Turn messy, unstructured data into clean, analysis-ready datasets. Expert data engineers ready to handle ETL pipelines, data integration, quality assurance, and automated workflows. From CSV cleaning to enterprise data lakes - we've got you covered.
Remove duplicates, fix errors, handle missing values. 99.9% data quality guaranteed.
Automated pipelines handle repetitive tasks. Free your team to focus on analysis, not cleanup.
Clean data = accurate analysis. Make confident business decisions with reliable datasets.
Set it and forget it. Scheduled ETL pipelines keep your data clean automatically.
Clean and prepare data for business intelligence dashboards, reporting tools (Tableau, Power BI), and statistical analysis
Preprocess datasets for ML models: feature engineering, normalization, handling imbalanced classes, train/test splits
Import legacy data into new CRM systems, merge duplicate contacts, standardize address formats, enrich with external data
Combine sales data from multiple channels, normalize product catalogs, reconcile inventory, prepare for analytics
Reconcile transactions, consolidate financial reports, handle currency conversions, prepare for accounting systems
Clean and structure scraped web data, extract key information, remove noise, standardize formats for analysis
💡 All prices are project-based. Custom quotes available for large-scale or ongoing data processing needs.
Data wrangling (also called data munging) is the process of cleaning, transforming, and organizing raw data into a format suitable for analysis. You need it because real-world data is messy - it has missing values, duplicates, inconsistent formats, and errors. Proper data wrangling ensures accurate analysis, better business decisions, and reliable machine learning models.
Time depends on data size and complexity: Small datasets (1K-100K rows) can be wrangled in 1-3 days. Medium datasets (100K-10M rows) typically take 1-2 weeks. Large datasets (10M+ rows) or complex transformations may take 2-4 weeks. We can provide a detailed timeline after reviewing your data.
We work with all data formats including CSV, Excel, JSON, XML, SQL databases (MySQL, PostgreSQL, MongoDB), APIs (REST, GraphQL), cloud storage (S3, Google Cloud, Azure), web scraping, and real-time streams. We can handle structured, semi-structured, and unstructured data.
Yes! We create automated ETL (Extract, Transform, Load) pipelines that run on schedule, handle new data automatically, validate quality, and alert on errors. This saves time and ensures consistent data quality. We use tools like Python (Pandas, Dask), Apache Airflow, and cloud-native solutions.
We always preserve your original data - we never modify or delete it. We create cleaned and transformed copies, leaving your source data untouched. All transformations are documented and reversible. We follow best practices for data backup and version control.
Yes, we work with sensitive data including PII (Personally Identifiable Information), financial data, healthcare records, and proprietary business data. We sign NDAs, use secure file transfer (SFTP, encrypted cloud storage), and can work in your secure environment. We're GDPR, HIPAA, and SOC 2 compliant.
Get a free consultation and detailed proposal for your data wrangling project. No obligations, just expert advice tailored to your data needs.
