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• Transcoding hevc to h264 using GPU and scale_npp

  19 mai 2022, par JanZg

  I am trying to transcode hevc to h264 using GPU. Default input is 10 bit hevc but I also try it on 8 bit hevc. I use hevc_cuvid decoder and h264_nvenc encoder. While scaling using CPU its correct. I was also using scale_npp=w=1280:h=720:format=yuv420p and scale_cuda - > no result.

  


  Working command without using GPU to scale :

  


  /usr/local/bin/ffmpeg -y -v warning -c:v hevc_cuvid -an -sn -dn -reconnect_at_eof 1 -reconnect_streamed 1 -reconnect_on_network_error 1 -i http://1.2.3.4:8794 -c:v h264_nvenc -pix_fmt yuv420p -vf scale=1280:720 test_hevc.mp4


  


  But when I try to scale using GPU for example scale_cuda or scale_npp I get this error :

  


  Command :

  


  /usr/local/bin/ffmpeg -y -v warning -c:v hevc_cuvid -an -sn -dn -reconnect_at_eof 1 -reconnect_streamed 1 -reconnect_on_network_error 1 -i http://1.2.3.4:8794 -c:v h264_nvenc -pix_fmt yuv420p -vf scale_npp=1280:720 test_hevc.mp4


  


  Outputs :

  


  Error output with trace log level

  


  [graph 0 input from stream 0:0 @ 0x56164efb6b40] w:3840 h:2160 pixfmt:p010le tb:1/90000 fr:50/1 sar:1/1
[format @ 0x56164efb7940] Setting ‘pix_fmts’ to value ‘yuv420p’
[auto_scale_0 @ 0x56164efb9940] w:iw h:ih flags:’’ interl:0
[Parsed_scale_npp_0 @ 0x56164efb58c0] auto-inserting filter ‘auto_scale_0’ between the filter ‘graph 0 input from stream 0:0’ and the filter ‘Parsed_scale_npp_0’
Impossible to convert between the formats supported by the filter ‘graph 0 input from stream 0:0’ and the filter ‘auto_scale_0’
Error reinitializing filters!
Failed to inject frame into filter network: Function not implemented
Error while processing the decoded data for stream #0:0
[AVIOContext @ 0x56164ea41300] Statistics: 0 seeks, 0 writeouts
[AVIOContext @ 0x56164ea39c80] Statistics: 15357720 bytes read, 0 seeks
[AVHWDeviceContext @ 0x56164ea68480] Calling cu->cuCtxDestroy(hwctx->cuda_ctx)
Conversion failed!


  


  Full output with warning log level

  


  [hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[hevc @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 1 times
[hevc @ 0x555bd6e9f0c0] Error parsing NAL unit #2.
[mpegts @ 0x555bd6e85dc0] Could not find codec parameters for stream 0 (Video: hevc (HEVC / 0x43564548), none): unspecified size
Consider increasing the value for the ‘analyzeduration’ (0) and ‘probesize’ (5000000) options
[NULL @ 0x555bd6e9f0c0] PPS id out of range: 0
Last message repeated 66 times
Impossible to convert between the formats supported by the filter ‘graph 0 input from stream 0:0’ and the filter ‘auto_scale_0’
Error reinitializing filters!
Failed to inject frame into filter network: Function not implemented
Error while processing the decoded data for stream #0:0

Additional informations:

My FFmpeg Version below:

ffmpeg version N-103630-g06de593303 Copyright (c) 2000-2021 the FFmpeg developers
built with gcc 8 (Debian 8.3.0-6)
configuration: --prefix=/usr/local --enable-libtwolame --enable-libzvbi --enable-nonfree --enable-cuda-nvcc --nvccflags=’-gencode arch=compute_75,code=sm_75 -O2’ --enable-libnpp --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64
libavutil 57. 5.100 / 57. 5.100
libavcodec 59. 7.103 / 59. 7.103
libavformat 59. 5.100 / 59. 5.100
libavdevice 59. 0.101 / 59. 0.101
libavfilter 8. 9.100 / 8. 9.100
libswscale 6. 1.100 / 6. 1.100
libswresample 4. 0.100 / 4. 0.100


  


  GPU : Tesla T4

  


  System : Linux tgpu 4.19.0-17-amd64 #1 SMP Debian 4.19.194-3 (2021-07-18) x86_64 GNU/Linux

  


  Nvcc version : nvcc : NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Mon_Oct_12_20:09:46_PDT_2020
Cuda compilation tools, release 11.1, V11.1.105
Build cuda_11.1.TC455_06.29190527_0

  


  Is it possible to scale hevc using GPU and how to fix this ?
Thank You in advance.

  


• 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 ! 

  21 day free trial. No credit card required.

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  I hereby accept the terms and conditions and the data processing agreeement (DPA).

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  

  » Start improving your websites now

  

• 10 Key Google Analytics Limitations You Should Be Aware Of

  9 mai 2022, par Erin

  Google Analytics (GA) is the biggest player in the web analytics space. But is it as “universal” as its brand name suggests ?
  

  Over the years users have pointed out a number of major Google Analytics limitations. Many of these are even more visible in Google Analytics 4. 

  Introduced in 2020, Google Analytics 4 (GA4) has been sceptically received. As the sunset date of 1st, July 2023 for the current version, Google Universal Analytics (UA), approaches, the dismay grows stronger.

  To the point where people are pleading with others to intervene : 

  

  Main limitations of Google Analytics

  Google Analytics 4 is advertised as a more privacy-centred, comprehensive and “intelligent” web analytics platform. 

  According to Google, the newest version touts : 

  • Machine learning at its core provides better segmentation and fast-track access to granular insights 
  • Privacy-by-design controls, addressing restrictions on cookies and new regulatory demands 
  • More complete understanding of customer journeys across channels and devices 

  Some of these claims hold true. Others crumble upon a deeper investigation. Newly advertised Google Analytics capabilities such as ‘custom events’, ‘predictive insights’ and ‘privacy consent mode’ only have marginal improvements. 

  Complex setup, poor UI and lack of support with migration also leave many other users frustrated with GA4. 

  

  Let’s unpack all the current (and legacy) limitations of Google Analytics you should account for. 

  1. No Historical Data Imports 

  Google rushed users to migrate from Universal Analytics to Google Analytics 4. But they overlooked one important precondition — backwards compatibility. 

  You have no way to import data from Google Universal Analytics to Google Analytics 4. 

  Historical records are essential for analysing growth trends and creating benchmarks for new marketing campaigns. Effectively, you are cut short from past insights — and forced to start strategising from scratch. 

  At present, Google offers two feeble solutions : 

  • Run data collection in parallel and have separate reporting for GA4 and UA until the latter is shut down. Then your UA records are gone. 
  • For Ecommerce data, manually duplicate events from UA at a new GA4 property while trying to figure out the new event names and parameters. 

  Google’s new data collection model is the reason for migration difficulties. 

  In Google Analytics 4, all analytics hits types — page hits, social hits, app/screen view, etc. — are recorded as events. Respectively, the “‘event’ parameter in GA4 is different from one in Google Universal Analytics as the company explains : 

  

  This change makes migration tedious — and Google offers little assistance with proper events and custom dimensions set up. 

  2. Data Collection Limits 

  If you’ve wrapped your head around new GA4 events, congrats ! You did a great job, but the hassle isn’t over. 

  You still need to pay attention to new Google Analytics limits on data collection for event parameters and user properties. 

  

  These apply to :

  • Automatically collected events
  • Enhanced measurement events
  • Recommended events 
  • Custom events 

  When it comes to custom events, GA4 also has a limit of 25 custom parameters per event. Even though it seems a lot, it may not be enough for bigger websites. 

  You can get higher limits by upgrading to Google Analytics 360, but the costs are steep. 

  3. Limited GDPR Compliance 

  Google Analytics has a complex history with European GDPR compliance. 

  A 2020 ruling by the Court of Justice of the European Union (CJEU) invalidated the Privacy Shield framework Google leaned upon. This framework allowed the company to regulate EU-US data transfers of sensitive user data. 

  But after this loophole was closed, Google faced a heavy series of privacy-related fines :

  • French data protection authority, CNIL, ruled that  “the transfers to the US of personal data collected through Google Analytics are illegal” — and proceeded to fine Google for a record-setting €150 million at the beginning of 2022. 
  • Austrian regulators also deemed Google in breach of GDPR requirements and also branded the analytics as illegal. 

  Other EU-member states might soon proceed with similar rulings. These, in turn, can directly affect Google Analytics users, whose businesses could face brand damage and regulatory fines for non-compliance. In fact, companies cannot select where the collected analytics data will be stored — on European servers or abroad — nor can they obtain this information from Google.

  Getting a web analytics platform that allows you to keep data on your own servers or select specific Cloud locations is a great alternative. 

  Google also has been lax with its cookie consent policy and doesn’t properly inform consumers about data collection, storage or subsequent usage. Google Analytics 4 addresses this issue to an extent. 

  By default, GA4 relies on first-party cookies, instead of third-party ones — which is a step forward. But the user privacy controls are hard to configure without losing most of the GA4 functionality. Implementing user consent mode to different types of data collection also requires a heavy setup. 

  4. Strong Reliance on Sampled Data 

  To compensate for ditching third-party cookies, GA4 more heavily leans on sampled data and machine learning to fill the gaps in reporting. 

  In GA4 sampling automatically applies when you :

  • Perform advanced analysis such as cohort analysis, exploration, segment overlap or funnel analysis with not enough data 
  • Have over 10,000,000 data rows and generate any type of non-default report 

  Google also notes that data sampling can occur at lower thresholds when you are trying to get granular insights. If there’s not enough data or because Google thinks it’s too complex to retrieve. 

  In their words :

  

  Data sampling adds “guesswork” to your reports, meaning you can’t be 100% sure of data accuracy. The divergence from actual data depends on the size and quality of sampled data. Again, this isn’t something you can control. 

  Unlike Google Analytics 4, Matomo applies no data sampling. Your reports are always accurate and fully representative of actual user behaviours. 

  5. No Proper Data Anonymization 

  Data anonymization allows you to collect basic analytics about users — visits, clicks, page views — but without personally identifiable information (or PII) such as geo-location, assigns tracking ID or other cookie-based data. 

  This reduced your ability to :

  • Remarket 
  • Identify repeating visitors
  • Do advanced conversion attribution 

  But you still get basic data from users who ignored or declined consent to data collection. 

  By default, Google Analytics 4 anonymizes all user IP addresses — an upgrade from UA. However, it still assigned a unique user ID to each user. These count as personal data under GDPR. 

  For comparison, Matomo provides more advanced privacy controls. You can anonymize :

  • Previously tracked raw data 
  • Visitor IP addresses
  • Geo-location information
  • User IDs 

  This can ensure compliance, especially if you operate in a sensitive industry — and delight privacy-mindful users ! 

  6. No Roll-Up Reporting

  Getting a bird’s-eye view of all your data is helpful when you need hotkey access to main sites — global traffic volume, user count or percentage of returning visitors.

  With Roll-Up Reporting, you can see global-performance metrics for multiple localised properties (.co.nz, .co.uk, .com, etc,) in one screen. Then zoom in on specific localised sites when you need to. 

  

  7. Report Processing Latency 

  The average data processing latency is 24-48 hours with Google Analytics. 

  Accounts with over 200,000 daily sessions get data refreshes only once a day. So you won’t be seeing the latest data on core metrics. This can be a bummer during one-day promo events like Black Friday or Cyber Monday when real-time information can prove to be game-changing ! 

  Matomo processes data with lower latency even for high-traffic websites. Currently, we have 6-24 hour latency for cloud deployments. On-premises web analytics can be refreshed even faster — within an hour or instantly, depending on the traffic volumes. 

  8. No Native Conversion Optimisation Features

  Google Analytics users have to use third-party tools to get deeper insights like how people are interacting with your webpage or call-to-action.

  You can use the free Google Optimize tool, but it comes with limits : 

  • No segmentation is available 
  • Only 10 simultaneous running experiments allowed 

  There isn’t a native integration between Google Optimize and Google Analytics 4. Instead, you have to manually link an Optimize Container to an analytics account. Also, you can’t select experiment dimensions in Google Analytics reports.

  What’s more, Google Optimize is a basic CRO tool, best suited for split testing (A/B testing) of copy, visuals, URLs and page layouts. If you want to get more advanced data, you need to pay for extra tools. 

  Matomo comes with a native set of built-in conversion optimization features : 

  • Heatmaps 
  • User session recording 
  • Sales funnel analysis 
  • A/B testing 
  • Form submission analytics 

  

  9. Deprecated Annotations

  Annotations come in handy when you need to provide extra context to other team members. For example, point out unusual traffic spikes or highlight a leak in the sales funnel. 

  This feature was available in Universal Analytics but is now gone in Google Analytics 4. But you can still quickly capture, comment and share knowledge with your team in Matomo. 

  You can add annotations to any graph that shows statistics over time including visitor reports, funnel analysis charts or running A/B tests. 

  10. No White Label Option 

  This might be a minor limitation of Google Analytics, but a tangible one for agency owners. 

  Offering an on-brand, embedded web analytics platform can elevate your customer experience. But white label analytics were never a thing with Google Analytics, unlike Matomo. 

  Wrap Up 

  Google set a high bar for web analytics. But Google Analytics inherent limitations around privacy, reporting and deployment options prompt more users to consider Google Analytics alternatives, like Matomo. 

  With Matomo, you can easily migrate your historical data records and store customer data locally or in a designated cloud location. We operate by a 100% unsampled data principle and provide an array of privacy controls for advanced compliance. 

  Start your 21-day free trial (no credit card required) to see how Matomo compares to Google Analytics ! 

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