![]() This post will demonstrate the searches and dashboard I built in Splunk to provide analytics on my library. My Apple Music Library is an 18MB XML file when exported, with roughly 9,000 songs. While iStats does exactly what I need, I was curious how Splunk could provide any additional insights as it has a far greater capability to analyze big data. The previous blog posts for iStats are here: I was interested in seeing most played tracks, artists, and albums, and other statistics. iStats was designed to provide play and library analytics for my iTunes (now Apple Music) library. In the past I wrote a Javascript application called iStats, which I posted about a couple of times. I have it setup at home, primarily to learn, and sometimes to try new things. ![]() Splunk allows you to download and run it freely with a limited ingest, which is perfect for home use and/or training. ![]() I’ve been involved with it for the past few years at work. Splunk is a fantastic data analytics tool.
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