# Data Normalizer Pure code-based data format normalization tool that cleans and standardizes messy data using programmatic logic > Canonical page: https://elysiatools.com/en/tools/data-normalizer - **Category:** Data Processing - **Keywords:** data, normalizer, clean, standardize, format, csv, json, excel, data cleaning, data preprocessing ## Overview The Data Normalizer is a powerful utility designed to clean and standardize inconsistent datasets. By applying programmatic logic, it transforms messy CSV, JSON, XML, or spreadsheet data into a uniform, professional format ready for analysis or integration. ## Inputs - **Input Data** (textarea): Enter any data that needs normalization - CSV, JSON, XML, Excel spreadsheets, and other formats - **Input Format** (select): Select the format of your input data - **Output Format** (select): Select the format for your output data - **Normalization Options** (checkbox): Select which normalization operations to perform ## When to use - When merging datasets from multiple sources that use different formatting conventions. - When preparing raw data for database imports or API consumption that requires strict schema adherence. - When cleaning up exported files containing whitespace errors, empty rows, or inconsistent quote styles. ## How it works - Paste your raw data into the input field and select the source format or use auto-detection. - Choose your desired output format, such as JSON or CSV, to match your target system requirements. - Select specific normalization options like trimming whitespace, removing empty rows, or standardizing headers. - Process the data to generate a clean, structured output ready for immediate use. ## Use cases - Standardizing inconsistent CSV exports from legacy accounting software for import into a modern CRM. - Cleaning up JSON API responses by removing null values and trimming whitespace before frontend integration. - Converting mixed-format XML and TSV files into a unified CSV structure for spreadsheet analysis. ## Frequently asked questions ### What file formats are supported? The tool supports CSV, JSON, XML, TSV, and SSV formats. ### Can I remove empty rows automatically? Yes, simply check the 'Remove empty rows' option in the normalization settings. ### Does this tool handle data type conversion? Yes, by selecting 'Auto-detect and convert data types', the tool will attempt to identify and format numbers, booleans, and strings correctly. ### Is my data stored on your servers? No, all data processing is performed locally in your browser to ensure your information remains private. ### Can I standardize column headers? Yes, the 'Standardize column headers' option ensures your data follows a consistent naming convention. ## Related tools - [AI Data Normalizer](https://elysiatools.com/en/tools/ai-data-normalizer): AI-powered data format normalization tool that intelligently cleans and standardizes messy data using advanced AI analysis - [BOM Character Remover](https://elysiatools.com/en/tools/data-bom-remover): Remove BOM (Byte Order Mark) characters from text and file content. Perfect for cleaning up text files that have encoding issues, fixing CSV imports, and preparing data for processing. Features: - Detect and remove UTF-8 BOM (EF BB BF) - Detect and remove UTF-16 BOM (FE FF or FF FE) - Detect and remove UTF-32 BOM (00 00 FE FF or FF FE 00 00) - Support multiple input formats - Visual BOM character display - Detailed detection report - Support for batch text processing Common Use Cases: - Fix CSV file import errors - Clean up text file encoding issues - Prepare data for JSON parsing - Fix XML parsing problems - Resolve API data encoding conflicts - Standardize text data format - [Time Series Anomaly Detector](https://elysiatools.com/en/tools/time-series-anomaly-detector): Upload CSV or JSON time series data, detect anomalies with Z-Score and IQR methods, and return a chart-backed report - [Time Series Forecast & Seasonality Analyzer](https://elysiatools.com/en/tools/time-series-forecast-seasonality-analyzer): Forecast future periods from CSV or JSON time-series data and inspect trend, seasonal, and residual decomposition in one report - [JSON-LD Generator from CSV](https://elysiatools.com/en/tools/json-ld-generator-from-csv): Turn CSV or Excel rows into Schema.org JSON-LD for articles, products, or events, with validation-ready output for SEO workflows - [Excel to CSV Converter](https://elysiatools.com/en/tools/excel-to-csv): Convert Excel file to CSV format, extracting data from the first worksheet - [Text to Excel Converter](https://elysiatools.com/en/tools/text-to-excel): Convert various text formats to Excel with customizable parsing and formatting options - [XLSX Multi Sheet Splitter](https://elysiatools.com/en/tools/xlsx-multi-sheet-splitter): Split a multi-sheet workbook into independent files by sheet name, with ZIP output ## Samples - [CSV Samples](https://elysiatools.com/en/samples/csv-samples): Sample CSV files with various data types, sizes, and complexity levels - [Python Samples](https://elysiatools.com/en/samples/python): Essential Python code examples and Hello World demonstrations - [Android Serialization Java Samples](https://elysiatools.com/en/samples/android-serialization-java): Android Java serialization examples including JSON serialization, deserialization, and XML parsing - [Android Serialization Kotlin Samples](https://elysiatools.com/en/samples/android-serialization-kotlin): Android Kotlin serialization examples including JSON serialization, deserialization, and XML parsing ## Related content - [JSON Change Review and Normalization Workflow](https://elysiatools.com/en/hubs/json-format): Prepare a canonical JSON or JSONL input, compare it with a baseline or environment bundle, investigate quality signals, and deliver a documented normalized result.