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• Google Analytics 4 and GDPR : Everything You Need to Know

  17 mai 2022, par Erin

  Four years have passed since the European General Data Protection Regulation (GDPR, also known as DSGVO in German, and RGPD in French) took effect.

  That’s ample time to get compliant, especially for an organisation as big and innovative as Google. Or is it ? 

  If you are wondering how GDPR affects Google Analytics 4 and what the compliance status is at present, here’s the lowdown. 

  Is Google Analytics 4 GDPR Compliant ?

  No. As of mid-2022, Google Analytics 4 (GA4) isn’t fully GDPR compliant. Despite adding extra privacy-focused features, GA4 still has murky status with the European regulators. After the invalidation of the Privacy Shield framework in 2020, Google is yet to regulate EU-US data protection. At present, the company doesn’t sufficiently protect EU citizens’ and residents’ data against US surveillance laws. This is a direct breach of GDPR.

  Google Analytics and GDPR : a Complex Relationship 

  European regulators have scrutinised Google since GDPR came into effect in 2018.

  While the company took steps to prepare for GDPR provisions, it didn’t fully comply with important regulations around user data storage, transfer and security.

  The relationship between Google and EU regulators got more heated after the Court of Justice of the European Union (CJEU) invalidated the Privacy Shield — a leeway Google used for EU-US data transfers. After 2020, GDPR litigation against Google followed. 

  This post summarises the main milestones in this story and explains the consequences for Google Analytics users. 

  

  2018 : Google Analytics Meets GDPR 

  In 2018, the EU adopted the General Data Protection Regulation (GDPR) — a set of privacy and data security laws, covering all member states. Every business interacting with EU citizens and/or residents had to comply.

  GDPR harmonised data protection laws across member states and put down extra provisions for what constitutes sensitive personal information (or PII). Broadly, PII includes any data about the person’s :

  • Racial or ethnic origin 
  • Employment status 
  • Religious or political beliefs
  • State of health 
  • Genetic or biometric data 
  • Financial records (such as payment method data)
  • Address and phone numbers 

  Businesses were barred from collecting this information without explicit consent (and even with it in some cases). If collected, such sensitive information is also subject to strict requirements on how it should be stored, secured, transferred and used. 

  7 Main GDPR Principles Explained 

  Article 5 of the GDPR lays out seven main GDPR principles for personal data and privacy protection : 

  • Lawfulness, fairness and transparency — data must be obtained legally, collected with consent and in adherence to laws. 
  • Purpose limitation — all personal information must be collected for specified, explicit and legal purposes. 
  • Data minimisation — companies must collect only necessary and adequate data, aligned with the stated purpose. 
  • Accuracy — data accuracy must be ensured at all times. Companies must have mechanisms to erase or correct inaccurate data without delays. 
  • Storage limitation — data must be stored only for as long as the stated purpose suggests. Though there’s no upper time limit on data storage. 
  • Integrity and confidentiality (security) — companies must take measures to ensure secure data storage and prevent unlawful or unauthorised access to it. 
  • Accountability — companies must be able to demonstrate adherence to the above principles. 

  Google claimed to have taken steps to make all of their products GDPR compliant ahead of the deadline. But in practice, this wasn’t always the case.

  In March 2018, a group of publishers admonished Google for not providing them with enough tools for GDPR compliance :

  “[Y]ou refuse to provide publishers with any specific information about how you will collect, share and use the data. Placing the full burden of obtaining new consent on the publisher is untenable without providing the publisher with the specific information needed to provide sufficient transparency or to obtain the requisite specific, granular and informed consent under the GDPR.”

  The proposed Google Analytics GDPR consent form was hard to implement and lacked customisation options. In fact, Google “makes unilateral decisions” on how the collected data is stored and used. 

  Users had no way to learn about or control all intended uses of people’s data — which made compliance with the second clause impossible. 

  Unsurprisingly, Google was among the first companies to face a GDPR lawsuit (together with Facebook). 

  By 2019, French data regulator CNIL, successfully argued that Google wasn’t sufficiently disclosing its data collection across products — and hence in breach of GDPR. After a failed appeal, Google had to pay a €50 million fine and promise to do better. 

  2019 : Google Analytics 4 Announcement 

  Throughout 2019, Google rightfully attempted to resolve some of its GDPR shortcomings across all products, Google Universal Analytics (UA) included. 

  They added a more visible consent mechanism for online tracking and provided extra compliance tips for users to follow. In the background, Google also made tech changes to its data processing mechanism to get on the good side of regulations.

  Though Google addressed some of the issues, they missed others. A 2019 independent investigation found that Google real-time-bidding (RTB) ad auctions still used EU citizens’ and residents’ data without consent, thanks to a loophole called “Push Pages”. But they managed to quickly patch this up before the allegations had made it to court. 

  In November 2019, Google released a beta version of the new product version — Google Analytics 4, due to replace Universal Analytics. 

  GA4 came with a set of new privacy-focused features for ticking GDPR boxes such as :

  • Data deletion mechanism. Users can now request to surgically extract certain data from the Analytics servers via a new interface. 
  • Shorter data retention period. You can now shorten the default retention period to 2 months by default (instead of 14 months) or add a custom limit.  
  • IP Anonymisation. GA4 doesn’t log or store IP addresses by default. 

  Google Analytics also updated its data processing terms and made changes to its privacy policy. 

  Though Google made some progress, Google Analytics 4 still has many limitations — and isn’t GDPR compliant. 

  2020 : Privacy Shield Invalidation Ruling 

  As part of the 2018 GDPR preparations, Google named its Irish entity (Google Ireland Limited) as the “data controller” legally responsible for EEA and Swiss users’ information. 

  The company announcement says : 

  

  Initially, Google assumed that this legal change would help them ensure GDPR compliance as “legally speaking” a European entity was set in charge of European data. 

  Practically, however, EEA consumers’ data was still primarily transferred and processed in the US — where most Google data centres are located. Until 2020, such cross-border data transfers were considered legal thanks to the Privacy Shield framework. 

  But in July 2020, The EU Court of Justice ruled that this framework doesn’t provide adequate data protection to digitally transmitted data against US surveillance laws. Hence, companies like Google can no longer use it. The Swiss Federal Data Protection and Information Commissioner (FDPIC) reached the same conclusion in September 2020. 

  The invalidation of the Privacy Shield framework put Google in a tough position.

   Article 14. f of the GDPR explicitly states : 

  “The controller (the company) that intends to carry out a transfer of personal data to a recipient (Analytics solution) in a third country or an international organisation must provide its users with information on the place of processing and storage of its data”.

  Invalidation of the Privacy Shield framework prohibited Google from moving data to the US. At the same time, GDPR provisions mandated that they must disclose proper data location. 

  But Google Analytics (like many other products) had no a mechanism for : 

  • Guaranteeing intra-EU data storage 
  • Selecting a designated regional storage location 
  • Informing users about data storage location or data transfers outside of the EU 

  And these factors made Google Analytics in direct breach of GDPR — a territory, where they remain as of 2022.

  2020-2022 : Google GDPR Breaches and Fines 

  The 2020 ruling opened Google to GDPR lawsuits from country-specific data regulators.

  Google Analytics in particular was under a heavy cease-fire. 

  • Sweden first fined Google for violating GDPR for no not fulfilling its obligations to request data delisting in 2020. 
  • France rejected Google Analytics 4 IP address anonymisation function as a sufficient measure for protecting cross-border data transfers. Even with it, US intelligence services can still access user IPs and other PII. France declared Google Analytics illegal and pressed a €150 million fine. 
  • Austria also found Google Analytics GDPR non-compliant and proclaimed the service as “illegal”. The authority now seeks a fine too. 

  The Dutch Data Protection Authority and  Norwegian Data Protection Authority also found Google Analytics guilty of a GDPR breach and seek to limit Google Analytics usage. 

  New privacy controls in Google Analytics 4 do not resolve the underlying issue — unregulated, non-consensual EU-US data transfer. 

  Google Analytics GDPR non-compliance effectively opens any website tracking or analysing European visitors to legal persecution.

  In fact, this is already happening. noyb, a European privacy-focused NGO, has already filed over 100 lawsuits against European websites using Google Analytics.

  2022 : Privacy Shield 2.0. Negotiations

  Google isn’t the only US company affected by the Privacy Shield framework invalidation. The ruling puts thousands of digital companies at risk of non-compliance.

  To settle the matter, US and EU authorities started “peace talks” in spring 2022.

  European Commission President Ursula von der Leyen said that they are working with the Biden administration on the new agreement that will “enable predictable and trustworthy data flows between the EU and US, safeguarding the privacy and civil liberties.” 

  However, it’s just the beginning of a lengthy negotiation process. The matter is far from being settled and contentious issues remain as we discussed on Twitter (come say hi !).

  

  For one, the US isn’t eager to modify its surveillance laws and is mostly willing to make them “proportional” to those in place in the EU. These modifications may still not satisfy CJEU — which has the power to block the agreement vetting or invalidate it once again. 

  While these matters are getting hashed out, Google Analytics users, collecting data about EU citizens and/or residents, remain on slippery grounds. As long as they use GA4, they can be subject to GDPR-related lawsuits. 

  To Sum It Up 

  • Google Analytics 4 and Google Universal Analytics are not GDPR compliant because of Privacy Shield invalidation in 2020. 
  • French and Austrian data watchdogs named Google Analytics operations “illegal”. Swedish, Dutch and Norwegian authorities also claim it’s in breach of GDPR. 
  • Any website using GA for collecting data about European citizens and/or residents can be taken to court for GDPR violations (which is already happening). 
  • Privacy Shield 2.0 Framework discussions to regulate EU-US data transfers have only begun and may take years. Even if accepted, the new framework(s) may once again be invalidated by local data regulators as has already happened in the past. 

  Time to Get a GDPR Compliant Google Analytics Alternative 

  Retaining 100% data ownership is the optimal path to GDPR compliance.

  By selecting a transparent web analytics solution that offers 100% data ownership, you can rest assured that no “behind the scenes” data collection, processing or transfers take place. 

  Unlike Google Analytics 4, Matomo offers all of the features you need to be GDPR compliant : 

  • Full data anonymisation 
  • Single-purpose data usage 
  • Easy consent and an opt-out mechanism 
  • First-party cookies usage by default 
  • Simple access to collect data 
  • Fast data removals 
  • EU-based data storage for Matomo Cloud (or storage in the country of your choice with Matomo On-Premise)

  Learn about your audiences in a privacy-centred way and protect your business against unnecessary legal exposure. 

  Start your 21-day free trial (no credit card required) to see how fully GDPR-compliant website analytics works ! 

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• CD-R Read Speed Experiments

  21 mai 2011, par Multimedia Mike — Science Projects, Sega Dreamcast

  I want to know how fast I can really read data from a CD-R. Pursuant to my previous musings on this subject, I was informed that it is inadequate to profile reading just any file from a CD-R since data might be read faster or slower depending on whether the data is closer to the inside or the outside of the disc.

  Conclusion / Executive Summary
  It is 100% true that reading data from the outside of a CD-R is faster than reading data from the inside. Read on if you care to know the details of how I arrived at this conclusion, and to find out just how much speed advantage there is to reading from the outside rather than the inside.

  Science Project Outline

  • Create some sample CD-Rs with various properties
  • Get a variety of optical drives
  • Write a custom program that profiles the read speed

  Creating The Test Media
  It’s my understanding that not all CD-Rs are created equal. Fortunately, I have 3 spindles of media handy : Some plain-looking Memorex discs, some rather flamboyant Maxell discs, and those 80mm TDK discs :

  
  
  

  My approach for burning is to create a single file to be burned into a standard ISO-9660 filesystem. The size of the file will be the advertised length of the CD-R minus 1 megabyte for overhead— so, 699 MB for the 120mm discs, 209 MB for the 80mm disc. The file will contain a repeating sequence of 0..0xFF bytes.

  Profiling
  I don’t want to leave this to the vagaries of any filesystem handling layer so I will conduct this experiment at the sector level. Profiling program outline :

  • Read the CD-ROM TOC and get the number of sectors that comprise the data track
  • Profile reading the first 20 MB of sectors
  • Profile reading 20 MB of sectors in the middle of the track
  • Profile reading the last 20 MB of sectors

  Unfortunately, I couldn’t figure out the raw sector reading on modern Linux incarnations (which is annoying since I remember it being pretty straightforward years ago). So I left it to the filesystem after all. New algorithm :

  • Open the single, large file on the CD-R and query the file length
  • Profile reading the first 20 MB of data, 512 kbytes at a time
  • Profile reading 20 MB of sectors in the middle of the track (starting from filesize / 2 - 10 MB), 512 kbytes at a time
  • Profile reading the last 20 MB of sectors (starting from filesize - 20MB), 512 kbytes at a time

  Empirical Data
  I tested the program in Linux using an LG Slim external multi-drive (seen at the top of the pile in this post) and one of my Sega Dreamcast units. I gathered the median value of 3 runs for each area (inner, middle, and outer). I also conducted a buffer flush in between Linux runs (as root : 'sync; echo 3 > /proc/sys/vm/drop_caches').

  LG Slim external multi-drive (reading from inner, middle, and outer areas in kbytes/sec) :

  • TDK-80mm : 721, 897, 1048
  • Memorex-120mm : 1601, 2805, 3623
  • Maxell-120mm : 1660, 2806, 3624

  So the 120mm discs can range from about 10.5X all the way up to a full 24X on this drive. For whatever reason, the 80mm disc fares a bit worse — even at the inner track — with a range of 4.8X - 7X.

  Sega Dreamcast (reading from inner, middle, and outer areas in kbytes/sec) :

  • TDK-80mm : 502, 632, 749
  • Memorex-120mm : 499, 889, 1143
  • Maxell-120mm : 500, 890, 1156

  It’s interesting that the 80mm disc performed comparably to the 120mm discs in the Dreamcast, in contrast to the LG Slim drive. Also, the results are consistent with my previous profiling experiments, which largely only touched the inner area. The read speeds range from 3.3X - 7.7X. The middle of a 120mm disc reads at about 6X.

  Implications
  A few thoughts regarding these results :

  • Since the very definition of 1X is the minimum speed necessary to stream data from an audio CD, then presumably, original 1X CD-ROM drives would have needed to be capable of reading 1X from the inner area. I wonder what the max read speed at the outer edges was ? It’s unlikely I would be able to get a 1X drive working easily in this day and age since the earliest CD-ROM drives required custom controllers.
  • I think 24X is the max rated read speed for CD-Rs, at least for this drive. This implies that the marketing literature only cites the best possible numbers. I guess this is no surprise, similar to how monitors and TVs have always been measured by their diagonal dimension.
  • Given this data, how do you engineer an ISO-9660 filesystem image so that the timing-sensitive multimedia files live on the outermost track ? In the Dreamcast case, if you can guarantee your FMV files will live somewhere between the middle and the end of the disc, you should be able to count on a bitrate of at least 900 kbytes/sec.

  Source Code
  Here is the program I wrote for profiling. Note that the filename is hardcoded (#define FILENAME). Compiling for Linux is a simple 'gcc -Wall profile-cdr.c -o profile-cdr'. Compiling for Dreamcast is performed in the standard KallistiOS manner (people skilled in the art already know what they need to know) ; the only variation is to compile with the '-D_arch_dreamcast' flag, which the default KOS environment adds anyway.

  PLAIN TEXT

  C :

  1. #ifdef _arch_dreamcast
  2.   #include <kos .h>
  3.  
  4.   /* map I/O functions to their KOS equivalents */
  5.   #define open fs_open
  6.   #define lseek fs_seek
  7.   #define read fs_read
  8.   #define close fs_close
  9.  
  10.   #define FILENAME "/cd/bigfile"
  11. #else
  12.   #include <stdio .h>
  13.   #include <sys /types.h>
  14.   #include </sys><sys /stat.h>
  15.   #include </sys><sys /time.h>
  16.   #include <fcntl .h>
  17.   #include <unistd .h>
  18.  
  19.   #define FILENAME "/media/Full disc/bigfile"
  20. #endif
  21.  
  22. /* Get a current absolute millisecond count ; it doesn’t have to be in
  23. * reference to anything special. */
  24. unsigned int get_current_milliseconds()
  25. {
  26. #ifdef _arch_dreamcast
  27.   return timer_ms_gettime64() ;
  28. #else
  29.   struct timeval tv ;
  30.   gettimeofday(&tv, NULL) ;
  31.   return tv.tv_sec * 1000 + tv.tv_usec / 1000 ;
  32. #endif
  33. }
  34.  
  35. #define READ_SIZE (20 * 1024 * 1024)
  36. #define READ_BUFFER_SIZE (512 * 1024)
  37.  
  38. int main()
  39. {
  40.   int i, j ;
  41.   int fd ;
  42.   char read_buffer[READ_BUFFER_SIZE] ;
  43.   off_t filesize ;
  44.   unsigned int start_time, end_time ;
  45.  
  46.   fd = open(FILENAME, O_RDONLY) ;
  47.   if (fd == -1)
  48.   {
  49.     printf("could not open %s\n", FILENAME) ;
  50.     return 1 ;
  51.   }
  52.   filesize = lseek(fd, 0, SEEK_END) ;
  53.  
  54.   for (i = 0 ; i <3 ; i++)
  55.   {
  56.     if (i == 0)
  57.     {
  58.       printf("reading inner 20 MB...\n") ;
  59.       lseek(fd, 0, SEEK_SET) ;
  60.     }
  61.     else if (i == 1)
  62.     {
  63.       printf("reading middle 20 MB...\n") ;
  64.       lseek(fd, (filesize / 2) - (READ_SIZE / 2), SEEK_SET) ;
  65.     }
  66.     else
  67.     {
  68.       printf("reading outer 20 MB...\n") ;
  69.       lseek(fd, filesize - READ_SIZE, SEEK_SET) ;
  70.     }
  71.     /* read 20 MB ; 40 chunks of 1/2 MB */
  72.     start_time = get_current_milliseconds() ;
  73.     for (j = 0 ; j <(READ_SIZE / READ_BUFFER_SIZE) ; j++)
  74.       if (read(fd, read_buffer, READ_BUFFER_SIZE) != READ_BUFFER_SIZE)
  75.       {
  76.         printf("read error\n") ;
  77.         break ;
  78.       }
  79.     end_time = get_current_milliseconds() ;
  80.     printf("%d - %d = %d ms => %d kbytes/sec\n",
  81.       end_time, start_time, end_time - start_time,
  82.       READ_SIZE / (end_time - start_time)) ;
  83.   }
  84.  
  85.   close(fd) ;
  86.  
  87.   return 0 ;
  88. }

• How to calculate ffmpeg output file size ?

  25 septembre 2011, par poundifdef

  I am using ffmpeg to convert home videos to DVD format and want to calculate the output file size before doing the conversion.

  My input file has a bit rate of 7700 kbps and is 114 seconds long. The audio bitrate is 256 kbit (per second ?) The input file is 77MB. To get this information I ran :

  mplayer -vo null -ao null -frames 0 -identify input.MOD

  So in theory, the input file should have (roughly) a file size of :

  ((7700 / 8) * 114) / 1024

  That is, (7700 / 8) is kilobytes/second, multiplied by 114 seconds, and then converted to megabytes. This gives me 107MB, which is way beyond my 77. Thus I am skeptical of his formula.

  That said, after converting the video :

  ffmpeg -i input.MOD -y -target ntsc-dvd -sameq -aspect 4:3 output.mpg

  The numbers seem to make more sense. Bitrate is 9000 kbps, and applying the above formula, I get 125MB, and my actual output file size is 126MB.

  So, two questions :

  1. How do I factor the audio bitrate into this calculation ? Is it additive (video file size + audio file size) ?

  2. Do DVDs always have a 9000 kilobit/second rate ? Is that the definition of a DVD ? Or might that change depending on video quality of my input video ? What does "-target ntsc-dvd" guarantee about my video ?

  3. Why does my input file not "match" the calculation, but the output file does ? Is there some other variable I'm not accounting for ?

  What is the correct way to calculate filesize ?