Eliminate noise. Elevate accuracy

Ensures trusted data by fixing inconsistencies, removing duplicates, and validating at scale.

The Hidden Cost of Dirty Data

Cleansing Engine Framework

Smart Deduplication

Integration with pipelines & tools

Business Impact

How to Start

The hidden cost of dirty data

If you don’t clean it, you’ll pay for it later

According to Gartner, poor data quality costs organizations an average of $12.9M per year.

These degrade everything—dashboards, ML models, personalization engines, and compliance efforts.

Common issues include:

Cleansing engine framework

From reactive fixes to preventive pipelines

Calsoft brings structured automation to the cleansing process:

Schema validation to detect type mismatches and rule violations

Standardization engines for formats, casing, address & date normalization

Business rule enforcement for custom validations (e.g., phone length by region)

AI-driven corrections using language models for typo detection and smart suggestions

Incremental validation during ingestion to prevent dirty data at entry

Smart deduplication

De-duplicate without losing what matters

We deploy entity resolution techniques to avoid blunt-force removal:

Rule-based and fuzzy matching

Threshold-driven similarity scoring (e.g., 85% match on Name + Email)

Survivorship logic to retain most complete, recent, or verified record

Graph-based clustering to resolve household or business entities

Master data creation for golden record reference

Integration with pipelines & tools

Cleanse where you already work

Calsoft integrates cleansing and deduplication into:

ETL/ELT tools: DBT, Informatica, Talend, Airflow

Data lakes and warehouses: Snowflake, Redshift, BigQuery, Databricks

Customer and product MDM: Reltio, Informatica MDM, AWS Entity Resolution

CRM & ERP: Salesforce, SAP, Dynamics

AI pipelines: MLflow, LangChain, Hugging Face

Business impact

Cleaner data = Faster action + higher confidence

Metric	Calsoft Result
Duplicate records reduced	↓ 94%
Null fields in key tables	↓ 78%
Data validation coverage	↑ 92%
Customer 360 reliability	↑ 3x
Downstream ML model accuracy	↑ 31%

How to start

Fix the foundation before you scale

Cleansing Readiness Assessment

Identify top dirty tables and inconsistent fields across environments.

Rule Configuration & Profiling

Define validation logic, acceptable value ranges, and matching rules.

Pipeline Integration & Execution

Inject real-time or batch cleansing logic into ETL/ELT flows.

Golden Record Certification

Tag deduplicated datasets with trust scores and lineage metadata.

Eliminate noise. Elevate accuracy

The hidden cost of dirty data

Cleansing engine framework

Smart deduplication

Integration with pipelines & tools

Business impact

How to start

Ensure accuracy and consistency with clean, unified data