep away from concurrent software execution: This software depends on the AssetsAsBundle APIs, which have low throttling thresholds. The pattern software isn’t designed to run a number of situations in parallel throughout the similar AWS account. If a number of groups want to make use of the software, think about implementing a concurrency management mechanism (for instance, a lock desk in DynamoDB or a database-level lock) to stop concurrent runs that would set off API throttling.

Scheduled execution

The pattern software described within the earlier part is designed for on-demand execution and is nicely fitted to getting began or working ad-hoc backups. For a production-grade backup technique, you would possibly wish to automate backup runs on a recurring schedule in order that your Fast Sight belongings are persistently protected with out handbook intervention.

This part outlines the high-level structure for a scheduled, absolutely automated backup answer. Detailed implementation and code for this structure are exterior the scope of this put up.

Structure overview

The scheduled execution structure is constructed on three AWS managed companies that work collectively to supply a dependable, serverless, and cost-effective automation pipeline:

• Amazon EventBridge is the scheduler. It triggers the backup workflow at an outlined cadence, for instance, every day at midnight. EventBridge guidelines allow you to outline versatile cron-based or rate-based schedules with out managing any underlying infrastructure.
• AWS Step Capabilities is the orchestration layer. It coordinates the run of the person backup steps within the appropriate sequence. Step Capabilities offers built-in error dealing with, retry logic, and execution historical past, which makes it nicely fitted to long-running workflows that span a number of API calls and asynchronous operations.
• AWS Lambda implements every particular person backup step as an unbiased, stateless operate. Splitting the backup logic throughout a number of Lambda capabilities addresses the time constraints inherent within the backup course of. Every export job is asynchronous and would possibly take a number of minutes to complete, relying on the quantity and dimension of belongings being exported.

Workflow steps

As a result of the end-to-end backup course of can take a major period of time, the automation is decomposed into discrete steps, every carried out by a devoted Lambda operate. AWS Step Capabilities orchestrates these capabilities in sequence, passing state between them and dealing with retries for transient failures. The workflow consists of the next steps:

1. Customers and teams backup: Retrieves all Fast Sight customers, teams, and group memberships utilizing the Fast Sight identification APIs and persists the information to DynamoDB with date-based desk suffixes, as described within the Technical implementation part. This operation can run in parallel with the asset backup operations as a result of it doesn’t have any dependency.
2. Asset backup discovery: Lists all Fast Sight belongings within the goal Area (information sources, datasets, analyses, and dashboards), applies the mandatory filters to exclude unsupported asset sorts, and teams belongings into lists of as much as 100 objects every. The output of this step is handed to subsequent steps as enter.
3. Generate bundle: Initiates export jobs for all of the belongings included within the record specified because the enter parameter, polls for job completion, and uploads the ensuing ZIP bundles to the designated Amazon S3 prefix.
4. Verify standing: Periodically polls the lively bundle execution and notifies the AWS Step Capabilities state machine when the export finishes.

The next diagram illustrates the high-level circulation of the scheduled execution structure.

Key design concerns

• Asynchronous polling: The check-status Lambda operate polls the job initiated by the generate-bundle Lambda operate utilizing the DescribeAssetBundleExportJob API till the job reaches a terminal state (SUCCESSFUL or FAILED). The check-status Lambda operate runs in a loop with a ready situation (for instance, 30 seconds) between calls.
• Parallelism: Configure an sufficient degree of parallelism to regulate the quantity of API calls carried out by the steps in your workflow, particularly on the generate-bundle step that calls the DescribeAssetBundleExportJob and StartAssetBundleExportJob APIs, which have low concurrent fee limits. You should use the inline map state MaxConcurrency subject to restrict the variety of concurrent runs of the generate-bundle step.
• Error dealing with: Step Capabilities helps you to outline catch blocks and retry insurance policies at every stage. A failure in a single step (for instance, an unsupported asset kind) doesn’t abort the whole backup run.
• Value: When scheduling is enabled, prices scale with backup frequency and retention interval. For steering on estimating storage prices, see the Value estimation part.

Value estimation

The next sections estimate the prices of working the backup software on Amazon S3 (for asset bundles) and DynamoDB (for consumer and group metadata).

Amazon S3: asset bundle storage

Asset bundles are compressed ZIP recordsdata uploaded to Amazon S3 after every export job. Based mostly on the answer design, every bundle of as much as 100 belongings averages roughly 500 KB when compressed.

Key takeaway: Amazon S3 storage prices for asset bundles are minimal. Even for very giant Fast Sight deployments with hundreds of belongings, the compressed bundle dimension stays within the low megabytes vary, leading to a month-to-month storage price nicely beneath $0.01.

Amazon DynamoDB: consumer and group metadata storage

Consumer and group info is saved in DynamoDB tables with date-based suffixes to protect backup historical past. DynamoDB storage is priced at roughly $0.25 per GB per 30 days (Normal desk class, on-demand mode).

Every merchandise saved in DynamoDB represents a single consumer or group definition (together with all related attributes corresponding to ARN, e mail, function, group memberships, and backup timestamp). Based mostly on the schema described on this put up, the typical merchandise dimension is roughly 256 KB.

You should use this method to estimate the dimensions of your DynamoDB tables:

Desk dimension estimate = Variety of objects × Common merchandise dimension (256 KB)

Key takeaway: For small and medium organizations, DynamoDB storage prices stay minimal (beneath $0.10 per 30 days per backup snapshot). For big organizations with tens of hundreds of customers, prices are nonetheless modest, within the low single-digit greenback vary per snapshot.

Abstract

For a single, unscheduled backup run, the whole AWS price is successfully close to zero, dominated by a couple of cents of Amazon S3 and DynamoDB storage at most. Should you implement scheduled backups (lined within the Scheduled execution part), prices scale linearly with backup frequency and retention interval. Even with every day backups retained for 90 days, complete storage prices stay within the low single-digit greenback vary for many deployments. Think about using Amazon S3 Lifecycle insurance policies and DynamoDB Normal-IA to optimize prices as your backup historical past grows.

Conclusion

On this put up, we lined find out how to design and implement a complete backup technique for Amazon Fast Sight belongings so you may preserve enterprise continuity, meet regulatory necessities, and shield towards information loss.

We lined find out how to use AssetsAsBundle APIs to programmatically export and protect important BI belongings, together with dashboards, analyses, datasets, and information sources, together with their dependencies and permissions. That can assist you get began, this put up features a pattern automation software which you can check and adapt to your group’s wants. The code orchestrates these APIs, shops asset bundles in Amazon S3, and preserves consumer and group info in DynamoDB for point-in-time restoration.

Prepared to guard your Fast Sight BI belongings? Get began at this time by cloning the pattern backup software from the AWS Samples repository and testing it in your non-production setting. Start with a easy configuration to again up your most crucial dashboards, then broaden to a production-ready backup technique as you validate the method. To be taught extra about Amazon Fast Sight, see the Amazon Fast Sight Consumer Information.

Concerning the writer