To handle inconsistent data from multiple sources in Google Sheets for IT asset tracking, I would take a structured approach involving cleaning, validation, and automation. First, I would focus on data cleaning by identifying common errors such as duplicates, extra spaces, and inconsistent formatting. I would use Google Sheets features like the 'Remove Duplicates' tool and the 'Trim Whitespace' function to standardize the data. For missing data, I would decide on a strategy, whether it's imputation, deletion, or marking them as missing, depending on the context and importance of the data.

Next, I would implement data validation rules to ensure data integrity. This includes setting up drop-down lists for specific fields, using date and number formats, and applying conditional formatting to highlight potential issues. I would also use formulas to cross-check data across different cells to identify discrepancies.

For automation, I would leverage Google Sheets formulas like VLOOKUP, SUMIF, and COUNTIF to streamline data analysis. Additionally, I would use Google Apps Script to automate repetitive tasks and create dynamic reports. For visualization, I would use Google Sheets' built-in charts and graphs to present the data clearly and effectively. This approach ensures that the data is accurate, reliable, and ready for decision-making processes.