DATA INTELLIGENCE PLATFORM

Smart Data Transformation & Quality Assurance

SMARBRE represents the end-to-end workflow of data ingestion, transformation, and quality assurance.

7SMARBRE Stages
10+Export Formats
2-WayData Conversion
RAWSMARBREREADY
JSON
CSV
XML
TXT
SQL
SMARBRE

One portal for the entire data lifecycle

Convert data structures, improve data quality, label classes, validate results, and export to multiple formats.

01

Bidirectional Conversion

Structured ⇄ Semi-structured ⇄ Unstructured in one workflow.

02

Preprocessing & Labeling

Missing values, duplicates, normalization, standardization, and class labels.

03

Quality Analytics

Before/after charts, missing values, duplicates, and dataset statistics.

04

Custom Methods

Admins can add safe JSON rule-based conversion and preprocessing methods.

END-TO-END

SMARBRE Workflow

Seven connected capabilities for consistent and auditable data pipelines.

S
01

Standardization

Uniform formatting, data typing, and code-value normalization across disparate sources.

M
02

Mapping

Schema, column, and relationship mapping between source structures and target destinations.

A
03

Automation

Automated data preparation workflows: cleansing, validation, and deduplication.

R
04

Reconciliation

Post-conversion data matching and verification for count and value integrity.

B
05

Batch Processing

High-volume, scheduled processing of large datasets for optimal performance.

R
06

Reporting

Dashboards and logs showing conversion status, error rates, and quality metrics.

E
07

Extraction

Initial process of pulling raw data from databases, APIs, and flat files.

S • M • A • R • B • R • E

SMARBRE

represents the end-to-end workflow of data ingestion, transformation, and quality assurance.

SStandardizationUniform formatting, data typing, and code-value normalization across disparate sources.
MMappingSchema, column, and relationship mapping between source structures and target destinations.
AAutomationAutomated data preparation workflows: cleansing, validation, and deduplication.
RReconciliationPost-conversion data matching and verification for count and value integrity.
BBatch ProcessingHigh-volume, scheduled processing of large datasets for optimal performance.
RReportingDashboards and logs showing conversion status, error rates, and quality metrics.
EExtractionInitial process of pulling raw data from databases, APIs, and flat files.

Ready to turn raw data into quality assets?

Use SMARBRE to build consistent, measurable pipelines ready for analytics or machine learning.

Get Started →