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• Your Essential SOC 2 Compliance Checklist

  11 mars, par Daniel Crough — Privacy, Security

  With cloud-hosted applications becoming the norm, organisations face increasing data security and compliance challenges. SOC 2 (System and Organisation Controls 2) provides a structured framework for addressing these challenges. Established by the American Institute of Certified Public Accountants (AICPA), SOC 2 has become a critical standard for demonstrating trustworthiness to clients and partners.

  A well-structured SOC 2 compliance checklist serves as your roadmap to successful audits and effective security practices. In this post, we’ll walk through the essential steps to achieve SOC 2 compliance and explain how proper analytics practices play a crucial role in maintaining this important certification.

  Download SOC2 Checklist

  

  What is SOC 2 compliance ?

  SOC 2 compliance applies to service organisations that handle sensitive customer data. While not mandatory, this certification builds significant trust with customers and partners.

  According to the AICPA, “SOC 2 reports are intended to meet the needs of a broad range of users that need detailed information and assurance about the controls at a service organisation relevant to security, availability, and processing integrity of the systems the service organisation uses to process users’ data and the confidentiality and privacy of the information processed by these systems.“

  At its core, SOC 2 helps organisations protect customer data through five fundamental principles : security, availability, processing integrity, confidentiality, and privacy.

  Think of it as a seal of approval that tells customers, “We take data protection seriously, and here’s the evidence.”

  Companies undergo SOC 2 audits to evaluate their compliance with these standards. During these audits, independent auditors assess internal controls over data security, availability, processing integrity, confidentiality, and privacy.

  What is a SOC 2 compliance checklist ?

  A SOC 2 compliance checklist is a comprehensive guide that outlines all the necessary steps and controls an organisation needs to implement to achieve SOC 2 certification. It covers essential areas including :

  • Security policies and procedures
  • Access control measures
  • Risk assessment protocols
  • Incident response plans
  • Disaster recovery procedures
  • Vendor management practices
  • Data encryption standards
  • Network security controls

  SOC 2 compliance checklist benefits

  A structured SOC 2 compliance checklist offers several significant advantages :

  Preparedness

  Preparing for a SOC 2 examination involves many complex elements. A checklist provides a clear, structured path, breaking the process into manageable tasks that ensure nothing is overlooked.

  Resource optimisation

  A comprehensive checklist reduces time spent identifying requirements, minimises costly mistakes and oversights, and enables more precise budget planning for the compliance process.

  Better team alignment

  A SOC 2 checklist establishes clear responsibilities for team members and maintains consistent understanding across all departments, helping align internal processes with industry standards.

  Risk reduction

  Following a SOC 2 compliance checklist significantly reduces the risk of compliance violations. Systematically reviewing internal controls provides opportunities to catch security gaps early, mitigating the risk of data breaches and unauthorised access.

  Audit readiness

  A well-maintained checklist simplifies audit preparation, reduces stress during the audit process, and accelerates the certification timeline.

  Business growth

  A successful SOC 2 audit demonstrates your organisation’s commitment to data security, which can be decisive in winning new business, especially with enterprise clients who require this certification from their vendors.

  Challenges in implementing SOC 2

  Implementing SOC 2 presents several significant challenges :

  Time-intensive documentation

  Maintaining accurate records throughout the SOC 2 compliance process requires diligence and attention to detail. Many organisations struggle to compile comprehensive documentation of all controls, policies and procedures, leading to delays and increased costs.

  Incorrect scoping of the audit

  Misjudging the scope can result in unnecessary expenses and extended timelines. Including too many systems complicates the process and diverts resources from critical areas.

  Maintaining ongoing compliance

  After achieving initial compliance, continuous monitoring becomes essential but is often neglected. Regular internal control audits can be overwhelming, especially for smaller organisations without dedicated compliance teams.

  Resource constraints

  Many organisations lack sufficient resources to dedicate to compliance efforts. This limitation can lead to staff burnout or reliance on expensive external consultants.

  Employee resistance

  Staff members may view new security protocols as unnecessary hurdles. Employees who aren’t adequately trained on SOC 2 requirements might inadvertently compromise compliance efforts through improper data handling.

  Analytics and SOC 2 compliance : A critical relationship

  One often overlooked aspect of SOC 2 compliance is the handling of analytics data. User behaviour data collection directly impacts multiple Trust Service Criteria, particularly privacy and confidentiality.

  Why analytics matters for SOC 2

  Standard analytics platforms often collect significant amounts of personal data, creating potential compliance risks :

  1. Privacy concerns : Many analytics tools collect personal information without proper consent mechanisms
  2. Data ownership issues : When analytics data is processed on third-party servers, maintaining control becomes challenging
  3. Confidentiality risks : Analytics data might be shared with advertising networks or other third parties
  4. Processing integrity questions : When data is transformed or aggregated by third parties, verification becomes difficult

  How Matomo supports SOC 2 compliance

  

  Matomo’s privacy-first analytics approach directly addresses these concerns :

  1. Complete data ownership : With Matomo, all analytics data remains under your control, either on your own servers or in a dedicated cloud instance
  2. Consent management : Built-in tools for managing user consent align with privacy requirements
  3. Data minimisation : Configurable anonymisation features help reduce collection of sensitive personal data
  4. Transparency : Clear documentation of data flows supports audit requirements
  5. Configurable data retention : Set automated data deletion schedules to comply with your policies

  By implementing Matomo as part of your SOC 2 compliance strategy, you address key requirements while maintaining the valuable insights your organisation needs for growth.

  Conclusion

  A SOC 2 compliance checklist helps organisations meet critical security and privacy standards. By taking a methodical approach to compliance and implementing privacy-respecting analytics, you can build trust with customers while protecting sensitive data.

  Start your 21-day free trial — no credit card needed.

• Use FFmpeg concat two video, is output video level mistake ?

  27 février, par 哇哈哈

  video1
{
    "index": 0,
    "codec_name": "hevc",
    "codec_long_name": "H.265 / HEVC (High Efficiency Video Coding)",
    "profile": "Main",
    "codec_type": "video",
    "codec_tag_string": "hev1",
    "codec_tag": "0x31766568",
    "width": 1920,
    "height": 1080,
    "coded_width": 1920,
    "coded_height": 1080,
    "has_b_frames": 2,
    "sample_aspect_ratio": "1:1",
    "display_aspect_ratio": "16:9",
    "pix_fmt": "yuv420p",
    "level": 120,
    "color_range": "tv",
    "chroma_location": "left",
    "field_order": "progressive",
    "refs": 1,
    "view_ids_available": "",
    "view_pos_available": "",
    "id": "0x1",
    "r_frame_rate": "30/1",
    "avg_frame_rate": "30/1",
    "time_base": "1/15360",
    "start_pts": 0,
    "start_time": "0.000000",
    "duration_ts": 200192,
    "duration": "13.033333",
    "bit_rate": "10794613",
    "nb_frames": "391",
    "extradata_size": 2496,
    "disposition": {
        "default": 1,
        "dub": 0,
        "original": 0,
        "comment": 0,
        "lyrics": 0,
        "karaoke": 0,
        "forced": 0,
        "hearing_impaired": 0,
        "visual_impaired": 0,
        "clean_effects": 0,
        "attached_pic": 0,
        "timed_thumbnails": 0,
        "non_diegetic": 0,
        "captions": 0,
        "descriptions": 0,
        "metadata": 0,
        "dependent": 0,
        "still_image": 0,
        "multilayer": 0
    },
    "tags": {
        "language": "eng",
        "handler_name": "VideoHandler",
        "vendor_id": "[0][0][0][0]",
        "encoder": "Lavc61.33.100 libx265",
        "timecode": "00:00:00;00"
    }
}

video2 
{
    "index": 0,
    "codec_name": "hevc",
    "codec_long_name": "H.265 / HEVC (High Efficiency Video Coding)",
    "profile": "Main",
    "codec_type": "video",
    "codec_tag_string": "hev1",
    "codec_tag": "0x31766568",
    "width": 1920,
    "height": 1080,
    "coded_width": 1920,
    "coded_height": 1080,
    "has_b_frames": 2,
    "sample_aspect_ratio": "1:1",
    "display_aspect_ratio": "16:9",
    "pix_fmt": "yuv420p",
    "level": 120,
    "color_range": "tv",
    "chroma_location": "left",
    "field_order": "progressive",
    "refs": 1,
    "view_ids_available": "",
    "view_pos_available": "",
    "id": "0x1",
    "r_frame_rate": "25/1",
    "avg_frame_rate": "25/1",
    "time_base": "1/12800",
    "start_pts": 0,
    "start_time": "0.000000",
    "duration_ts": 1309696,
    "duration": "102.320000",
    "bit_rate": "1024122",
    "nb_frames": "2558",
    "extradata_size": 2496,
    "disposition": {
        "default": 1,
        "dub": 0,
        "original": 0,
        "comment": 0,
        "lyrics": 0,
        "karaoke": 0,
        "forced": 0,
        "hearing_impaired": 0,
        "visual_impaired": 0,
        "clean_effects": 0,
        "attached_pic": 0,
        "timed_thumbnails": 0,
        "non_diegetic": 0,
        "captions": 0,
        "descriptions": 0,
        "metadata": 0,
        "dependent": 0,
        "still_image": 0,
        "multilayer": 0
    },
    "tags": {
        "language": "und",
        "handler_name": "VideoHandler",
        "vendor_id": "[0][0][0][0]",
        "encoder": "Lavc61.33.100 libx265"
    }
}

out:
{
    "index": 0,
    "codec_name": "hevc",
    "codec_long_name": "H.265 / HEVC (High Efficiency Video Coding)",
    "profile": "Main",
    "codec_type": "video",
    "codec_tag_string": "hev1",
    "codec_tag": "0x31766568",
    "width": 1920,
    "height": 1080,
    "coded_width": 1920,
    "coded_height": 1080,
    "has_b_frames": 2,
    "sample_aspect_ratio": "1:1",
    "display_aspect_ratio": "16:9",
    "pix_fmt": "yuv420p",
    "level": 186,
    "color_range": "tv",
    "chroma_location": "left",
    "field_order": "progressive",
    "refs": 1,
    "view_ids_available": "",
    "view_pos_available": "",
    "id": "0x1",
    "r_frame_rate": "30/1",
    "avg_frame_rate": "147450/5767",
    "time_base": "1/1000000",
    "start_pts": 0,
    "start_time": "0.000000",
    "duration_ts": 115340000,
    "duration": "115.340000",
    "bit_rate": "1060604",
    "nb_frames": "2949",
    "extradata_size": 2500,
    "disposition": {
        "default": 1,
        "dub": 0,
        "original": 0,
        "comment": 0,
        "lyrics": 0,
        "karaoke": 0,
        "forced": 0,
        "hearing_impaired": 0,
        "visual_impaired": 0,
        "clean_effects": 0,
        "attached_pic": 0,
        "timed_thumbnails": 0,
        "non_diegetic": 0,
        "captions": 0,
        "descriptions": 0,
        "metadata": 0,
        "dependent": 0,
        "still_image": 0,
        "multilayer": 0
    },
    "tags": {
        "language": "und",
        "handler_name": "VideoHandler",
        "vendor_id": "[0][0][0][0]",
        "encoder": "Lavc61.33.100 libx265"
    }
}


  


  output video level is 6.2 ? i wiki level refer to fps resolusion or bitrate,but not suit this output video.
0。0 ! Could Someone HELP me ?

  


  ffmpeg -i .\HEVC_1080p_30P_yellowtree.mp4 -i .\HEVC_1080p_24fps_happy.mp4 -filter_complex "[0:v][1:v]concat=n=2:v=1:a=0[outv]" -map "[outv]" -c:v libx265 concat_output.mp4

  


  ffmpeg version N-118448-g43be8d0728-20250209 Copyright (c) 2000-2025 the FFmpeg developers
built with gcc 14.2.0 (crosstool-NG 1.26.0.120_4d36f27)
configuration : —prefix=/ffbuild/prefix —pkg-config-flags=—static —pkg-config=pkg-config —cross-prefix=x86_64-w64-mingw32- —arch=x86_64 —target-os=mingw32 —enable-gpl —enable-version3 —disable-debug —enable-shared —disable-static —disable-w32threads —enable-pthreads —enable-iconv —enable-zlib —enable-libfreetype —enable-libfribidi —enable-gmp —enable-libxml2 —enable-lzma —enable-fontconfig —enable-libharfbuzz —enable-libvorbis —enable-opencl —disable-libpulse —enable-libvmaf —disable-libxcb —disable-xlib —enable-amf —enable-libaom —enable-libaribb24 —enable-avisynth —enable-chromaprint —enable-libdav1d —enable-libdavs2 —enable-libdvdread —enable-libdvdnav —disable-libfdk-aac —enable-ffnvcodec —enable-cuda-llvm —enable-frei0r —enable-libgme —enable-libkvazaar —enable-libaribcaption —enable-libass —enable-libbluray —enable-libjxl —enable-libmp3lame —enable-libopus —enable-librist —enable-libssh —enable-libtheora —enable-libvpx —enable-libwebp —enable-libzmq —enable-lv2 —enable-libvpl —enable-openal —enable-libopencore-amrnb —enable-libopencore-amrwb —enable-libopenh264 —enable-libopenjpeg —enable-libopenmpt —enable-librav1e —enable-librubberband —enable-schannel —enable-sdl2 —enable-libsnappy —enable-libsoxr —enable-libsrt —enable-libsvtav1 —enable-libtwolame —enable-libuavs3d —disable-libdrm —enable-vaapi —enable-libvidstab —enable-vulkan —enable-libshaderc —enable-libplacebo —disable-libvvenc —enable-libx264 —enable-libx265 —enable-libxavs2 —enable-libxvid —enable-libzimg —enable-libzvbi —extra-cflags=-DLIBTWOLAME_STATIC —extra-cxxflags= —extra-libs=-lgomp —extra-ldflags=-pthread —extra-ldexeflags= —cc=x86_64-w64-mingw32-gcc —cxx=x86_64-w64-mingw32-g++ —ar=x86_64-w64-mingw32-gcc-ar —ranlib=x86_64-w64-mingw32-gcc-ranlib —nm=x86_64-w64-mingw32-gcc-nm —extra-version=20250209
libavutil 59. 56.100 / 59. 56.100
libavcodec 61. 33.100 / 61. 33.100
libavformat 61. 9.107 / 61. 9.107
libavdevice 61. 4.100 / 61. 4.100
libavfilter 10. 9.100 / 10. 9.100
libswscale 8. 13.100 / 8. 13.100
libswresample 5. 4.100 / 5. 4.100
libpostproc 58. 4.100 / 58. 4.100

  


• Introducing the BigQuery & Data Warehouse Export feature

  30 janvier, par Matomo Core Team

  Matomo is built on a simple truth : your data belongs to you, and you should have complete control over it. That’s why we’re excited to launch our new BigQuery & Data Warehouse Export feature for Matomo Cloud, giving you even more ways to work with your analytics data. 

  Until now, getting raw data from Matomo Cloud required APIs and custom scripts, or waiting for engineering help.  

  Our new BigQuery & Data Warehouse Export feature removes those barriers. You can now access your raw, unaggregated data and schedule regular exports straight to your data warehouse. 

  The feature works with all major data warehouses including (but not limited to) : 

  • Google BigQuery 
  • Amazon Redshift 
  • Snowflake 
  • Azure Synapse Analytics 
  • Apache Hive 
  • Teradata 

  You can schedule exports, combine your Matomo data with other data sources in your data warehouse, and easily query data with SQL-like queries. 

  Direct raw data access for greater data portability 

  Waiting for engineering support can delay your work. Managing API connections and writing scripts can be time-consuming. This keeps you from focusing on what you do best—analysing data. 

  

  With the BigQuery & Data Warehouse Export feature, you get direct access to your raw Matomo data without the technical setup. So, you can spend more time analysing data and finding insights that matter. 

  Bringing your data together 

  Answering business questions often requires data from multiple sources. A single customer interaction might span your CRM, web analytics, sales systems, and more. Piecing this data together manually is time-consuming—what starts as a seemingly simple question from stakeholders can turn into hours of work collecting and comparing data across different tools. 

  This feature lets you combine your Matomo data with data from other business systems in your data warehouse. Instead of switching between tools or manually comparing spreadsheets, you can analyse all your data in one place to better understand how customers interact with your business. 

  Easy, custom analysis with SQL-like queries 

  Standard, pre-built reports often don’t address the specific, detailed questions that analysts need to answer.  

  When you use the BigQuery & Data Warehouse Export feature, you can use SQL-like queries in your data warehouse to do detailed, customised analysis. This flexibility allows you to explore your data in depth and uncover specific insights that aren’t possible with pre-built reports. 

  

  Here is an example of how you might use SQL-like query to compare the behaviours of paying vs. non-paying users : 

  				
                                          <xmp>SELECT  
  
  
  
  custom_dimension_value AS user_type, -- Assuming 'user_type' is stored in a custom dimension 
  
  
  
  COUNT(*) AS total_visits,  
  
  
  
  AVG(visit_total_time) AS avg_duration, 
  
  
  
  SUM(conversion.revenue) AS total_spent  
  
  
  
  FROM  
  
  
  
  `your_project.your_dataset.matomo_log_visit` AS visit 
  
  
  
  LEFT JOIN  
  
  
  
  `your_project.your_dataset.matomo_log_conversion` AS conversion  
  
  
  
  ON  
  
  
  
  visit.idvisit = conversion.idvisit  
  
  
  
  GROUP BY  
  
  
  
  custom_dimension_value; </xmp>
  
                                  
  			

  This query helps you compare metrics such as the number of visits, average session duration, and total amount spent between paying and non-paying users. It provides a full view of behavioural differences between these groups. 

  Advanced data manipulation and visualisation 

  When you need to create detailed reports or dive deep into data analysis, working within the constraints of a fixed user interface (UI) can limit your ability to draw insights. 

  Exporting your Matomo data to a data warehouse like BigQuery provides greater flexibility for in-depth manipulation and advanced visualisations, enabling you to uncover deeper insights and tailor your reports more effectively. 

  Getting started 

  To set up data warehouse exports in your Matomo : 

  1. Go to System Admin (cog icon in the top right corner) 
  2. Select ‘Export’ from the left-hand menu 
  3. Choose ‘BigQuery & Data Warehouse’ 

  You’ll find detailed instructions in our data warehouse exports guide.  

  Please note, enabling this feature will cost an additional 10% of your current subscription. You can view the exact cost by following the steps above. 

  New to Matomo ? Start your 21-day free trial now (no credit card required), or request a demo. 

  Try Matomo for Free

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