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• How to Choose a GDPR Compliant Web Analytics Solution

  2 mars 2022, par Matthieu Aubry — Privacy

  Since the launch of GDPR, one big question has lingered around with uncertainty – is Google Analytics GDPR compliant ? The current GDPR enforcement trend happening across the EU is certainly shedding some light on this question.

  Starting with the Austrian Data Protection Authority’s ruling on Google Analytics and more recently, CNIL (the French Data Protection Authority) has followed suit by also ruling Google Analytics illegal to use. Organisations with EU-based web visitors are now scrambling to find a compliant solution.

  The French Data Protection Authority (CNIL) has already started delivering formal notices to websites using Google Analytics, so now is the time to act. According to CNIL, organisations have two options :

  1. Ceasing use of the Google Analytics functionality (under the current conditions) 
  2. Use a compliant web analytics tool that does not transfer data outside the EU

  Getting started 

  For organisations considering migrating to a compliant web analytics tool, I’ve outlined below the things you need to consider when weighing up compliant web analytics tools. Once you’ve made a choice, I’ve also included a step-by-step guide to migrating away from Google Analytics. This guide is useful regardless of which GDPR compliant analytics provider you choose.

  Before getting started, I recommend that you document your findings against the following considerations while reviewing GDPR compliant Google Analytics alternatives. This document can then be shared with your Data Protection Officer (DPO) to get their final recommendation.

  10 key considerations when selecting a GDPR compliant web analytics tools

  Many tools will claim to be GDPR compliant so it’s important that you do your due diligence and review tools against the following considerations. 

  1. Where does the tool store data ? 

  The rulings in France and Austria were based on the fact that Google Analytics stores data in the US, which does not have an adequate level of data protection. Your safest option is to find a tool that legally stores data in the EU.

  You should be able to find out where the data is stored in the organisation’s privacy policy. Generally, data storage information can be found under sections titled “Subprocessors” and “Third-party services”. Check out the Matomo Privacy Policy as an example. 

  If you’re unable to easily find this information or it’s unclear, reach out to the organisation for more information.

  2. Does the tool offer anonymous tracking ?

  Anonymous tracking comes with many benefits, including :

  • The ability to track visitors without a cookie consent screen. Due to the privacy-respecting aspect of cookieless tracking, you don’t need to worry about the extra steps involved with compliant cookie banners.
  • More accurate data. When visitors deny tracking cookies, you lose out on valuable data. With anonymous tracking there is no data lost as you don’t need consent to track.
  • Simplified GDPR compliance. With this enabled, there are fewer steps you need to take to get GDPR compliant and stay GDPR compliant.

  For those reasons, it may be important for you to select a tool that offers anonymous tracking functionalities. The level of anonymous tracking you require will depend on your situation but you should look out for tools that allow you to :

  • Disable fingerprinting 
  • Disable user profiles 
  • Anonymise data
  • Cookieless tracking

  If you want to read more about data anonymization, check out this guide on data anonymization in web analytics.

  3. Does the tool integrate with my existing tech stack ?

  You’ll want to ensure that a new web analytics tool will play well with other tools in your tech stack including things like your CMS (content management system), eCommerce shop, etc. You should list out all the existing tools that currently integrate with your Google Analytics and check that the same integrations can be re-created with the new tool, via integrations or APIs.

  If not, it could become costly trying to connect your existing tech stack to a new solution.

  4. Does the tool offer the same features and insights you are currently using in Google Analytics ? Or more, if necessary ? 

  Just because you are moving to a new web analytics platform, doesn’t mean you have to give up the insights, reports and features you’ve grown accustomed to with Google Analytics. Ensuring that a new platform provides the same features and reports that you value the most will result in a smoother transition away from Google Analytics.

  It’s unlikely that a new tool will have all of the same features as Google Analytics, so I’d recommend listing out and prioritising your business-critical features and reports. 

  If I had to guess, you probably set up Google Analytics years ago because it was the default option. Now is your chance to make the most of this switch from Google Analytics and find a tool that offers additional reports and features that better aligns with your business. If time permits, I’d highly recommend that you consider other features or reports that you might have been missing out on while using Google Analytics.

  Check out this comparison of Google Analytics vs Matomo to see side-by-side feature comparison.

  5. Does the tool accept Google Analytics data imports ? 

  The historical data in Google Analytics is a critical asset for many businesses. Fortunately, some tools accept Google Analytics data imports so you don’t lose all of the data you’ve generated over time.

  However, it’s important to note that any data you import from Google Analytics to a new tool needs to be compliant data. I’ll cover this more below.

  6. Does the tool provide conversion tracking exports ? 

  Do you invest in paid advertising ? If you do, then tracking the conversions from people clicking on these paid ads is critical in assessing your return on investment. Since sending IP addresses or other personal information to the US is illegal under GDPR, we can only assume that this will also apply to advertising pixel/conversion tracking (e.g., Facebook pixel, Google Ads conversion tracking, etc). 

  As an example, Matomo offers conversion tracking exports so you can get a better understanding of ad performance while meeting privacy laws and without requiring consent from users. See how it works with Matomo’s conversion tracking exports. 

  7. How will you train up your in-house team ? Or can you hire a contractor ?

  This is a common concern of many, and rightfully so. You’ll want to confirm what resources are readily available so you can hit the ground running with your new web analytics tool. If you’d prefer to train up your in-house team, check the provider’s site for training resources, videos, guides, etc.

  If you’d rather hire an external contractor, we recommend heading to LinkedIn, reaching out to your community or asking the provider if they have any recommendations for contractors.

  In addition, check that the provider offers technical support or a forum, in case you have specific questions and need help.   

  8. Does the tool offer self-hosting ? (optional)

  For organisations that want full control over their data and storage location, an on-premise web analytics tool will be the preferred option. From a GDPR perspective, this is also the easiest option for compliance.

  Keep in mind that this requires resources, regular maintenance, technical knowledge and/or technical consultants. If you’re unsure which option is best for your organisation, check out our on-premise vs cloud web analytics comparison breakdown.

  Find out more about self-hosting Matomo.

  9. Is the tool approved by the CNIL for tracking without consent ?

  This is an important step for websites with French users. This step will help narrow down your selection of tools. The CNIL offers a programme to identify web analytics solutions that can be used without tracking consent. The CNIL’s list of recommended web analytics tools can act as your starting point for solutions to review.

  While this step is specific to sites with French users, it can also be helpful for websites with visitors from any other EU country.

  Benefits of consent-free tracking

  There are many benefits of tracking without consent.
  

  For one, it simplifies GDPR compliance and reduces the chances of GDPR breaches and fines. Cookie consent screens have recently been the target for EU Data Protection Authorities because many websites are unknowingly serving cookie consent screens that do not meet GDPR requirements. 

  Yet another benefit, and quite possibly the most important is more accurate data. Even if a website displays a user-friendly, lawful consent screen, the majority of users will either ignore or reject cookie consent. Legally website owners can’t track anything unless the visitor gives consent. So not having a cookie consent screen ensures that every visit is tracked and your web analytics data is 100% accurate. 

  Lastly, many visitors have grown fatigued and frustrated with invasive cookie consent screens. Not having one on your site creates a user-friendly experience, which will likely result in longer user sessions and lower bounce rates.

  10. Does the tool offer a Data Processing Agreement (DPA) ? 

  Technically, any GDPR compliant web analytics tool should offer a DPA but for the sake of completeness, I’ve added this as a consideration. Double check that any tools you are looking at provide this legally binding document. This should be located in the Privacy Policy of the web analytics provider, if not reach out to request it.

  As an example, here’s Matomo’s Data Processing Agreement which can be found in our Privacy Policy under Subprocessors. 

  That wraps up the key considerations. When it comes to compliance, privacy and customer data, Matomo leads the way. We are looking forward to helping you achieve GDPR compliance easily. Start your free 21-day trial of Matomo now – no credit card required.

  Try Matomo Cloud

  A step-by-step guide to migrating from Google Analytics

  Once you’ve identified a tool that suits your needs and your Data Protection Officer (DPO) has approved, you’re ready to get started. Here’s a simple step-by-step guide with all the important steps for you to follow :

  1. Before getting started, you should sign or download the Data Processing Agreement (DPA) offered by your new web analytics provider.

  2. Register for the new tool and configure it for compliance. The provider should offer guides on how to configure for GDPR compliance. This will include things like giving your users an easy way to opt-out of all tracking, turning on cookieless tracking or asking users for consent and anonymizing data and IP addresses, for instance.

  3. Inform your organisation about the change. Whether your colleagues use the tool or not, it’s important that you share information about the new tool with your staff. Let them know what the tool will be used for, who will use the tool and how it complies with GDPR. 

  4. Let your DPO know that you’ve removed Google Analytics and have implemented the new tool.

  5. Update your records of processing activities to include the new tool.

  6. Update your privacy policy. You’ll need to include details about the web analytics provider, where the data is stored, what data is being collected, how long the data will be stored and why the data is being collected. The web analytics tool should readily have this information for you.

  As an example, if you decide to use Matomo as your web analytics tool, we provide a Privacy Policy template for you to use on your site and a guide on how to complete your privacy policy under GDPR with Matomo. Note that these are only applicable if you are using Matomo.

  In addition, if the tool has an opt-out feature, you will also need to put the opt-out into the privacy policy (e.g., when using cookieless tracking).

  7. Now, the exciting part. Add the tracking code to your site by following the steps provided by the web analytics tool. 

  If you’re not comfortable with this step, the provider should offer steps to do this and you can share this with your web developer.

  8. Once added, login to your tool and check to see if traffic is being tracked.

  9. If your tool does not offer Google Analytics data imports or you do not need the historical data in your new tool, go to step 11. 

  To plan for your Google Analytics data migration, you’ll first need to establish what historical data is compliant with GDPR.

  For example, you shouldn’t import any data stored beyond the retention period established in your Privacy Policy or any personally identifiable information (PII) like IP addresses that aren’t anonymised. Discuss this further with your DPO.

  10. Once you’ve established what data you can legally import, then you can begin the import. Follow the steps provided by your new web analytics solution provider.

  11. Remove Google Analytics tracking code from your site. This will stop the collection of your visitors data by Google as well as slightly increase the page load speed.

  If you still haven’t made a choice yet, try Matomo free for 21-days and see why over 1 million websites choose Matomo. 

• How to install Ffmpeg fluent in LAMBDA ?

  9 octobre 2020, par Jhony code

  Hi, can you help how did you set up the library (node-fluent-ffmpeg) in a lambda function correctly ?

  


  Because i already set up the :

  


  

  • Serverless file with it's layer parameters

  


  • Uploaded the binaries to the lambda function as a layer

  


  • Already set up the FFPROBE_PATH AND FFMPEG_PATH from the lambda function

  


  


  Also the weird thing is that : the lambda function just finish working, like sending a normal response.

  


  https://user-images.githubusercontent.com/35440957/95387637-ff99a580-08be-11eb-9fc9-1498aea2e2c1.png

  


  I mean also if you could show me step by step how did you make it work in a lambda function ?

  


  You will see the following example of how i have everything setup and it still does not work :

  


  1- This is from the lambda console

  


  https://user-images.githubusercontent.com/35440957/95386867-ee03ce00-08bd-11eb-91ae-29b45bd90471.png

  


  https://user-images.githubusercontent.com/35440957/95386217-f60f3e00-08bc-11eb-9fd8-b51d1b04a81e.png

  


  2- My json dependencies

  


   "dependencies": {
    "aws-sdk": "^2.764.0",
    "aws-serverless-express": "^3.3.8",
    "fluent-ffmpeg": "^2.1.2",
    "lambduh-execute": "^1.3.0"
  }


  


  3- My serverless file

  


  `service: functionName

provider:
  name: aws
  runtime: nodejs12.x
  memorySize: 3008
  timeout: 300
  stage: live
  region: us-east-1
  environment:
    FFMPEG_PATH: /opt/ffmpeg/ffmpeg
    FFPROBE_PATH: /opt/ffmpeg/ffprobe

functions:
  api:
    handler: lambda.handler
    events:
      - s3: ${self:custom.bucket}
    layers:
      - { Ref: FfmpegLambdaLayer }

layers:
  ffmpeg:
    path: layer

custom:
  bucket: buckename



  


  4- The directory of the layer

  


  https://user-images.githubusercontent.com/35440957/95386502-6918b480-08bd-11eb-95e6-1b0b78f3a230.png

  


  5- Javascript file

  


  
const fs = require("fs");
const AWS = require("aws-sdk");
const ffmpeg = require("fluent-ffmpeg");
const s3 = new AWS.S3();

exports.handler = async (event, context, callback) => {

ffmpeg({
        source: `**Object file which i already verified it exists**`
      })
        .on("filenames", async (filenames) => {
          console.log("Uploading please wait");
        })
        .on("error", function (err) {
          console.log("Error in filenames section: " + JSON.stringify(err));
        })
        .on("end", function () {
          console.log("Screenshots taken");
        })
        .screenshots({
          count: 10,
          folder: "tmp/",
          filename: "thumbnail-at-%i.png",
          size: "1600x900",
        })
        .on("end", function (stdout, stderr) {


        })
        .on("error", function (err) {
          console.log("Error writing video to disk: " + JSON.stringify(err));
          throw "An error: " + err.message;
        });

};



  


  Expected results

  


  The dependecy must work as expected in a AWS lambda function.

  


  Observed results

  


  When using enviroment variables

  


  https://user-images.githubusercontent.com/35440957/95548905-154cbf00-09d4-11eb-8f46-f06cd012b05b.png

  


  When not using enviroment variables

  


  Lambda function just finish it's job without showing any log (Error) messages
In the cloudwatch console it just show the log that lambda finished de function succesfully (Not the expected from the dependency)

  


  I already used this dependecy locally, and it works ! but in LAMBDA it is too hard

  


  Checklist

  


  

  • [ X] I have read the FAQ

  


  • [ X] I have included full stderr/stdout output from ffmpeg

  


  • [ X] I have included the binaries from the static build and deployed it to the lambda function

  


  • [ X] I have set the enviroment variables
FFMPEG_PATH : /opt/ffmpeg/ffmpeg
FFPROBE_PATH : /opt/ffmpeg/ffprobe

  


  


  Version information

  


  

  • fluent-ffmpeg version : ^2.1.2

  


  • ffmpeg version or build : ffmpeg-git-20190925-amd64-static.tar.xz

  


  • OS : Lambda (Linux enviroment) / Node 12.x

  


  


• AR.Drone 2, ffmpeg avcodec_decode_video2( ) segmentation fault

  21 avril 2014, par mechanicalmanb

  I have been trying to decode the video stream from an AR.Drone 2.0 (http://ardrone2.parrot.com/) for a while now with no success. Despite several examples that I have been following closely (I’d paste links, but I am not allowed) I cannot escape a segmentation fault inside of the ffmpeg libavcodec library. I thought that perhaps I was making some kind of mistake in the multi-threaded structure I was building, so I cut out everything except the bare minimum you need to connect to the drone, collect a frame from the drone, and send it to ffmpeg’s avcodec_decode_video2() function.

  I compiled the ffmpeg source (I’ve actually tried three different releases !) and can get the ffplay utility to display the drone’s video TCP stream. The video lags significantly, but at least I know the drone isn’t sending me complete gibberish.

  Has anyone encountered a problem like this before ? What could be causing this segmentation fault, and what can I do about it ? Is there a way to isolate a test on ffmpeg so that I can be sure it is the library and not something I’ve been doing this entire time ?

  Thanks for your time.

  A pastebin with my code :
  http://pastebin.com/NYTf0NeT

  Some details on my ffmpeg and compiler set up :

  ffmpeg version 2.2.git Copyright (c) 2000-2014 the FFmpeg developers
  
    built on Mar  3 2014 18:05:42 with gcc 4.8 (Ubuntu 4.8.1-2ubuntu1~12.04)
  
    configuration: 
  
    libavutil      52. 66.100 / 52. 66.100
  
    libavcodec     55. 52.102 / 55. 52.102
  
    libavformat    55. 33.100 / 55. 33.100
  
    libavdevice    55. 10.100 / 55. 10.100
  
    libavfilter     4.  2.100 /  4.  2.100
  
    libswscale      2.  5.101 /  2.  5.101
  
    libswresample   0. 18.100 /  0. 18.100

  The output of my code and a backtrace at the segmentation fault :

  *********************** START ***********************
  
  
  
  
  
  
  
  booting...
  
  
  
  [h264 @ 0x604040] err{or,}_recognition separate: 1; 1
  
  
  
  [h264 @ 0x604040] err{or,}_recognition combined: 1; 1
  
  
  
  [h264 @ 0x604040] Unsupported bit depth: 0
  
  
  
  asked for 40000 bytes, received packet of 1448 bytes
  
  
  
  PaVE synchronized. YIPEEEEEEEEEEEEEEEEEEEEEEEE
  
  
  
  
  
  
  
  ---------------------------
  
  
  
  Codec : H264
  
  
  
  StreamID : 1 
  
  
  
  Timestamp : 1031517 ms
  
  
  
  Encoded dims : 640 x 368
  
  
  
  Display dims : 640 x 360
  
  
  
  Header size : 76
  
  
  
  Payload size : 17583
  
  
  
  Size of SPS inside payload : 14
  
  
  
  Size of PPS inside payload : 10
  
  
  
  Slices in the frame : 1
  
  
  
  Frame Type / Number : IDR-Frame : 31467 : slide 1/1
  
  
  
  ---------------------------
  
  
  
  
  
  
  
  
  
  gathering payload...
  
  
  
  asked for 16211 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 14763 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 13315 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 11867 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 10419 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 8971 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 7523 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 6075 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 4627 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 3179 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 1731 bytes, received packet of 1448 bytes
  
  
  
  gathering payload...
  
  
  
  asked for 283 bytes, received packet of 283 bytes
  
  
  
  payload complete, attempting to decode frame
  
  
  
  
  
  
  
  
  
  Program received signal SIGSEGV, Segmentation fault.
  
  
  
  0x00007ffff73fccba in ?? () from /usr/lib/x86_64-linux-gnu/libavcodec.so.53
  
  
  
  (gdb) bt
  
  
  
  #0  0x00007ffff73fccba in ?? () from /usr/lib/x86_64-linux-gnu/libavcodec.so.53
  
  
  
  #1  0x00007ffff73fd8f5 in avcodec_decode_video2 () from /usr/lib/x86_64-linux-gnu/libavcodec.so.53
  
  
  
  #2  0x000000000040159f in fetch_and_decode(int, parrot_video_encapsulation_t, AVCodecContext*, AVFrame*)
  
  
  
      ()
  
  
  
  #3  0x00000000004019c6 in main ()

  EDIT : I used Valgrind to try and get a better picture of the seg fault, and received the following :

  ==4730== Invalid read of size 1
  
  ==4730==    at 0x5265CBA: ??? (in /usr/lib/x86_64-linux-gnu/libavcodec.so.53.35.0)
  
  ==4730==    by 0x52668F4: avcodec_decode_video2 (in /usr/lib/x86_64-linux-gnu/libavcodec.so.53.35.0)
  
  ==4730==    by 0x40140E: fetch_and_decode(int, AVCodecContext*, AVFrame*) (main.cpp:176)
  
  ==4730==    by 0x401757: main (main.cpp:273)
  
  ==4730==  Address 0x280056c46f9 is not stack'd, malloc'd or (recently) free'd
  
  ==4730== 
  
  ==4730== 
  
  ==4730== Process terminating with default action of signal 11 (SIGSEGV)
  
  ==4730==  Access not within mapped region at address 0x280056C46F9
  
  ==4730==    at 0x5265CBA: ??? (in /usr/lib/x86_64-linux-gnu/libavcodec.so.53.35.0)
  
  ==4730==    by 0x52668F4: avcodec_decode_video2 (in /usr/lib/x86_64-linux-gnu/libavcodec.so.53.35.0)
  
  ==4730==    by 0x40140E: fetch_and_decode(int, AVCodecContext*, AVFrame*) (main.cpp:176)
  
  ==4730==    by 0x401757: main (main.cpp:273)

  "Invalid read size of 1" refers to trying to access a byte outside the bounds of an array. Does this mean that the library is trying to access something outside the bounds of an array I’m giving it ? I’ve checked the AVPkt, and that seems fine. I’m still stumped !