DATA INTELLIGENCE PLATFORM

Smart Data Transformation & Quality Assurance

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

Masuk ke Dashboard Pelajari Workflow ↓

7SMARBRE Stages

10+Export Formats

2-WayData Conversion

RAWSMARBREREADY

JSON

CSV

XML

TXT

SQL

SMARBRE

Satu portal untuk seluruh siklus data

Konversikan struktur data, bersihkan kualitas data, lakukan pelabelan kelas, validasi hasil, dan ekspor ke berbagai format.

Konversi Dua Arah

Structured ⇄ Semi-structured ⇄ Unstructured dalam satu workflow.

Preprocessing & Labeling

Missing values, duplikasi, normalisasi, standardisasi, dan label kelas.

Quality Analytics

Grafik sebelum/sesudah, missing values, duplikasi, dan statistik dataset.

Custom Methods

Admin dapat menambah metode konversi dan preprocessing berbasis rule JSON yang aman.

END-TO-END

Workflow SMARBRE

Tujuh kapabilitas yang saling terhubung untuk pipeline data yang konsisten dan dapat diaudit.

Standardization

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

Mapping

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

Automation

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

Reconciliation

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

Batch Processing

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

Reporting

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

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.

Siap mengubah data mentah menjadi aset yang berkualitas?

Gunakan SMARBRE untuk membangun pipeline data yang konsisten, terukur, dan siap untuk analitik atau machine learning.

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