Aquata Data Platform Data Quality & Health

Financial Data Quality Platform for Modern Investment Management

The Aquata® data platform embeds data quality management into every step of ingestion and transformation. The programmatic framework detects exceptions across every stage of transformation, and flags violations to ensure uncompromising data integrity downstream. Users leverage no-code tools for simple rule authoring and data editing to create, maintain, and iterate for customizable and self-serviceable data oversight across capital markets.

Data Quality Framework for Clean Ingestion

The data quality framework ensures raw information from external sources flows cleanly through pipelines and connectors at every phase of ingestion and data preparation. The Aquata platform enables automated checks of incoming data against predefined quality standards across all six dimensions: completeness, accuracy, uniqueness, validity, consistency, and timeliness. This automation enables thorough cleansing of structured and unstructured documents by elegantly embedding validation rules into processing workflows for data in programmatic feeds, system integrations, PDFs, research reports, and regulatory filings.

These data quality automation tools power proactive data cleansing and validation to detect and resolve inconsistencies, missing values, duplicates, and erroneous data.

Self-Service Tools to Customize Data Quality Rules

Aquata’s rule manager provides intuitive self-service tools to customize your rule library and define tailored validation checks and quality enforcement at every step of the transformation journey, from ingestion to curation. Aquata Copilot supports AI-powered authoring so you can accelerate and democratize rule creation across business users and establish a data-driven culture. Define criteria for data ingestion, validation, ingress checks, and verification checks to maintain institutional-grade data integrity.

Buy-side and sell-side institutions can create specific rules according to their functional needs, such as:

Asset Managers

Reference data completeness
Security master consistency
Price validation

Asset Managers

Reference data completeness
Security master consistency
Price validation

Private Markets

Capital Call and Capital Distribution Accuracy
Valuation Methodology Consistency
Investor Allocation Checks

Capital Markets

Entity data uniqueness
Day-over-day balance sheet changes
Reference data checks

Hedge Funds

Security master accuracy
Market Data Timeliness
Leverage Exposure Rules

Asset Servicers

Client data ingest
Market data normalization
Valuation methodology consistency

Data Health Monitoring and Exception Management

For intraday oversight and data integrity, Aquata comes with a full exception-management workflow and data-quality analytics dashboards. View all anomalies and potentially adverse events in the dashboard and identify trends over time including time to close and the consistency of data quality from individual sources.

Data Editor provides auditable, governed access directly into the Aquata data tables. Manage data health by resolving discrepancies directly in the dataset, while retaining full audit trails for each change implemented.

Aquata’s data quality and cleansing framework for defining, running, and resolving exceptions allows firms to ensure best-in-class data quality from the outset.

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Financial Data Quality Platform for Modern Investment Management

Data Quality Framework for Clean Ingestion

Self-Service Tools to Customize Data Quality Rules

Asset Managers

Asset Managers

Data Health Monitoring and Exception Management

Read About Mastering the Five Essential Pillars of Data Management in Private Credit

Data Quality Framework for Clean Ingestion

Data Health Monitoring and Exception Management

Self-Service Tools to Customize Data Quality Rules

Asset Managers

Asset Managers

Read About Mastering the Five Essential Pillars of Data Management in Private Credit