📊 Data Workbench
Transform, validate, and convert your data files with ease. Upload CSV, JSON, XML, YAML, Excel, or Parquet files to get started.
CSV, JSON, XML, YAML, NDJSON, Excel, Parquet
Up to 200MB
Understanding Data File Formats
📄 CSV (Comma-Separated Values)
CSV is a plain text format for storing tabular data, where each line represents a row and commas separate columns. It's the most widely used format for data exchange between spreadsheet applications, databases, and data analysis tools.
Common uses: Excel spreadsheets, database exports, data science projects, contact lists, sales reports, financial data, importing into Google Sheets, and migrating data between systems.
🔤 JSON (JavaScript Object Notation)
JSON is a lightweight data interchange format that's easy for humans to read and write, and easy for machines to parse. It uses key-value pairs and supports nested structures, making it ideal for complex hierarchical data.
Common uses: REST APIs, web applications, configuration files, NoSQL databases (MongoDB), mobile app data, JavaScript applications, data serialization, and microservices communication.
📑 XML (eXtensible Markup Language)
XML is a markup language that defines rules for encoding documents in a format that's both human-readable and machine-readable. It's self-descriptive with custom tags and supports schema validation for data integrity.
Common uses: SOAP web services, RSS feeds, configuration files, Microsoft Office documents, SVG graphics, Android layouts, sitemap.xml for SEO, and enterprise data integration.
⚙️ YAML (YAML Ain't Markup Language)
YAML is a human-friendly data serialization format that uses indentation to represent structure. It's more readable than JSON or XML and commonly used for configuration files in modern development workflows.
Common uses: Docker Compose files, Kubernetes configurations, CI/CD pipelines (GitHub Actions, GitLab), Ansible playbooks, application settings, and infrastructure as code.
📊 Excel (XLSX)
Excel XLSX is Microsoft's XML-based spreadsheet format that supports multiple sheets, formulas, charts, and rich formatting. It's the industry standard for business data analysis and reporting.
Common uses: Business reports, financial models, data analysis, budgeting, inventory management, project planning, sales tracking, and data visualization with charts.
🗄️ Parquet
Parquet is a columnar storage format optimized for big data analytics. It provides efficient compression and encoding schemes, making it ideal for processing large datasets with tools like Apache Spark and Hadoop.
Common uses: Data lakes, big data analytics, Apache Spark jobs, AWS Athena queries, data warehousing, machine learning pipelines, and processing terabyte-scale datasets efficiently.
Why Convert Between Data Formats?
🔄 Interoperability
Different systems and applications require specific formats. Converting CSV to JSON enables API integration, while JSON to XML supports legacy enterprise systems.
⚡ Performance Optimization
Parquet offers superior compression and query performance for analytics workloads compared to CSV, reducing storage costs and speeding up data processing.
🛠️ Development Workflows
Convert configuration files from JSON to YAML for better readability in DevOps pipelines, or transform API responses for different client applications.
📊 Data Analysis
Import JSON API data into Excel for business analysis, or export Excel reports to CSV for processing with Python pandas or R statistical software.