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• Google Analytics 4 (GA4) vs Matomo

  7 avril 2022, par Erin

  Google announced that Universal Analytics’ days are numbered. Universal Analytics will be replaced by Google Analytics 4 (or GA4) on the 1st of July 2023. 

  If Google Analytics users want to compare year-on-year data, they have until July 2022 to get set up and start collecting data before the sun sets on Universal Analytics (or UA).

  But is upgrading to Google Analytics 4 the right move ? There’s a lot to consider, and many organisations are looking for an alternative to Google Analytics. So in this blog, we’ll compare GA4 to Matomo – the leading Google Analytics alternative. 

  In this blog, we’ll look at :

  What is Matomo ?

  Matomo is a powerful privacy-first web analytics platform that gives you 100% data ownership. First launched in 2007, Matomo is now the world’s leading open-source web analytics platform and is used by more than 1 million websites. 

  Matomo’s core values are based on ethical data collection and processing. Consistently more businesses and organisations from around the globe are adopting data-privacy-compliant web analytics solutions like Matomo. 

  Matomo offers both Cloud and On-Premise solutions (and a five-star rated WordPress plugin), making for an adaptable and flexible solution. 

  What is Google Analytics 4 ?

  Google Analytics 4 is the latest version of Google Analytics and represents a completely new approach to data-modelling than its predecessor, Universal Analytics. For an in-depth look at how GA4 and UA compare, check out this Google Analytics 4 vs Universal Analytics comparison. 

  Google Analytics 4 will soon be the only available version of analytics software from Google. So what’s the issue ? Surely, in 2022, Google makes it easy to migrate to their newest (and only) analytics platform ? Not quite.

  Google Analytics 4 vs Matomo

  Whilst the core purpose of GA4 and Matomo is similar (providing web analytics that help to optimise your website and grow your business), there are several key differences that organisations should consider before making the switch.

  Importing Historical Data from Universal Analytics

  Google Analytics 4

  Users assuming that historical data from Universal Analytics could be imported into Google Analytics 4 were faced with swift disappointment. Unfortunately, Google Analytics 4 does not have an option to import data from its predecessor, Universal Analytics. This means that businesses won’t be able to import and compare data from previous years.

  Matomo

  If you don’t want to start from scratch with your web analytics data, then Matomo is an ideal solution for data continuity. Matomo offers users the ability to import their historical Universal Analytics data. So you can keep all that valuable historical data you’ve collected over the years.

  

  User Interface

  Google Analytics 4

  GA4’s new user interface has been met with mixed reviews. Many claim that it’s overly complex and difficult to navigate. Some have even suggested that the tool has been designed specifically for enterprises with specialised analytics teams. 

  

  Matomo

  Matomo, on the other hand, is recognised for an easy to use interface, with a rating of 4.5 out of 5 stars for ease of use on Capterra. Matomo perfectly balances powerful features with a user-friendly interface so valuable insights are only a click away. There’s a reason why over 1 million websites are using Matomo. 

  

  Advanced Behavioural Analytics Features 

  Google Analytics 4

  While Google Analytics is undoubtedly robust in some areas (machine learning, for instance), what it really lacks is advanced behavioural analytics. Heatmaps, session recordings and other advanced tools can give you valuable insights into how users are engaging with your site. Well beyond pageviews and other metrics.

  Unfortunately, with this new generation of GA, Google still hasn’t introduced these features. So users have to manage subscriptions and tracking in third-party behavioural analytics tools like Hotjar or Lucky Orange, for example. This is inefficient, costly and time-consuming to manage. 

  

  Matomo 

  Meanwhile, Matomo is a one-stop shop for all of your web analytics needs. Not only do you get access to the metrics you’ve grown accustomed to with Universal Analytics, but you also get built-in behavioural analytics features like Heatmaps, Scroll Depth, Session Recordings and more. 

  Want to know if visitors are reaching your call to action at the bottom of the page ? Scroll Depth will answer that.

  Want to know why visitors aren’t clicking through to the next page ? Heatmaps will give you the insights you need.

  You get the picture – the full picture, that is. 

  

  Data Accuracy

  Google Analytics 4

  GA4 aims to make web and app analytics more privacy-centric by reducing the reliance on cookies to record certain events across platforms and devices. 

  However, when site and application visitors opt-out of cookie tracking, GA4 instead relies on machine learning to fill in the gaps. Data sampling could mean that your business is making business decisions based on inaccurate reports. 

  Matomo

  Data is the backbone of web analytics, so why make critical business decisions on sampled data ? With Matomo, you’re guaranteed 100% unsampled accurate data. So you can rest assured that any decisions you make are based on actual facts. 

  Compliance with Privacy Laws (GDPR, CCPA, etc.) 

  Google Analytics 4

  Google is making changes in an attempt to become compliant with privacy laws. However, even with GA4, users are still transferring data to the US. For this reason, both Austrian and French governments have ruled Google Analytics illegal under GDPR.

  The only possible workaround is “Privacy Shield 2.0”, but GDPR experts are still sceptical of this one. 

  Matomo

  If compliance with global privacy laws is a concern (and it should be), then Matomo is the clear winner here. 

  As an EU hosted web analytics tool, your data is stored in Europe, and no data is transferred to the US. On the other hand, if you choose to self-host, the data is stored in your country of choice.

  In addition, with cookieless tracking enabled, you can say goodbye to those pesky cookie consent screens. 

  Also, remember that under GDPR, and many other data privacy laws like CCPA and LGPD, end users have a legal right to access, amend and/or erase the personal data collected about them. 

  With Matomo you get 100% ownership of your web analytics data. This means that we don’t on-sell to third parties ; can’t claim ownership of the data ; and you can export your data at any time.

  

  Wrap up

  At the end of the day, the worst thing an organisation can do is nothing. Waiting until July 2023 to migrate to GA4 or another web analytics platform would be very disruptive and costly. Organisations need to consider their options now and start migrating in the next few months. 

  With all that said, moving to Google Analytics 4 could prove to be a costly and time-consuming operation. The global trend towards increased data privacy is a threat to platforms like Google Analytics which uses data for advertising and transfers data across borders.

  With Matomo, you get an easy to use all-in-one web analytics platform and keep your historical Universal Analytics data. Plus, you can future-proof your business by being compliant with global privacy laws and get access to advanced behavioural analytics features. 

  There’s a lot to weigh up here but fortunately, getting started with Matomo is easy. Try it free for 21-days (no credit card required) and see for yourself why over 1 million websites choose Matomo. 

  While this is the end of the road for Universal Analytics, it’s also an opportune time for organisations to find a better fit web analytics tool. 

  21 day free trial. No credit card required.

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• Files dissapearing with ffmpeg recursive conversion

  13 août 2014, par CaRoXo

  I started in askubuntu, asking for a way to convert recursively more than 14K of wma to mp3 extracting the wma files path from a txt file.
  There was an answer that could cover my needs, but a bug appears. The first run with some hundreds worked ok. The second, some wma albums got converted, others entirely deleted. There were some modifications. And last time completely, deleted all wma without converting.

  this was the original script

  #!/usr/bin/env bash
  
  
  
  readarray -t files < wma-files.txt
  
  
  
  for file in "${files[@]}"; do
  
      out=`echo $file | sed "s:wma:mp3:"`
  
      probe=`avprobe -show_streams "$file" 2>/dev/null`
  
      rate=`echo "$probe" | grep "bit_rate" | sed "s:.*=\(.*\)[0-9][0-9][0-9][.].*:\1:"`
  
      avconv -i "$file" -ab "$rate"k "$out"
  
      rm "$file"
  
  done

  Then the adaptation with ffmpeg

  #!/usr/bin/env bash
  
  
  
  readarray -t files < wma-files.txt
  
  
  
  for file in "${files[@]}"; do
  
      out=`echo $file | sed "s:wma:mp3:"`
  
      probe=`avprobe -show_streams "$file" 2>/dev/null`
  
      rate=`echo "$probe" | grep "bit_rate" | sed "s:.*=\(.*\)[0-9][0-9][0-9][.].*:\1:"`
  
      ffmpeg -i "$file" -ab "$rate"k "$out" && rm "$file"
  
  done

  With the first one I converted many files. Other just get deleted. The ones deleted were always the same release (so, all tracks from a release). I can listen, and even convert them with Soundkonverter.

  Both of them produces "no such file of directory" and when this happens, everything get deleted.

  The partition where files are stored is a usb HDD ntfs, but also happens in my ext4 internal HD.
  Im under Xubuntu 14.04

  Here the script running with avconv (wich what i managed to convert some, but other get dissapeared) http://pastebin.com/w5weqEws and with ffmpeg (that didn’t convert any) http://pastebin.com/3QkaPzvW

  I can’t find differences between successfully and deleted original wma’s. But for example, while other progs like beets read and write the tags, puddletag and mp3tag (under wine) don’t, until I converted them with soundkonverter.

  As the person trying to help me there redirect me here on the original post http://askubuntu.com/questions/508278/how-to-use-ffmpeg-to-convert-wma-to-mp3-recursively-importing-from-txt-file/508304#508304
  Im here asking for any help to make run an script like this. Or any to use ffmpeg to convert recursively the audio files. My capacity of understanding is short for being able to make something working just reading the docs.

  So I ask a help to run this. If I miss any relevant information, just tell me.

  NOTE : I want to add that doing the conversion with

  for file in "${files[@]}"; do
  
      out=`echo "$file" | sed s:wma:mp3:`
  
      avconv -i "$file" -ab 192k "$out"
  
      rm "$file"
  
  done

  It works in the same files (the ones that are deleted with the other). Only that it makes everything to 192k, so not good if Im converting lower bitrate ones. And get this error "Application provided invalid, non monotonically increasing dts to muxer in stream 0" that seems something typical from avconv in 14.04. With ffmpeg I cant try becouse I don’t find the way how to use it, even out of the script. I really don’t understand the docs seems
  .

  NOTE2 : This is a mediainfo exit from :

  1- A typical wma that get dissapeared always with the script

  Audio
  
  ID                                       : 1
  
  Format                                   : WMA
  
  Format version                           : Version 2
  
  Codec ID                                 : 161
  
  Codec ID/Info                            : Windows Media Audio
  
  Description of the codec                 : Windows Media Audio 9 - 128 kbps, 44 kHz, stereo 1-pass CBR
  
  Duration                                 : 2mn 25s
  
  Bit rate mode                            : Constant
  
  Bit rate                                 : 128 Kbps
  
  Channel(s)                               : 2 channels
  
  Sampling rate                            : 44.1 KHz
  
  Bit depth                                : 16 bits
  
  Stream size                              : 2.21 MiB (99%)
  
  Language                                 : English (US)

  2- A Wma that got succesfully converted (yes Im using copies now, I cant risk specially some rares audios that I got on the road)

  Audio
  
  ID                                       : 1
  
  Format                                   : WMA
  
  Format version                           : Version 2
  
  Codec ID                                 : 161
  
  Codec ID/Info                            : Windows Media Audio
  
  Description of the codec                 : Windows Media Audio 9 - 128 kbps, 44 kHz, stereo 1-pass CBR
  
  Duration                                 : 4mn 35s
  
  Bit rate mode                            : Constant
  
  Bit rate                                 : 128 Kbps
  
  Channel(s)                               : 2 channels
  
  Sampling rate                            : 44.1 KHz
  
  Bit depth                                : 16 bits
  
  Stream size                              : 4.21 MiB (99%)
  
  Language                                 : English (US)

  So, as I don’t see difference, but maybe, I’m losing any data to look into ?

• Of ctors and dtors

  18 février 2011, par Multimedia Mike — Programming, Sega Dreamcast

  I haven’t given up on the Sega Dreamcast programming. I was able to compile a bunch of homebrew code for the DC many years ago and I can’t make it work anymore. Again, I was working with a purpose-built, open source RTOS named KallistiOS (or KOS). I can make the programs compile but not run. I had ELF files left over from years ago which still executed. But when I tried to build new ELF files, no luck— the programs crashed before even reaching my main() function.

  I found the problem : ELF files are comprised of a number of sections and 2 of these sections are named ’.ctors’ and ’.dtors’ which stand for constructors and destructors. The KOS RTOS performs a manual traversal of .ctors section during program initialization and this is where things go bad. The traversal code doesn’t seem to account for a .ctors section that only contains a single entry. I commented out the function that does the traversal and programs started to work, at least until it was time to exit the program and return control to the program loader. That’s when the counterpart .dtors section traversal code ran and demonstrated the same problem. I’ll exhibit the problematic code at the end of this post.

  So I’m finally tinkering with Sega Dreamcast programming once again and with a slightly better grasp of software engineering than the first time I did this.

  Portable and Compatible C ?
  If nothing else, this low-level embedded stuff exposes you to some serious toolchain arcana, the likes of which you will likely never see working strictly in the desktop arena.

  Still, this exercise makes me wonder why C code from a decade ago doesn’t compile reliably now. Part of it is because gcc has gotten stricter about the syntax it will accept. In the case of this specific crashing problem, I suspect it comes down to a difference in the way the linker generates the final ELF file. I’ve written a list of items I have had to modify in the KOS codebase in order to get it to compile on more recent gcc versions. I wonder if it would be worth publishing the specifics, or if anyone would ever find the information useful ? Oh, who am I kidding ? Of course I’ll write it up, perhaps publish a new version of the code, if only because that’s the best chance I have of finding my own work again some years down the road.

  Problematic C Code
  See if this code makes any sense to you. It somehow traverse a list of 32-bit function pointers (in different directions, depending on constructors or destructors), executing each in turn. However, it appears to fall over if the list of pointers consists of a single entry.
  

  PLAIN TEXT

  C :

  1. typedef void (*fptr)(void) ;
  2.  
  3. static fptr ctor_list[1] __attribute__((section(".ctors"))) = { (fptr) -1 } ;
  4. static fptr dtor_list[1] __attribute__((section(".dtors"))) = { (fptr) -1 } ;
  5.  
  6. /* Call this to execute all ctors */
  7. void arch_ctors() {
  8.     fptr *fpp ;
  9.  
  10.     /* Run up to the end of the list (defined by crtend) */
  11.     for (fpp=ctor_list + 1 ; *fpp != 0 ; ++fpp)
  12.          ;
  13.  
  14.     /* Now run the ctors backwards */
  15.     while (—fpp> ctor_list)
  16.         (**fpp)() ;
  17. }
  18.  
  19. /* Call this to execute all dtors */
  20. void arch_dtors() {
  21.     fptr *fpp ;
  22.  
  23.     /* Do the dtors forwards */
  24.     for (fpp=dtor_list + 1 ; *fpp != 0 ; ++fpp )
  25.         (**fpp)() ;
  26. }