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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.

• Revision 34497 : Premier jet de la categorie maintenance

  16 janvier 2010, par eric@… — Log

  Premier jet de la categorie maintenance

• Adjusting The Timetable and SQL Shame

  16 août 2012, par Multimedia Mike — General, Python, sql

  My Game Music Appreciation website has a big problem that many visitors quickly notice and comment upon. The problem looks like this :

  
  
  

  The problem is that all of these songs are 2m30s in length. During the initial import process, unless a chiptune file already had curated length metadata attached, my metadata utility emitted a default play length of 150 seconds. This is not good if you want to listen to all the songs in a soundtrack without interacting with the player page, but have various short songs (think “game over” or other quick jingles) that are over in a few seconds. Such songs still pad out 150 seconds of silence.

  So I needed to correct this. Possible solutions :

  1. Manually : At first, I figured I could ask the database which songs needed fixing and listen to them to determine the proper lengths. Then I realized that there were well over 1400 games affected by this problem. This just screams “automated solution”.
  2. Automatically : Ask the database which songs need fixing and then somehow ask the computer to listen to the songs and decide their proper lengths. This sounds like a winner, provided that I can figure out how to programmatically determine if a song has “finished”.

  SQL Shame
  This play adjustment task has been on my plate for a long time. A key factor that has blocked me is that I couldn’t figure out a single SQL query to feed to the SQLite database underlying the site which would give me all the songs I needed. To be clear, it was very simple and obvious to me how to write a program that would query the database in phases to get all the information. However, I felt that it would be impure to proceed with the task unless I could figure out one giant query to get all the information.

  This always seems to come up whenever I start interacting with a database in any serious way. I call it SQL shame. This task got some traction when I got over this nagging doubt and told myself that there’s nothing wrong with the multi-step query program if it solves the problem at hand.

  Suddenly, I had a flash of inspiration about why the so-called NoSQL movement exists. Maybe there are a lot more people who don’t like trying to derive such long queries and are happy to allow other languages to pick up the slack.

  Estimating Lengths
  Anyway, my solution involved writing a Python script to iterate through all the games whose metadata was output by a certain engine (the one that makes the default play length 150 seconds). For each of those games, the script queries the song table and determines if each song is exactly 150 seconds. If it is, then go to work trying to estimate the true length.

  The forgoing paragraph describes what I figured was possible with only a single (possibly large) SQL query.

  For each song represented in the chiptune file, I ran it through a custom length estimator program. My brilliant (err, naïve) solution to the length estimation problem was to synthesize seconds of audio up to a maximum of 120 seconds (tightening up the default length just a bit) and counting how many of those seconds had all 0 samples. If the count reached 5 consecutive seconds of silence, then the estimator rewound the running length by 5 seconds and declared that to be the proper length. Update the database.

  There were about 1430 chiptune files whose songs needed updates. Some files had 1 single song. Some files had over 100. When I let the script run, it took nearly 65 minutes to process all the files. That was a single-threaded solution, of course. Even though I already had the data I needed, I wanted to try to hand at parallelizing the script. So I went to work with Python’s multiprocessing module and quickly refactored it to use all 4 CPU threads on the machine where the files live. Results :

  • Single-threaded solution : 64m42s to process corpus (22 games/minute)
  • Multi-threaded solution : 18m48s with 4 CPU threads (75 games/minute)

  More than a 3x speedup across 4 CPU threads, which is decent for a primarily CPU-bound operation.

  Epilogue
  I suspect that this task will require some refinement or manual intervention. Maybe there are songs which actually have more than 5 legitimate seconds of silence. Also, I entertained the possibility that some songs would generate very low amplitude noise rather than being perfectly silent. In that case, I could refine the script to stipulate that amplitudes below a certain threshold count as 0. Fortunately, I marked which games were modified by this method, so I can run a new script as necessary.

  SQL Schema
  Here is the schema of my SQlite3 database, for those who want to try their hand at a proper query. I am confident that it’s possible ; I just didn’t have the patience to work it out. The task is to retrieve all the rows from the games table where all of the corresponding songs in the songs table is 150000 milliseconds.
  

  sql

  < view plain text >

  1. CREATE TABLE games
  2.   (
  3.    id INTEGER PRIMARY KEY AUTOINCREMENT,
  4.    uncompressed_sha1 TEXT,
  5.    uncompressed_size INTEGER,
  6.    compressed_sha1 TEXT,
  7.    compressed_size INTEGER,
  8.    system TEXT,
  9.    game TEXT,
  10.    gme_system TEXT default NULL,
  11.    canonical_url TEXT default NULL,
  12.    extension TEXT default "gamemusicxz",
  13.    enabled INTEGER default 1,
  14.    redirect_to_id INT DEFAULT -1,
  15.    play_lengths_modified INT DEFAULT NULL) ;
  16. CREATE TABLE songs
  17.   (
  18.    game_id INTEGER,
  19.    song_number INTEGER NOT NULL,
  20.    song TEXT,
  21.    author TEXT,
  22.    copyright TEXT,
  23.    dumper TEXT,
  24.    length INTEGER,
  25.    intro_length INTEGER,
  26.    loop_length INTEGER,
  27.    play_length INTEGER,
  28.    play_order INTEGER default -1) ;
  29. CREATE TABLE tags
  30.   (
  31.    game_id INTEGER,
  32.    tag TEXT NOT NULL,
  33.    tag_type TEXT default "filename") ;
  34. CREATE INDEX gameid_index_songs ON songs(game_id) ;
  35. CREATE INDEX gameid_index_tag ON tags(game_id) ;
  36. CREATE UNIQUE INDEX sha1_index ON games(uncompressed_sha1) ;