if you're doing frequent updates of dashboards and always need the freshest data together with historical data. In turn, this can then be referenced by e.g. enable CANvas "auto conversion" and continuously expand your output database. In CANvas you can now specify to save an output file onto an existing output file, which will "append" it to the end of the file. from a fleet of FTP pushing WiFi C元000 units), you'll want an easy way to combine them into a dataset as they arrive on your PC or cloud server. If you're constantly getting new, small log files (e.g. Simply select the columns in Output Settings you wish to exclude and move them - and that's it:ĥ# Create Accumulating Output Datasets (NEW) Now we've made this really easy with our customized header selection! Often you'll want to exclude certain columns from your final output to compress or simplify. This lets you manipulate data sets far larger than what Excel normally handles (we've tested with 20 GB+ files).Ĥ# Customize Output File Column Structure (NEW) This makes the data a lot easier to utilize in Excel Pivot tables and many other programs.įurther, by excluding the info header from the output file, you'll be able to load the data directly into an Excel PowerPivot. one column for each of the following: YYYY, MM, DD, HH, MM, SS, kkk. In particular, we've added a "timestamp split" feature that allows you to split each part of the timestamp in separate columns: We've recently made it a lot easier to work with the output files in various 3rd party programs - incl. Sliced and diced, ready to provide you with insight!ģ# Excel & Pivot Friendly Timestamp & Header Format (NEW) They allow you in a few clicks to go from tons of log files and data - to a single, optimized output file with just the data you need. Together, Log File Merging and Downsampling provide a powerful combination: No problem - you can just add this information as separate columns in your output file! Maybe you also need the standard deviation, min, max or observation count per interval. The average may not be enough for your analysis. This lets you turn super frequent data into one observation per Signal per interval (e.g. For your analysis you may just need the long-term trend data - and 16 GB of high frequency data can be impractical.īy enabling Downsampling in your data conversion, you can aggregate your CAN data to a specified frequency (in miliseconds).
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