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Continuous Data Alignment

Add context, ensure quality, and track lineage from the moment data is created.

What Is Data Alignment?

Data alignment ensures every piece of data has the right context, quality, and lineage before it enters your platforms. Without alignment, data arrives incomplete, untagged, and unusable for AI.

Gartner Framework: Alignment Capabilities

How Expanso implements each Gartner capability

Quantification & Quality

Gartner Definition:

Measure and ensure data quality metrics at the source.

How Expanso Delivers:

Our 'shift-left' cleaning, filtering, and schema analysis ensures data quality before it hits your warehouse, not after.

  • Real-time schema validation at origination
  • Anomaly detection on streaming data
  • Automatic filtering of null values and duplicates

Semantics

Gartner Definition:

Add context, meaning, and metadata to make data understandable.

How Expanso Delivers:

Add context and tags to data streams as they're created. Convert logs to JSON, enrich events with metadata - make your data usable for AI.

  • Semantic enrichment with business context
  • Log parsing and structured conversion
  • Metadata injection at source

Lineage

Gartner Definition:

Track data's origin, transformations, and journey.

How Expanso Delivers:

Create an immutable audit log and track data lineage from the moment of creation, not just from when it lands in S3.

  • Complete lineage from source device
  • Transformation tracking at every step
  • Immutable audit trail for compliance

Problems Data Alignment Solves

Data Arrives Without Context

Before:

Logs, events, and telemetry arrive as raw strings with no semantic meaning. Data teams spend weeks reverse-engineering what fields mean.

After:

Add semantic tags, business context, and metadata at creation. Data arrives self-describing and immediately usable.

70% reduction in data prep time

Quality Issues Discovered Too Late

Before:

Bad data (nulls, duplicates, wrong types) reaches warehouse. Data teams spend 60% of time cleaning retroactively.

After:

Validate schemas, detect anomalies, and filter bad data Only quality data reaches platforms.

80% fewer quality issues

No Lineage from Source

Before:

Data lineage starts when data lands in S3 or warehouse. Origin and early transformations are lost.

After:

Track every transformation from origination. Complete lineage from source device to final destination.

Complete audit trail

How Expanso Enables Data Alignment

1

Deploy at Data Origination Points

Lightweight agents run on source devices, gateways, or infrastructure - wherever data is created.

2

Apply Alignment Rules Declaratively

Define quality checks, semantic enrichment, and lineage tracking once. Apply everywhere automatically.

3

Track Transformations Immutably

Every filter, transform, and enrichment is logged. Complete audit trail from creation to destination.

Data Alignment in Action

Manufacturing: Quality Data for AI

Manufacturing

Production line telemetry arrives with machine IDs, timestamps, and operational context. No manual tagging needed.

3x faster model training with pre-contextualized data

Healthcare: HIPAA-Compliant Lineage

Healthcare

Track patient data from medical device → gateway → secure archive. Prove compliance to auditors.

100% audit trail for regulatory compliance

Financial Services: Transaction Context

Financial Services

Enrich transaction logs with customer IDs, risk scores, and regulatory flags at origination.

Real-time fraud detection with contextualized data

Add Context and Quality at the Source