Amazon Redshift integration

Relate Redshift analysis to the customers, suppliers and transactions it describes. Uplyst connects warehouse results with operational records across the business.

Controlled access to analytical data

AWS identity

IAM controls access to supported temporary database credential mechanisms.

Workload identityScoped IAM permissions

Redshift permissions

Database users and roles determine which schemas, tables and views the integration can read.

Database rolesApproved source objects
Uplyst

Analytical results linked to business entities

Source query, reporting period and currency retained.
How it connects

Connect Amazon Redshift to Uplyst

Approved Redshift tables and views can supply analytical data to Uplyst through SQL access. Warehouse records are mapped to shared customer, supplier and transaction identities, connecting historical measures to current business activity.

Redshift supports database clients and the Data API, which runs SQL asynchronously through an HTTP endpoint without a persistent client database connection. The deployment and workload determine the appropriate access method and refresh schedule.

Redshift access review separates an AWS workload role from database grants on an approved supplier spend view, with UK01 row scope and no write access.
Workload identity and database grants define which analytical records the integration can read.

AWS identity and database permissions

The Redshift Data API supports AWS Secrets Manager credentials and temporary database credentials. IAM permissions govern access to these mechanisms, while database users, roles and grants control access to source objects.

The integration's permissions cover the intended schemas, tables, views and operations. Authentication and database access are configured for the selected provisioned or serverless deployment.

Fit queries around warehouse workloads

Query scope, concurrency and scheduling affect the capacity available to existing reporting workloads. Timeouts and cancellation keep integration queries within the operating limits of the warehouse.

An extract becomes useful business context when its results are complete. Retaining execution state and checking completeness allows an interrupted read to resume or restart without presenting a partial dataset as current.

Relate warehouse facts to current activity

Supplier and customer identifiers can differ across legal entities and source applications. Uplyst's business model relates those identifiers while preserving their source, so historical spend or revenue connects to the correct operational records.

Currency, reporting period and calculation rules give each measure its business meaning. Source view and query references help explain the result.

Redshift dataBusiness context
Supplier spendSupplier identity, currency and reporting period
Sales and revenueCustomers, orders and financial records
Delivery performanceCurrent commitments and operational events
Query resultSource calculation and refresh time

Supplier and financial visibility

Procurement can combine historical spend and delivery variance with open commitments to understand supplier exposure. Finance can relate warehouse measures to invoices, payments and the customers behind them.

The last completed refresh and source reporting period help teams judge whether the analysis is current enough for the decision. Reconciliation accounts for corrections to earlier periods.

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