Kramata

Kramata organizes Excel and CSV files through reusable recipes. The system joins sheets by key, groups data, unpivots wide columns into long format, generates calculated columns, removes duplicates, standardizes dates, and flags rows with errors. Each recipe is built once and executed on new files or entire folders, producing byte-identical results every run. Processing happens locally and handles large files without freezing.

★★★★★

5.0(1 ratings)

• Sheet joining by key. The module pulls columns from a second file by matching a common key, working as a reproducible VLOOKUP that never breaks when column order changes. It preserves the original row count by using the first match per key, preventing unexpected duplicates in the final output.
• Grouping and totals. This function groups rows by one or more columns and computes sums, counts, and averages on the selected numeric fields. It operates like a pivot table that can be re-run on every new file without manually reconfiguring ranges or updating references.
• Unpivot from wide to long. Transforms month or category columns into tidy rows in a single step, reversing cross-tab structures without the multiple operations Excel demands. Each value migrates to a new row while retaining the original record identification keys.
• Calculated columns. Allows creating totals, differences, percentages, and averages across columns without learning any formula language. Operations are configured by selecting source columns and calculation type, and they recalculate automatically each time a file is processed.
• Duplicate removal. Detects and removes repeated rows based on any combination of columns. The system keeps the first occurrence and discards subsequent ones, applying the cleanup consistently in every scheduled recipe execution.
• Date format fixing. Automatically standardizes heterogeneous date formats within a single column, converting varied text representations into a uniform and sortable format. It also trims spaces, unifies letter case, and fills blank cells with user-defined values.
• Problematic row flagging. Rows that fail configured checks are diverted to a separate flagged list for review and export. No record is silently dropped; every data point that violates a rule remains accessible for subsequent auditing.
• Batch processing over folders. Runs a recipe across all files in a folder at once, returning each cleaned file separately or merging all results into a single consolidated document. The same transformations apply to hundreds of reports without manual intervention.
• Exact reproducibility. The same input combined with the same recipe produces byte-identical output on every execution. This property eliminates discrepancies between deliveries and guarantees complete traceability in recurring workflows.
• Large file handling. Incorporates an in-process database that loads large CSV files and allows smooth scrolling without interface freezes. The underlying technology manages memory so data volumes that exceed Excel limitations are processed fluidly.
• Before and after preview. The interface displays a direct comparison of the original state and the transformed result before export. The left panel contains the cleanup step sequence while the right panel reflects applied changes in real time on the spreadsheet.
• Combinable predefined steps. The program includes ready-made cleanup operations selected from a list and chained into a custom recipe. Each step is configured by indicating target columns and adjusting a few options, without writing code or formulas.

Kramata began development in 2026 as a response to the weekly repetition of data cleanup tasks in environments where Excel and CSV are the standard exchange formats. The responsible team, with experience in data analysis and software engineering, designed the application to bridge the gap between repetitive manual operations and transformation tools requiring advanced technical knowledge. The application is written in TypeScript and leverages DuckDB as its internal processing engine, enabling manipulation of large files directly on the user's machine without depending on external services.

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