QUORA

Quality Operations & Reconciliation Agent
Detects, explains, and helps resolve data quality issues, reconciliation breaks, mapping problems, and inconsistencies across systems, especially in Databricks/lakehouse environments.
QUORA AI data quality and reconciliation agent illustration

What QUORA Can Do For You

QUORA uses an agentic quality and reconciliation pipeline to detect data issues, explain root causes, compare data across systems, and help teams resolve inconsistencies across Databricks, lakehouse, and downstream reporting environments.
Data Quality Detection
QUORA monitors and scans datasets, tables, and data products for quality issues such as missing values, duplicates, invalid formats, threshold breaches, schema drift, and unexpected distribution changes, surfacing the problems that need attention first.
Reconciliation Break Analysis
QUORA compares records, balances, aggregates, and control totals across systems and lakehouse layers, identifying where breaks occur, how material they are, and which upstream or downstream process is most likely responsible.
Mapping & Transformation Validation
QUORA reviews mapping rules, joins, transformations, and reference data logic to detect inconsistencies between source, clean, curated, and reporting layers, helping teams find broken assumptions before they reach consumers.
Root Cause Explanation
QUORA links observed quality failures back to lineage, pipeline runs, metadata, and recent data changes, generating plain-language explanations that show what changed, why the issue appeared, and which teams need to act.
Remediation Recommendation Support
QUORA proposes practical remediation actions for each issue: fix mappings, correct reference data, rerun failed pipelines, update quality rules, or route exceptions to data owners, always keeping human approval at the point of change.
Lakehouse Quality Operations
QUORA works across Databricks and lakehouse environments, monitoring quality rules, reconciliation controls, data product health, and operational exceptions so teams can manage trusted data at production scale, not by spreadsheet.

How it works

From a single conversation to a production-ready, tested, and committed data application — infrastructure dependencies aside.

1

Connect to data platforms and controls

QUORA connects to your lakehouse, data catalogues, quality rule stores, reconciliation outputs, and pipeline metadata. It reads the control framework already in place and builds a structured view of what should be checked, where, and why.

2

Scan data quality and reconciliation results

QUORA evaluates tables, data products, and pipeline outputs against configured checks: schema, completeness, duplicates, thresholds, mappings, aggregates, and cross-system control totals. Breaks are prioritised by severity, business impact, and downstream exposure.

3

Investigate root cause across lineage

When an issue appears, QUORA traces it through source systems, transformations, joins, reference data, and recent pipeline runs, using lineage and metadata to explain where the inconsistency started and which process likely introduced it.

4

Recommend remediation and route ownership

QUORA generates a clear remediation plan for each issue: the evidence, the suspected cause, the recommended fix, and the accountable owner. Data teams can review, approve, reject, or assign the action before anything is changed.

5

Track resolution and strengthen controls

Once remediation is approved, QUORA tracks progress through closure, records the outcome, and recommends updates to data quality rules or reconciliation controls so the same issue is detected earlier, or prevented entirely, next time.

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Who is it for

QUORA is built for data teams that need trusted, reconciled data across lakehouse and enterprise systems without relying on manual investigation every time a break appears.
Data quality, governance & operations teams
Detect issues faster, explain them clearly, and route them to the right owner. QUORA reduces manual investigation time and gives quality teams a structured operating model for managing exceptions across the data estate.
Data engineering & platform teams
Keep Databricks and lakehouse pipelines production-ready with automated checks, lineage-aware diagnostics, and remediation recommendations. QUORA helps engineers focus on fixing root causes, not hunting through logs and spreadsheets.
Finance, risk & reporting teams
Get confidence that figures reconcile before they reach reporting, regulatory submissions, or management packs. QUORA highlights breaks, explains the evidence, and tracks resolution so business users know which data can be trusted.