Hi everyone,
I am currently working on a data tracking project where I compile external software performance logs into a spreadsheet to create a dashboard for system crashes and execution delays. I am importing raw string logs and timestamp files that originate from a mobile testing environment, but I am running into major cell overflow and formatting issues upon import.
The main problem is that a lot of the telemetry data contains nested brackets, symbols, and continuous strings without natural spaces. When I use the CSV import tool, it completely messes up the columns because the engine struggles to parse where a specific string package ends. This creates a chain reaction of automated formatting headaches, like forcing random line breaks across my rows or accidentally auto-converting alpha-numeric configuration strings into broken dates.
I have been analyzing the output layout instructions listed on this website to see if I can modify the raw data output settings at the source level before running the text-to-columns filter, but so far the formatting still breaks during the transition. I am trying to figure out if it is more efficient to build a custom Regular Expression macro within the spreadsheet to sanitize the layout during the paste operation, or if there is a native configuration option I am overlooking in the import wizard that stops the engine from guessing column data types so aggressively.
If anyone here routinely works with complex technical data logs or script execution sheets, what is your preferred workflow for preserving raw string formatting without having to manually clean up hundreds of rows after every import? I would really appreciate any advice on how to structure a macro or filter to handle this more seamlessly.