Excel

Time for some smoke & mirrors ..

Microsoft Excel

Data Input and Reading is handled through Pentaho's dedicated Excel input steps. The "Excel Input" and "Microsoft Excel Input" steps allow you to read both legacy .xls (Excel 97-2003) and modern .xlsx (Excel 2007+) formats directly into your transformations. You can specify which worksheets to read by name or index, define specific cell ranges (e.g., A1:G500 or Sheet2!B5:F100), skip header rows, and process multiple sheets within a single workbook either sequentially or in parallel. These steps automatically detect column names from the first row when configured and can handle complex workbook structures including merged cells, hidden sheets, and password-protected files (when credentials are provided).

Data Output and Writing is accomplished using the "Excel Output" and "Microsoft Excel Writer" steps, which support creating brand-new Excel files or appending data to existing workbooks. You have fine-grained control over formatting options including sheet names, cell styles, column widths, header row formatting, and data type preservation (dates, numbers, text). The output steps can dynamically name files using variables, write multiple sheets to a single workbook, and handle large datasets by streaming data rather than loading everything into memory - though extremely large files (100,000+ rows) may benefit from CSV export instead due to Excel's file size and performance limitations.

Template-Based Reporting and Dynamic Generation is a powerful feature where pre-formatted Excel templates serve as the foundation for automated report generation. You can create polished templates with company branding, charts, pivot tables, and conditional formatting, then use PDI to inject live data into specific cells or named ranges while preserving all formatting and formulas. This approach is ideal for recurring business reports (monthly sales summaries, financial dashboards, operational KPIs) where the layout remains constant but the data refreshes from your data warehouse or transactional systems. The "Excel Writer" step specifically supports template injection, allowing you to maintain separate template files managed by business users while PDI handles the data population.

Data Transformation and Business Logic Migration enables you to replicate Excel-based calculations within your ETL processes. Complex formulas used in Excel spreadsheets - such as VLOOKUP, SUMIF, nested IF statements, or custom business calculations - can be translated into PDI's Calculator, Formula, or User Defined Java Expression steps, moving the logic from desktop spreadsheets into enterprise-grade, version-controlled, and auditable ETL workflows. This migration is crucial when organizations need to scale beyond Excel's limitations, ensure data governance, or eliminate "spreadsheet hell" where critical business processes depend on error-prone manual spreadsheet manipulation.

Metadata Extraction and Schema Discovery capabilities allow PDI to intelligently inspect Excel files before processing. The input steps can automatically detect sheet names, column headers, data types (text, numeric, date, boolean), and even sample data to help you configure field mappings. This is particularly useful when dealing with dynamically structured Excel files where the schema isn't known in advance, or when building generic transformations that need to adapt to different Excel file layouts from various departments or external partners.

Error Handling and Data Quality Management provides several mechanisms to deal with Excel-specific challenges. You can configure how to handle empty cells (treat as null vs. empty string vs. zero), what to do with formula errors (#DIV/0!, #VALUE!, #REF!—either skip the row, substitute a default value, or log the error), and how to process cells with data validation errors or out-of-range dates. The "Filter Rows" and "Switch/Case" steps can route problematic records to error handling streams, while the "Write to Log" step helps identify which specific rows or cells caused issues, making it easier to work with business users to correct source data quality problems in their Excel files.